layout for retrofitting an electric vehicle · electric motor and mule vehicle parameter to obtain...
TRANSCRIPT
LAYOUT FOR RETROFITTING AN
ELECTRIC VEHICLE
By
Himani Mazumder
B.Sc., MBA
A thesis submitted in fulfilment of the requirements for the degree of
Doctor of Philosophy
Centre for Sustainable Infrastructure
Faculty of Science, Engineering and Technology
Swinburne University of Technology
Victoria, Australia
January 2015
Doctoral Committee:
Professor Ajay Kapoor, Principal Co-ordinating Supervisor
Dr. Mehran Ektesabi, Associate Supervisor
Dr. Clint Steele, Associate Supervisor
I
ABSTRACT
Global automotive industry is facing a great challenge in achieving an
emission-free environment. There is several alternate transportation solutions are
introduced to the industry among which the electric vehicle (EV) has created a new
paradigm in the context of zero emission schema. The Original Equipment
Manufacturers (OEMs) have taken initiatives to commercialize the EVs in a large
scale, but limitations involved with EV technology has been found as a barrier to the
rapid industrialization. The crucial limitation would be the production cost of EVs.
Retrofitting has been considered as an ideal method for the prompt adaptation of EV
by the consumers as it offers lower costs and short time-to-market. Retrofitting of
EVs possesses the concerns for the appropriate placement of the power-trained
components as it involves significant change in the weight of the vehicle. The change
in vehicle weight controls the dynamic stability of the vehicle in driving conditions.
In this context, the attention goes to the selection of suitable propulsion system,
electric motor and mule vehicle parameter to obtain a proper retrofitting system for
the vehicle. Moreover, retrofitting of EVs comprises the battery performance in
operating condition. Therefore, it is required to develop a balanced retrofitting
system which can be compatible with the dynamic characteristics and safety
concerns of the battery performance during vehicle crash.
In this study, three architectural layouts were defined for evaluation based on
the placement positions of the components. The architectural layouts led towards the
longitudinal, lateral and vertical position of centre of gravity (CG) of the retrofitted
vehicle which changed the dynamic characteristics of the vehicle in different
manoeuvring conditions. The layouts were defined considering the specification of
the mule vehicle. Analysing the dynamics of three layouts, a new architectural layout
was proposed in this research. The mule vehicle was simulated in the dynamic
conditions considering the proposed layout. The proposed layout was validated
experimentally in case of a demo vehicle in the lab. Then the proposed load
II
distribution layout was implemented in the mule vehicle model in the simulation and
the dynamic characteristics were compared with the results found in other load
distribution layouts.
Considering the new retrofitting layout, a further study on the safety analysis
of the packaging arrangement and cooling system for the battery pack was
accomplished. A novel design for the packaging and cooling system of the battery
was provided in this research. Validation of the design included the structural safety
analysis considering the vehicle crash. A whole cooling circuit integrated with the
existing components for the retrofitted vehicle was proposed in this study. The use of
existing components was to enhance the efficiency of the system by avoiding the cost
escalation. The efficiency of the designed battery cooling system was determined and
demonstrated through the fluid-solid-interface analysis process.
The research focused on a suitable and sustainable retrofitting layout
analysed based on the dynamic handling and stability of a selected vehicle parameter,
the structural safety and thermal analysis of the battery packaging arrangement and
cooling system.
III
ACKNOWLEDGEMENTS
First of all, I would like to express my sincere gratitude and
acknowledgement to my principal co-ordinating supervisor, Professor Ajay Kapoor
for his constant supervision, support, encouragement and enthusiasm providing me
theoretical and technical guidance and valuable feedback throughout these years.
I would also like to thank my associate supervisors Dr. Mehran Motamed
Ektesabi and Dr. Clint Steele for their constructive suggestions during the course of
this research.
My PhD study was financed by Automotive Co-operative Research Centre
(AUTOCRC) and Swinburne University of Technology scholarship. I hereby greatly
appreciate their contribution and provision of using the EV Lab equipment which
facilitated this research.
I would like to thank my colleagues Dr. Mehedi Hasan and Md. Shamsul
Arefin for their support in technical knowledge and software expertise.
I would like to express my sincere thanks and gratefulness to my parents for
their utmost support and encouragement for my study. I am hereby deeply indebted
to my husband and my daughter for their support and sacrifice without which I could
not have reached at this stage. I wish to express my gratitude to my family for
walking with me on this journey with the infinite love, support and encouragement.
IV
Dedicated to:
My beloved parents, Cherished husband & adorable daughter
V
DECLARATION
I declare that this thesis represents my own work and contains no material
which has been accepted for the award of any other degree, diploma or qualification
in any university. To the best of my knowledge and belief this thesis contains no
material published or written by other person except where due acknowledgement
has been made.
Himani Mazumder
January, 2015.
VI
TABLE OF CONTENTS
ABSTRACT .............................................................................................................................................. I
ACKNOWLEDGEMENTS .................................................................................................................. III
DECLARATION ..................................................................................................................................... V
TABLE OF CONTENTS ...................................................................................................................... VI
LIST OF FIGURES ............................................................................................................................ XII
LIST OF TABLES ............................................................................................................................... XV
LIST OF NOTATIONS AND ACRONYMS ................................................................................ XVII
CHAPTER 1 INTRODUCTION .......................................................................................................... 1
1.1 PROBLEM STATEMENT ................................................................................................................ 2
1.2 AIMS AND OBJECTIVES ................................................................................................................ 4
1.3 METHODOLOGY ........................................................................................................................... 4
1.4 PROJECT FLOWCHART ................................................................................................................. 6
1.5 THESIS STRUCTURE ..................................................................................................................... 8
CHAPTER 2 LITERATURE REVIEW ............................................................................................ 12
2.1 ENVIRONMENTAL ASPECTS ....................................................................................................... 12
2.2 ALTERNATIVE POWER FOR AUTOMOBILES ............................................................................... 13
2.2.1 The Hybrid and Plug-in Hybrid Vehicle ........................................................................ 14
2.2.2 Hydrogen Fuel Cell......................................................................................................... 15
2.2.3 The Full Electric Vehicle ................................................................................................ 15
2.2.4 Vehicle System Architecture ........................................................................................... 16
2.2.4.1 Electric Propulsion System ................................................................................... 16
2.2.4.2 Electric Motor ....................................................................................................... 18
2.2.4.3 Electric Motor Used in Commercial EVs ............................................................. 20
2.2.4.4 Evaluation of Existing Vehicle Architectures ...................................................... 21
2.2.4.5 Brake System ......................................................................................................... 23
2.2.4.6 Suspension System ................................................................................................ 23
2.3 VEHICLE DYNAMIC ANALYSIS .................................................................................................. 24
2.3.1 Configuration of tyres ..................................................................................................... 25
2.3.2 Road Surface Friction ..................................................................................................... 26
2.3.3 Aerodynamic Drag .......................................................................................................... 27
2.3.4 Vehicle Model and Simulation ........................................................................................ 27
VII
2.3.5 Tyre Model for longitudinal, lateral and normal forces ................................................ 30
2.4 STRUCTURAL SAFETY ANALYSIS OF BATTERY PACKAGING .................................................... 31
2.4.1 EV Batteries .................................................................................................................... 31
2.4.2 Batteries Used in Commercial EVs ................................................................................ 33
2.4.1 Packaging of EV Batteries .............................................................................................. 34
2.4.2 Analysis of Battery Packaging Design ........................................................................... 36
2.5 BATTERY COOLING SYSTEM & THERMAL ANALYSIS ............................................................... 37
2.5.1 Air and Water Cooling System ....................................................................................... 38
2.5.2 Cooling System Used in Commercial EVs ..................................................................... 39
2.5.3 Use of PCM as Cooling Material ................................................................................... 40
2.5.4 Thermal Management of Batteries ................................................................................. 41
2.6 RETROFITTING OF EVS .............................................................................................................. 44
2.7 FINDINGS ................................................................................................................................... 45
CHAPTER 3 RETROFITTED ARCHITECTURAL LAYOUT .................................................... 46
3.1 EV PROPULSION SYSTEM SELECTION ....................................................................................... 47
3.2 ELECTRIC MOTOR SELECTION .................................................................................................. 49
3.3 VEHICLE SELECTION ................................................................................................................. 51
3.4 BRAKE SYSTEM ANALYSIS ........................................................................................................ 54
3.4.1 FE Model details ............................................................................................................. 55
3.4.2 Boundary conditions and input data for the analysis .................................................... 55
3.4.1 Results and discussion .................................................................................................... 58
3.5 SUSPENSION SYSTEM ANALYSIS ............................................................................................... 59
3.6 BATTERY PACKAGING ............................................................................................................... 62
3.6.1 Selection of suitable places in the vehicle ...................................................................... 63
3.7 CAD MODEL OF THE LOAD DISTRIBUTION LAYOUTS ................................................................ 64
3.7.1 Geometry Considerations for the CAD Model ............................................................... 64
3.7.2 Front Loaded Layout (Case I) ........................................................................................ 65
3.7.1 Mid Loaded Layout (Case II) ......................................................................................... 66
3.7.1 Rear Loaded Layout (Case III) ....................................................................................... 66
3.8 LOAD DISTRIBUTION OF THE VEHICLE ....................................................................................... 67
3.8.1 Longitudinal load distribution ........................................................................................ 67
3.8.1.1 Longitudinal load distribution: case I ................................................................... 68
3.8.1.2 Longitudinal load distribution: case II .................................................................. 68
3.8.1.3 Longitudinal load distribution: case III ................................................................ 69
3.8.2 Lateral load distribution ................................................................................................. 70
3.9 VEHICLE PERFORMANCE AND EFFECT OF CG ........................................................................... 70
3.9.1 Calculation of longitudinal CG ...................................................................................... 71
3.9.2 Calculation of lateral CG ............................................................................................... 71
VIII
3.9.3 Calculation of vertical CG .............................................................................................. 72
3.10 DISCUSSION AND FINDINGS ....................................................................................................... 72
CHAPTER 4 VEHICLE DYNAMIC ANALYSIS ............................................................................ 75
4.1 POLAR MOMENT ........................................................................................................................ 78
4.2 PATH RADIUS ............................................................................................................................ 79
4.3 VEHICLE MODEL ....................................................................................................................... 80
4.3.1 Modelling Assumptions ................................................................................................... 81
4.3.1.1 Moving Load ......................................................................................................... 82
4.3.1.2 Camber Angle ....................................................................................................... 82
4.3.1.3 Angle of Inclination .............................................................................................. 82
4.3.1.4 Road Surface ......................................................................................................... 82
4.3.2 Sudden Manoeuvring Vehicle Dynamics ........................................................................ 83
4.3.2.1 The Motion Plane .................................................................................................. 84
4.3.2.2 Longitudinal, lateral and normal force ................................................................. 85
4.3.2.3 Steering Angle ....................................................................................................... 87
4.3.2.4 Velocity and Yaw rate ........................................................................................... 88
4.3.2.5 Front and Rear Slip ............................................................................................... 88
4.3.3 Vehicle Cornering Dynamics .......................................................................................... 89
4.3.3.1 Sprung and Un-sprung Roll .................................................................................. 90
4.3.3.2 Wheels Block ........................................................................................................ 90
4.3.3.3 Body Sensor Block ................................................................................................ 91
4.3.3.4 Vehicle Trajectory ................................................................................................. 92
4.3.3.5 Lateral Load Transfer – Tyre Grip ....................................................................... 93
4.4 RESULTS .................................................................................................................................... 95
4.4.1 Polar moment .................................................................................................................. 95
4.4.2 Path Radius ..................................................................................................................... 96
4.4.1 Velocity and Yaw Rate .................................................................................................... 96
4.4.2 Front and Rear Slip ........................................................................................................ 97
4.4.3 Vehicle Trajectory ........................................................................................................... 99
4.4.4 Lateral Load Transfer and Tyre Grip .......................................................................... 101
4.5 DISCUSSION ............................................................................................................................. 102
4.5.1 Analysis on polar moment and curved path radius calculation .................................. 103
4.5.2 Analysis on sudden change in manoeuvre condition ................................................... 103
4.5.3 Analysis on cornering behaviour of the vehicle ........................................................... 104
4.5.4 Comparison based on dynamic behaviour of the vehicle ............................................ 105
4.6 FINDINGS ................................................................................................................................. 105
4.6.1 The proposal of a new architectural layout ................................................................. 106
4.6.1.1 CAD Model of the proposed layout .................................................................... 106
IX
4.6.1.2 Load distribution ................................................................................................. 107
4.6.1.3 Calculation of CG ............................................................................................... 108
CHAPTER 5 EXPERIMENT RESULTS AND VALIDATION OF PROPOSED LAYOUT .. 110
5.1 EXPERIMENT SET UP ................................................................................................................ 111
5.1.1 Frictional Coefficient of the track (lab floor) .............................................................. 113
5.1.2 CG Calculation ............................................................................................................. 114
5.1.2.1 Longitudinal and lateral CG ................................................................................ 114
5.1.2.2 Vertical CG.......................................................................................................... 114
5.1.3 Measurement of turning radius .................................................................................... 117
5.1.4 Measurement of contact patch ...................................................................................... 117
5.2 EXPERIMENT AND SIMULATION RESULTS FOR THE TEST VEHICLE .......................................... 118
5.2.1 Polar Moment ............................................................................................................... 118
5.2.2 Turning Radius .............................................................................................................. 119
5.2.3 Vehicle Trajectory ......................................................................................................... 119
5.2.4 Tyre grip ........................................................................................................................ 120
5.2.5 Velocity and yaw rate ................................................................................................... 122
5.2.1 Forces on tyres .............................................................................................................. 123
5.2.2 Slip Ratio ....................................................................................................................... 125
5.3 ANALYSIS OF DYNAMIC RESULTS FOR THE TEST VEHICLE ...................................................... 126
5.3.1 Analysis based on cornering dynamics ........................................................................ 127
5.3.2 Analysis based on tyre model ....................................................................................... 127
5.4 SIMULATION OF TOYOTA CAMRY BASED ON PROPOSED LAYOUT ........................................... 128
5.5 FINDINGS ................................................................................................................................. 130
CHAPTER 6 STRUCTURAL ANALYSIS OF BATTERY PACKAGING ................................ 131
6.1 CONCEPTUAL DESIGN .............................................................................................................. 132
6.1.1 Design targets ............................................................................................................... 133
6.1.2 Geometry Definition ..................................................................................................... 134
6.1.3 Design Options .............................................................................................................. 135
6.1.4 Vehicle Crash Simulation ............................................................................................. 136
6.1.4.1 Boundary Conditions and Governing Equations ................................................ 137
6.1.4.2 Nodal force, displacement and stress during the crash test ................................ 137
6.1.5 Design Model ................................................................................................................ 141
6.2 MATHEMATICAL MODEL FOR THE TRANSIENT STRUCTURAL ANALYSIS ................................. 142
6.3 COMPUTATIONAL ANALYSIS ................................................................................................... 143
6.3.1 Material Properties ....................................................................................................... 143
6.3.2 Meshing ......................................................................................................................... 144
6.3.3 Boundary Conditions .................................................................................................... 145
X
6.3.3.1 Battery Temperature with time steps .................................................................. 145
6.4 RESULTS .................................................................................................................................. 146
6.4.1 Total deformation .......................................................................................................... 146
6.4.2 Equivalent stress ........................................................................................................... 147
6.5 DISCUSSION ............................................................................................................................. 149
6.6 FINDINGS ................................................................................................................................. 149
CHAPTER 7 THERMAL ANALYSIS OF BATTERY COOLING SYSTEM ........................... 151
7.1 BATTERY PACK CONFIGURATION ........................................................................................... 154
7.2 MATHEMATICAL MODEL ......................................................................................................... 155
7.2.1 Fluid Structure Interaction ........................................................................................... 157
7.3 COMPUTATIONAL ANALYSIS ................................................................................................... 158
7.3.1 Material Properties ....................................................................................................... 158
7.3.2 Geometry ....................................................................................................................... 159
7.3.3 Meshing ......................................................................................................................... 161
7.3.4 Boundary Conditions .................................................................................................... 163
7.3.4.1 Fluid temperature ................................................................................................ 163
7.3.4.2 Flow Domain ....................................................................................................... 164
7.3.4.3 CFX Solver Control ............................................................................................ 166
7.3.4.4 Battery Temperature with Time steps ................................................................. 166
7.3.5 Transient Thermal Analysis Module ............................................................................ 166
7.4 RESULTS .................................................................................................................................. 168
7.4.1 CFX Analysis ................................................................................................................. 168
7.4.2 Transient Thermal Analysis .......................................................................................... 170
7.5 DISCUSSION ............................................................................................................................. 172
7.5.1 Fluid Flow Analysis ...................................................................................................... 172
7.5.2 Transient Thermal Analysis .......................................................................................... 173
7.6 FINDINGS ................................................................................................................................. 174
CHAPTER 8 CONCLUSIONS AND FUTURE RECOMMENDATIONS ................................. 176
8.1 CONCLUSIONS ......................................................................................................................... 176
8.1.1 Retrofitted Architectural Layout ................................................................................... 176
8.1.2 Vehicle Dynamic Analysis ............................................................................................ 179
8.1.3 Structural Safety Analysis of the Battery Cooling System ........................................... 182
8.1.4 Thermal Analysis of the Battery Cooling System ......................................................... 182
8.2 KEY FINDINGS OF THE RESEARCH ........................................................................................... 183
8.3 FUTURE RECOMMENDATIONS ................................................................................................. 185
REFERENCES .................................................................................................................................... 187
APPENDIX .......................................................................................................................................... 194
XI
LIST OF PUBLICATIONS
Mazumder, H.; Ektesabi, M.; Kapoor, A., “Effect of mass distribution on
cornering dynamics of retrofitted EV”, IEEE International Electric Vehicle
Conference, 4-8 March 2012
Hasan, M.; Mazumder, H.; Ektesabi, M., “Vehicle modeling for electronic
stability control in a four in-wheel electric vehicle”, IEEE International Electric
Vehicle Conference, 4-8 March 2012
Mazumder, H; Hasan, M.; Ektesabi, M.; Kapoor, A., “Performance analysis
of EV for different mass distributions to ensure safe handling”, ICAEE, 26-28
December 2011
Lovatt,H., Elton, D.; Cahill, L.; Huynh, D.; Stumpf, A.; Kulkarni, A.; Kapoor
, A.; Ektesabi, M.; Mazumder, H.; Dittmar, T.; White, G., "Design procedure for low
cost, low mass, direct drive, in-wheel motor drive trains for electric and hybrid
vehicles", IECON, November 2011
Kulkarni, A.; Mazumder, H.; Ektesabi, M.; Kapoor, A., "Evaluation of
vehicle architectures for in-wheel electric vehicle drive train design”, AutoCRC
Conference, 7 July 2011
Lovatt,H., Elton, D.; Cahill L.; Huynh, D.; Stumpf, A.; Kulkarni, A.; Kapoor,
A.; Ektesabi, M.; Mazumder, H.; Dittmar, T.; White, G., "Design procedure for low
cost, low mass, direct drive, in-wheel motor drive trains for electric and hybrid
vehicles", AutoCRC Conference, 7 July 2011
XII
LIST OF FIGURES
Figure 1-1: Project Flowchart ..................................................................................... 7
Figure 3-1: Comparison based on weight and efficiency of 100 KW motors ............ 50
Figure 3-2: Thermal load input data for the analysis ................................................ 57
Figure 3-3: Boundary conditions and load applied on the disc ................................. 57
Figure 3-4: Total deformation found in the disc due to both the thermal and elastic
load .......................................................................................................... 58
Figure 3-5: Von-Mises stress and thermal strain generated under the effect of
thermal and elastic load in the disc ........................................................ 59
Figure 3-6: Total deformation (elastic) of the spring ................................................. 61
Figure 3-7: Normal stress of the spring ..................................................................... 62
Figure 3-8: Front-loaded Layout ............................................................................... 65
Figure 3-9: Mid-loaded Layout .................................................................................. 66
Figure 3-10: Rear Loaded Layout .............................................................................. 67
Figure 4-1: Forces acting on different components ................................................... 76
Figure 4-2: Forces acting on the tyres while cornering ............................................. 78
Figure 4-3: The schematic diagram of the simulation ............................................... 81
Figure 4-4: Vehicle model in sudden maneuvering condition .................................... 84
Figure 4-5: The Plane of the motion .......................................................................... 85
Figure 4-6: Steering angle for sudden maneuvering .................................................. 87
Figure 4-7: Calculation of velocity and yaw rate ....................................................... 88
Figure 4-8: Model for cornering behavior of the vehicle ........................................... 89
Figure 4-9: Sprung and un-sprung roll calculation ................................................... 90
Figure 4-10: Steering angle for cornering dynamic model ........................................ 91
Figure 4-11: Lateral force on the front (drive) and rear wheels accordingly ........... 91
Figure 4-12: The calculation of Tyre Grip ................................................................. 94
Figure 4-13: Vx & Vy (m/s Vs time sec.) accordingly for front loaded layout ........... 96
Figure 4-14: Vx & Vy (m/s Vs time sec.) accordingly for mid loaded layout ............ 97
Figure 4-15: Vx & Vy (m/s Vs time sec.) accordingly for rear loaded layout ............ 97
Figure 4-16: Yaw rate Vs time accordingly for front, mid and rear loaded layout ... 97
XIII
Figure 4-17: Front and rear slip Vs time sec. (Front load case I) ............................. 98
Figure 4-18: Front and rear slip Vs time sec. (Mid load case I) ............................... 98
Figure 4-19: Front and rear slip Vs time sec. (Rear load case) ................................ 99
Figure 4-20: Vehicle trajectory plot (Front loaded layout) ..................................... 100
Figure 4-21: Vehicle trajectory plot (Mid loaded layout) ........................................ 100
Figure 4-22: Vehicle trajectory plot (Rear loaded layout) ....................................... 101
Figure 4-23: Tyre grip Vs. Lateral Load Transfer. .................................................. 102
Figure 4-24: The proposed architectural layout ...................................................... 107
Figure 5-1: Experiment set up of the vehicle in the lab ............................................ 112
Figure 5-2: Diagram for CGH calculation .............................................................. 114
Figure 5-3: Vertical CG calculation ........................................................................ 116
Figure 5-4: The profile of contact patch of the tyre ................................................. 117
Figure 5-5: Vehicle trajectory plot (Test Vehicle).................................................... 120
Figure 5-6: Lateral load transfer over time sec. ...................................................... 121
Figure 5-7: Tyre grip of the vehicle over time sec. .................................................. 121
Figure 5-8: Vx & Vy (m/s Vs time sec.) accordingly for test vehicle ....................... 122
Figure 5-9: Yaw rate Vs time sec. for test vehicle .................................................... 122
Figure 5-10: Longitudinal force, Fx (N) on each tyre over time sec. ....................... 123
Figure 5-11: Lateral force, Fy (N) on each tyre over time sec. ............................... 124
Figure 5-12: Normal force Fzf and Fzr (N) on each tyre over time sec................... 124
Figure 5-13: Angular velocity rad/s over time sec. .................................................. 125
Figure 5-14: Total Slip, σ at front and rear tyre accordingly over time sec. ........... 125
Figure 6-1: Process flowchart of structural safety analysis of the battery packaging
and cooling arrangement ...................................................................... 133
Figure 6-2: Hollow square sections of the cooling pipe .......................................... 135
Figure 6-3: CAD model of the Outer shell and Chassis for the specification of Toyota
Camry .................................................................................................... 138
Figure 6-4: Nodal forces generated at 3 defined nodes with time ........................... 139
Figure 6-5: Nodal displacement in meshed view of the vehicle ............................... 140
Figure 6-6: Contours of effective stress (v-m) at time .............................................. 141
Figure 6-7: CAD model created using SolidWorks .................................................. 142
Figure 6-8: Tetrahedral mesh of the structure ......................................................... 145
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Figure 6-9: Temperature of the battery pack with time ............................................ 146
Figure 6-10: Total deformation in design iteration 2............................................... 147
Figure 6-11: Stress (Pa) developed in design iteration 1 ......................................... 148
Figure 6-12: Stress (Pa) developed in design iteration 2 ......................................... 148
Figure 7-1: Cooling Circuit in the front bay ............................................................ 152
Figure 7-2: Simulation Process used in FSI analysis .............................................. 153
Figure 7-3: Thermal Conductivity data of Aluminum Alloy ..................................... 158
Figure 7-4: CAD model of battery cooling system ................................................... 159
Figure 7-5: Flow path of coolant through the pipe .................................................. 160
Figure 7-6: General Mesh of the Design Model....................................................... 161
Figure 7-7: Mapped Face meshing with refinement for the coolant pipe ................ 161
Figure 7-8: RMS target value with time sec. ............................................................ 162
Figure 7-9: Domain imbalance with time sec. for refined mesh .............................. 163
Figure 7-10: Inlet, outlet and wall in CFX-Pre module ........................................... 165
Figure 7-11: Detail flowchart of FSI analysis.......................................................... 167
Figure 7-12: Temperature probes placed to get the temperature of different locations
of the battery ....................................................................................... 168
Figure 7-13: Velocity profile of the coolant fluid flow ............................................. 169
Figure 7-14: Pressure profile of coolant fluid (inlet, outlet and wall) ..................... 169
Figure 7-15: Temperature profile of pipe acting as heating/cooling interface ........ 170
Figure 7-16: Battery temperature magnitude ramp accordingly at 11.11 and 33.33
sec. ...................................................................................................... 171
Figure 7-17: Temperature data chart at four temperature probes .......................... 172
XV
LIST OF TABLES
Table 3-1: Comparison of three EV propulsion systems ............................................ 48
Table 3-2: Comparison model of different electric motors ........................................ 51
Table 3-3: Comparison of Different Vehicle Parameter (data collected from industry)
................................................................................................................. 52
Table 3-4: Vehicle specification and parameters for Toyota Camry Attara S ........... 54
Table 3-5: Parameter used in the analysis ................................................................. 55
Table 3-6: Thermo-mechanical properties of the disc material................................. 56
Table 3-7: Properties of the spring and damper ........................................................ 60
Table 3-8: Longitudinal load distribution of front loaded layout (Case I) ................ 68
Table 3-9: Longitudinal load distribution of mid loaded layout (Case II) ................ 69
Table 3-10: Longitudinal load distribution of rear loaded layout (Case III) ............ 69
Table 3-11: EV component placement and different load properties of front, mid and
rear architectural layouts ....................................................................... 73
Table 4-1: Average values of the frictional coefficient of road surface ..................... 83
Table 4-2: The aerodynamic drag force calculated for three load cases .................. 86
Table 4-3: Calculation results of polar Moment ........................................................ 95
Table 4-4: Calculation results of Path Radius ........................................................... 96
Table 4-5: Comparison on dynamic analysis results ............................................... 105
Table 4-6: Load distribution of the vehicle .............................................................. 108
Table 4-7: The longitudinal, lateral and vertical position of CG ............................ 108
Table 5-1: Drive train configuration of the test vehicle ........................................... 111
Table 5-2: Parameter of the vehicle ......................................................................... 113
Table 5-3: Load on each tyre ................................................................................... 113
Table 5-4: Experimental data and result of the vehicle ........................................... 116
Table 5-5: Contact patch and effective radius of the tyre calculation ..................... 118
Table 5-6: Summery of computational and experimental results for test vehicle .... 126
Table 5-7: Comparison of proposed layout with front and mid loaded layout ........ 129
Table 6-1: Outer dimensions of Li-Ion phosphate battery ....................................... 134
Table 6-2: Sectional properties of Grade 350 (AU standard) steel ......................... 135
XVI
Table 6-3: Material properties of concrete .............................................................. 136
Table 6-4: Mechanical properties of Aluminum Alloy ............................................. 143
Table 6-5: Mechanical properties of Grade 350 steel ............................................. 144
Table 6-6: Comparison between two design iterations ............................................ 150
Table 7-1: Battery Configuration for EV retrofitting ............................................... 154
Table 7-2: Standard Model Coefficients .................................................................. 157
Table 7-3: Material Properties of the coolant ........................................................ 158
Table 7-4: Thermal properties of aluminum alloy ................................................... 158
Table 7-5: Background physics data of the analysis model ..................................... 164
Table 7-6: Inlet boundary conditions ....................................................................... 165
Table 7-7: Outlet boundary conditions .................................................................... 166
XVII
LIST OF NOTATIONS AND ACRONYMS
CFD Computational Fluid Dynamics
FSI Fluid-Solid Interface
OEM Original Equipment Manufacturer
CG Centre of Gravity
EV Electric Vehicle
BEV Battery Electric Vehicle
HEV Hybrid Electric Vehicle
PHEV Plug-in Hybrid Electric Vehicle
ICE Internal Combustion Engine
PCM Phase Change Material
Fx Longitudinal tyre force
Fy Lateral tyre force
Fz Normal force on tyres
Fxf Longitudinal force on front tyres
Fxr Longitudinal force on rear tyres
Fyf Lateral force on front tyres
Fyr Lateral force on rear tyres
Fzf Normal force on front tyres
Fzr Normal force on rear tyres
Fa Aerodynamic drag force
FR Rolling resistance
δ Steering angle
Yaw rate
Wb Wheel base
Tr Track width
Vx Longitudinal velocity
Vy Lateral velocity
XVIII
M Vehicle weight
σx Longitudinal slip
σy Lateral slip
αf Front tyre slip angle
αr Rear tyre slip angle
lf Longitudinal distance from CG to front tyres
lr Longitudinal distance from CG to rear tyres
CGH Vertical distance from CG to ground
µ Tyre road friction coefficient
R Radius of the curved path
ρ Fluid density
K Thermal conductivity
Cp Specific heat
1
CHAPTER 1
INTRODUCTION
Environmental awareness worldwide led the automobile industry to
concentrate on the development of alternative solution which can provide emission
free transportation. The emission free transportation agenda possesses a great change
in technology for the long adopted automobile consumers. In this technological
challenge replacing the petroleum products for fuel in transportation is the main
concern. There are several solutions introduced to the industry. These alternatives are
hybrids, plug-in hybrids, full electric vehicles, hydrogen-fuel etc. Among these
solutions, full electric vehicles or the battery electric vehicles provide zero carbon
emissions, i.e. the most effective technology for the green transportation to date. But
electric vehicles (EVs) require further attention in engineering research to be a
suitable replacement of internal combustion engine vehicles for the mass market of
the automobile users worldwide. Currently, EVs are exhibiting many technological
advances. Till now, considering the growing interest of automobile consumers
towards it and the imposing facilities, rules and regulation from the Governments of
different countries in the world, the development of EVs is getting more attention.
The technological advances involves in it are creating great challenges for the
engineers to collaborate with the existing system in proceeding with the EV
development. Research on light-weight materials for the automobile body,
regenerative braking system, motor controlling techniques for the electric motor,
electronic stability controllers of the vehicle are adding new aspects to the EV
development field. The automotive OEMs all over the world are introducing new
models of commercial EVs especially the passenger vehicles such as Nissan Leaf,
Mitsubishi i-MiEV, the hybrid vehicle GM Chevy Volt, E-Buses, electric bikes etc.
But approaching towards the mass production of commercial EVs has been a
challenge for the industry due to the cost issues. The main concern with the mass
2
production of commercial EVs has been the adaption of the new technology to the
consumers. As an alternative to replace the long accepted petrol engine vehicles, EVs
are not yet established in the mass market. Though the EVs and hybrids have been
introduced as the transportation alternative for urban use within 100-120 Km of
driving range, the limited range anxiety of the consumers are still crucial for the
adaptation of the EVs commercially. The limited infrastructure for the recharging of
the EV batteries has been another obstacle to overcome the range anxiety associated
with EVs. As the mass production of EVs is not yet established to the industry, a
transition period has been going on with the commercialization of the alternative
green transportation. In this transition, the conversion of existing internal combustion
engine (ICE) vehicles to the electric drives is an effective way in terms of cost and
time to market linked with it. But more analysis requires enhancing the performance,
durability and ease of retrofitting the existing vehicles to EVs.
This research was focused on the development of a new engineering system
for retrofitting the battery EVs which included the architectural layout of placing all
the drive train components, load distribution based on the position of the
components, the packaging of battery of the vehicle and the design of the cooling
system for the battery etc. The study mainly developed a new architectural layout to
place the drive components for the EVs considering the retrofitting issues. The
dynamic behaviour of the vehicle based on the both analytical and experimental
results of different handling and stability characteristics was analysed to validate the
proposed new layout. The new layout concept was proposed for the retrofitting after
evaluating different existing load distribution layouts. Then the packaging
arrangement for the battery was designed and analysed based on the structural safety
aspects of the vehicle considering the vehicle crash situation. The cooling system of
the battery was designed considering the proposed layout in this research and the
thermal analysis was done to obtain the operating state of battery temperature.
1.1 Problem Statement The environmental requirement directs to an alternative solution for emission
free transportation. Among all solutions introduced to the automobile industry, EVs
3
have become very promising as an option with some limitations associated with it
such as range, costs and re-charging infrastructure. Considering the costs,
manufacturing time and the adaptation issues as a new technology in the well-
accepted ICE vehicle market, the retrofitting is an optimum solution at the
transitional stage. The mass production of new EVs involves a great financial
investment for the automotive OEMs, but at this stage the adaptability issue with this
new technology is creating hindrance for this investment. Retrofitting provides a
balance of trade considering the lower cost because of the use of existing chassis and
body, quick time to market. But due to the lack of dynamic performance data
involved with retrofitting, the adaptation issue is ruling the industry. Retrofitting
includes an enormous escalation in vehicle weight and effective change in weight
distribution because of the placement of the heavy battery pack. This change affects
the dynamic balance of the vehicle in driving condition. Therefore, the users come
across an uncertainty about the dynamic performance of the vehicle. Installing the
stability controller in the retrofitted vehicle can be a way to solve the handling
problem of the vehicle, though the increase of cost involved is a crucial concern with
retrofitting. In this regard, regulating the dynamic handling characteristics of the
retrofitted vehicle is becoming more important. The load distribution layout by
placing the EV drive train components in different locations of the vehicle is the
most effective solution to control the vehicle handling characteristics. As retrofitting
involves using an existing vehicle, it is important to select a suitable vehicle
parameter and drive train system to obtain a better result. The selection of suitable
vehicle parameter for retrofitting is mainly based on small but enough space to place
the battery pack. Another concern is the compatibility of the existing brake and
suspension system with the added vehicle weight. The research focuses on the cost
effective way to solve the dynamic performance of the retrofitted vehicle and
determines the effective load distribution and architectural layout considering
different manoeuvring conditions.
As retrofitting has not yet accepted in the automobile industry commercially,
the proposed structure is required to be an all-inclusive system which considers all
the components of retrofitting such as battery packaging arrangement, cooling
system, the cooling circuit of the retrofitted vehicle. The battery pack for the EV
4
propulsion plays a significant role in this process because it requires to be
accommodated in the limited and existing space of the vehicle with the massive
weight and volume of it. Therefore, the proper packaging arrangement for the battery
with the cooling system has become another vital issue for retrofitting with
consideration of structural and thermal safety.
1.2 Aims and Objectives As previously mentioned, the retrofitting system for EV is required to
consider all of the components of it to get this technique well accepted by the
industry. On the other hand, the cost issues restrain the installation of new generation
technology like electronic stability controller to regulate the dynamic handling
characteristics of the vehicle.
The main objective of this research is to obtain an entire retrofitting layout
which can take care of all the basic concerns of retrofitting. The aim of the study is to
determine a suitable architectural layout at which the retrofitted vehicle can
demonstrate a stable dynamic behaviour in different manoeuvring conditions. The
study provides the vehicle performance analysis based on the dynamic characteristics
data of centre of gravity, polar moment, radius of the cornering path of the vehicle,
slip of the tyres in different manoeuvres. The research proposes an architectural
layout and provided experimental results to validate the proposal. Other retrofitting
concerns such as the packaging arrangement and cooling system of the battery pack
are designed and analysed in this study to verify the feasibility of the proposal and to
obtain a total retrofitting layout.
1.3 Methodology Prior to any numerical and experimental analysis on dynamic handling
characteristics in different manoeuvring conditions, appropriate EV propulsion
system, electric motor, mule vehicle including specification and parameter is
evaluated and selected for this study. Accordingly, finite element analysis for the
existing mechanical brake and suspension coil spring is performed in ANSYS as a
preliminary stage to provide the feasibility of the retrofitting system. Based on the
5
selected components for EV drive train, three basic architectural layouts have been
evaluated in terms of dynamic stability of the vehicle. For this evaluation, a vehicle
model is created using MATLAB SIMULINK which can demonstrate different
dynamic characteristics of the vehicle in different manoeuvring conditions. Based on
the results obtained from this SIMULINK vehicle model, a new architectural layout
has been proposed to obtain a more suitable solution for retrofitting. Experimental
data is collected and analysed for the proposed architectural layout and the tyre
model is created to demonstrate the dynamic behaviour of the vehicle with proposed
layout in given manoeuvring condition.
The battery packaging arrangement is designed using the concept of
proposed architectural layout of the retrofitted vehicle. The configuration of the
suitable battery pack is determined considering the power requirement of the mule
vehicle. The feasibility of the design is then verified through the finite element
analysis using LS-DYNA and ANSYS. To create the appropriate inputs for the
structural safety analysis of the battery packaging arrangement, the vehicle crash is
simulated in ANSYS LS-DYNA. The effect of the sudden impact on the battery
packaging arrangement due to the crash is examined considering two design
iterations. Two design iterations are constructed based on the selection of Australian
standard of structural sections for the coolant pipe. The results of the analysis
determine the proper choice for the retrofitting system.
The battery cooling system is designed by facilitating the existing
components of the vehicle. The total cooling circuit of the vehicle is demonstrated in
this study based on the concept developed for proposed architectural layout. The FSI
analysis is performed to obtain the efficiency of the cooling system for the battery
pack. The temperature of the fluid flow is determined from the CFD analysis of the
coolant fluid and then the flow body temperature is coupled to the solid battery
structure. The initial solid body temperature is given as input in the thermal analysis
module for the battery. The given temperature profile is followed by the average
range of the selected battery configuration. The analysis results based on the
temperature data are obtained for different points of the battery pack due to the
coolant fluid flow temperature.
6
1.4 Project Flowchart The study provided a balanced and stable system for retrofitting of the
selected vehicle specification. The assumptions made for the analysis were based on
the availability of the study resources and the simplification of the simulation model
and analysis. A flowchart was demonstrated in Figure 1-1 to display the process
integration of the retrofitting of this EV research project. The process flowchart
shows that background research and automotive industry data determined the drive
train accessories selection of the retrofitting. The selected parameter of the vehicle
calculated the load distribution and the CG of the vehicle from which three basic
loading conditions of the retrofitted vehicle were chosen for dynamic analysis such
as front-loaded (Case I), mid-loaded (Case II) and rear-loaded (Case III). To perform
the vehicle dynamic analysis two different manoeuvring conditions such as sudden
change in steering (Manoeuvre 1) while driving at a speed and cornering (Manoeuvre
2). Dynamic analysis results for these two manoeuvring conditions were evaluated in
case of selected vehicle parameter and validated experimentally in case of a
demonstration vehicle in the lab. After evaluation of dynamic analysis results a new
architectural layout for the vehicle loading was proposed. For this proposed layout,
transient thermal and structural analysis were accomplished for the battery packaging
and cooling system.
7
Figure 1-1: Project Flowchart
8
1.5 Thesis Structure The main focus of the research was to obtain an optimum architectural layout
for retrofitting an electric vehicle in which the battery packaging and cooling system
concerns would also be considered. In the CHAPTER 1, the basic concerns behind
the industry interest towards EVs including the environmental aspects, the balance of
trade with different fuel alternatives, retrofitting pros and cons are enlightened. The
study is conceived as having 7 major chapters which are briefly discussed here with a
general orientation of the overall approach.
CHAPTER 2 describes the background literature regarding environmental
aspects, brakes and suspension analysis, theory of vehicle motions for dynamic
analysis, the forces acting on the vehicle, tyre modelling, vehicle crash analysis,
structural analysis of the solid, cooling system of the battery, operating temperature
of the battery during charging and discharging condition, the fluid solid interface
analysis, computational fluid dynamic analysis of the coolant and the temperature of
the solid under the effect of fluid temperature. Literature review found the gap in the
research trend of EV development in focusing on retrofitting and other feasibility
issues associated with it.
CHAPTER 3 focuses on the evaluation and selection of power train
accessories of the vehicle such as electric motor, propulsion system, outer
dimensions and other specifications of the vehicle. Different propulsion system for
EV were compared based on connection diagram, transmission power loss,
packaging cost, space savings, motor packaging arrangement and weight impact.
Three propulsion systems for EV were evaluated. Those are: conventional, by-wheel
and in-wheel propulsion system. Among these, the in-wheel propulsion system was
chosen for this retrofitting study. To select the proper electric motor for retrofitting
of the vehicle, the brushed DC motor, induction motor, permanent magnet motor and
switch reluctance motor were evaluated based on efficiency, space and power to
weight ratio according to the literature review. Vehicle specification was selected by
comparing the market data of small, medium and SUV sector vehicles. Toyota
Camry 2.4L sedan was selected for the conversion. Removed and added weight items
were defined with the corresponding weight for retrofitting of the selected vehicle.
9
The brake and suspension system of the selected vehicle was analysed considering
the extra weight due to the retrofitted weight of the vehicle. Three architectural
layouts depending on the placing of the battery, motor and motor controller in
different locations of the vehicle were selected for evaluation based on the dynamic
behaviour. Load distribution ratio and the position of centre of gravity of the vehicle
were calculated for three architectural layouts to proceed on the vehicle dynamic
analysis.
CHAPTER 4 concentrates on the vehicle dynamic analysis considering three
architectural layouts. Forces acting on the vehicle due to the motor power, tyre-road
interface friction, wind, gravity etc. were calculated for change in CG position due to
different architectural layouts. Two different manoeuvring conditions were
considered to simulate the dynamic handling and stability characteristics of the
vehicle which were sudden change in steering while driving and cornering of the
vehicle at a speed. Polar moment, turning radius in the dynamic condition of the
vehicle were calculated. Vehicle model was prepared assuming some driving
constraints such as road surface friction, inclination and camber of the path. In
sudden change in manoeuvre, the longitudinal and lateral velocity of the vehicle, slip
of the tyre at front and rear and yaw rate were calculated to compare three layouts. In
cornering analysis, the curved path followed by the vehicle, slip angles at the tyre,
lateral load transfer due to the centrifugal force and grip of the tyre based on that
were considered for evaluating the results in case of three layouts. The analysis was
done considering the Toyota Camry 2.4L sedan. The results for three load layouts are
evaluated and then this chapter proposes a new architectural layout based on placing
the EV drive train components in different locations.
CHAPTER 5 studies the new proposed architectural layout based on
experiment and vehicle model simulation. For experimental validation, a
demonstration vehicle was used in the lab to do the experiment in obtaining dynamic
behaviour of the vehicle in given manoeuvring condition. The load distribution and
CG data were collected from the test vehicle and experiment was accomplished to
calculate the dynamic characteristics which were compared with the simulation
results. Based on the experimental data collected from the test vehicle, the polar
moment, vehicle path, tyre grip, velocity of the vehicle were calculated using the
10
simulation modelled in chapter 4. Tyre model was simulated to get the forces acting
on each tyre and the slip ratio. All the computational and experimental results data
were compared and analysed in context of the proposed architectural layout for
retrofitting of EV. After validating the proposed architectural layout, this chapter
provides the analysis result for Toyota Camry by using the proposed load distribution
and compares the with other load distribution layouts.
CHAPTER 6 demonstrates the design model of battery cooling system from
the conceptual stage to the structural safety analysis. The safety analysis considered
the vehicle crash for the design constraint of the cooling system and packaging of the
battery arrangement. In the conceptual design stage, the design targets, geometry
definition and design options were fixed. In determining the dimension of the cooing
duct for the battery cooling system, two sets of standard pipe dimensions were
designated for the design. Two design iterations were analysed and evaluated for the
cooling system design. The vehicle crash simulation was done considering the outer
shell and the chassis of the vehicle. Collecting the required data from the crash
simulation the transient structural analysis was performed to obtain the safety
analysis results for the battery packaging and cooling system. The design of
packaging arrangement and the cooling system of the battery was based on the
architectural layout proposed earlier. In the analysis result, the design life or
durability of the packaging and cooling system of the battery was also provided. The
analysis results were collected for two design options from which the best suitable
one was chosen.
CHAPTER 7 discusses the thermal analysis of the battery cooling system.
The thermal management of the battery pack in the operating condition of the electric
vehicle were considered as the crucial part for the state of health of the battery.
Battery pack configuration was selected to suit the power train requirement of the
Toyota Camry Attara sedan vehicle. Then the battery packaging arrangement of the
vehicle was designed considering the proposed architectural layout. In the
computation fluid dynamic analysis in obtaining the temperature effect of the cooling
fluid on the discharging temperature of the selected battery pack, the fluid solid
interface theory was applied. In the fluid solid interface, the results data were
collected from the fluid flow analysis and imported into the transient thermal
11
analysis system to obtain the impact of the fluid temperature on the temperature of
the battery. The boundary conditions were designated for the thermal analysis both in
fluid flow analysis and the transient thermal analysis. The results found from the
both analysis were discussed in terms of the requirement of the retrofitting.
CHAPTER 8 describes the conclusions and the future recommendation based
on this study. The core objectives and methodology of the study are summarized and
a conclusion on the main results is presented. The limitations of the current study are
pointed out and recommendations are made for future works.
12
CHAPTER 2
LITERATURE REVIEW
2.1 Environmental Aspects In recent years, global warming, climate change and environmental pollution
were the major concerns in automobile industry worldwide. According to global
annual green-house gas emissions by sector report 2013, the automobile industry
associated with its supply chains (transportation fuels and fossil fuel retrieval-
processing- distribution) caused around 50% of the annual greenhouse gas emissions.
CO2 (Carbon-Dioxide) gas consisted of the main portion of the greenhouse gas
emissions and automotive sector was the major source of CO2 emissions. Several of
the world’s major automotive markets adopted policies to reduce vehicle-related
CO2 emissions. In the typical life cycle of an automobile 75% of automotive-related
emissions were occurred during vehicle use (19% during fuel production, 4% during
the production of materials/components, and 2% during assembly work). In fact, of
all land-based modes of transport, vehicles were the most energy intensive with
petrol-powered vehicles consuming in aggregate more energy and producing more
greenhouse gas emissions than any other type of vehicle. Thus, fuel economy and
CO2 emission standards offered the best prospect for reducing vehicles’ contribution
to climate change. Moreover, the vehicles were a major cause of acid rain. Road
transport accounted for 48% of NO2 emissions in OECD (Organization for Economic
Cooperation and Development) countries on average, and around 60% of this was
accounted for by the automotive sector (Jain, 2009, Michalek et al., 2004).
According to the Department of climate change and energy efficiency
Australia (DCCEE, Australia) report 2012, transport emissions caused around 15%
of Australia’s total domestic emissions which was 85 Mt CO2-e in 2011. Based on
data collected from 2011 NGGI 1990 levels SGLP (2011) and CSIRO (2011),
DCCEE found the estimated carbon emissions in transportation sector in the duration
13
of 1990 – 2030 would be increasing from 60 to 102 Mt CO2-e without carbon price.
They estimated this range would be 62 to 89 Mt CO2-e considering the carbon price.
Transport emission consisted of several subsectors such as road transport, domestic
aviation, domestic shipping, rail, off-road recreational etc. Among these, the road
transport subsector was found as the largest contributor in transport emissions which
was 85% (73 Mt CO2-e). Private light transport vehicles which were not covered by
the carbon price alone contributed 42 Mt CO2-e which was almost 50% of the total
transport emissions. So, changes in carbon price would not have significant effect on
the increasing trend of the transport emissions. This resulted into the consideration of
the alternative fuel solution for the light transport vehicles. While demand for less
emissions, bio-diesel was initiated to be adopted by the heavy vehicles which were
covered by the carbon price. But there were some limitations to adopt biodiesel for
the heavy vehicles and the light vehicles as well because of the required
infrastructure for the commercialization whereas only the diesel fuelled light vehicles
could be converted into the biodiesel vehicles. This solution would not have a
significant impact on the demand of less emission because less percentage of the
existing light vehicle was on diesel fuel. In these circumstances, in both carbon price
scenarios the attention went to the falling costs of hybrid and electric vehicles
competitive with internal combustion engine vehicles (Hickman et al., 2010,
Laschober et al., 2004, Morawska et al., 2005).
2.2 Alternative Power for Automobiles Intensive focus on the energy initiatives led to other solutions of alternative
power for automobiles. The most touted alternatives were hybrids, plug-in hybrids,
hydrogen fuel cell vehicles, full electric vehicles (Battery electric vehicles). All of
these alternatives included some limitations such as range, infrastructure, costs
compared to ICE vehicles. Although the environmental concerns were very crucial in
automobile industry, the commercialization of these alternative technologies was not
getting much adopted due to the associated limitations. Despite the limited number of
these vehicles on the roads, market research estimated 3.1% of global auto sales will
be EVs and plug-in HEVs by 2017 (Butler et al., 1999, Chan, 2002).
14
2.2.1 The Hybrid and Plug-in Hybrid Vehicle
The hybrid, plug-in hybrid electric vehicles (HEVs) were widely publicised
as the apparent solution to the global carbon emission concerns as a substitute to the
conventional petrol engine vehicles that could lower the fuel usage and toxic
emissions. Having perspective of the consumers, automotive OEMs (Original
Equipment Manufacturers) had taken the environmental issues under consideration.
In the early 1990s, the management of Toyota decided that the company should
address environmental sustainability as a key challenge. In 1994 the company started
designing a vehicle to be twice as fuel efficient as existing vehicles and the result
was the Prius sedan. Launched worldwide in 1997, and now in its second generation
model, it achieved twice the fuel economy of similar sized vehicles, released one
tenth the carbon monoxide, hydrocarbon and NO2 emissions and only half the CO2
emissions. It worked by using a hybrid petrol/electric engine. Toyota has also
developed and brought to market a vehicle using a hydrogen fuel-cell engine that
developed 90kw of power and emits only water vapour (UNEP and ACEA 2002: 30;
National Roads and Motorists Association 2003: 47). In 1997, Daimler-Benz
committed to create hydrogen fuel-cell engines, with forecast annual production of
100,000 vehicles per annum powered by these engines by 2005. Ford later joined the
venture (Hawken et al, 1999: 26; Suzuki and Dressel 2002: 291). The Volkswagen
Lupo achieved fuel consumption of only 3 litres/100km, and the company had plans
to develop models that achieve 2 and 1 litre/100km (Hawken et al, 1999: 26). PSA
Peugeot Citroen had improved its diesel engines to the point where they deliver 40%
better fuel economy than a similar petrol engine and emissions were so low that a
diesel Peugeot 607 produced particulate emissions that registered at the lowest
measurable level of 0.004g/km, over 12 times lower than the limit required by
European legislation (UNEP and ACEA 2002: 31). HEVs had been the most popular
choice till date with Toyota Prius or Ford Fiesta in the market. Depending on the fuel
economy, durability, comparative price with ICE vehicles, safety HEVs had a much
larger impact on the automobile sales. HEVs included the electric motor to drive the
vehicle at low speeds or in traffic and the combustion engine to drive the vehicle in
15
highway cruising at high speed or during hill climbing situation when required power
was very high (Chan, 2007, Decarlo et al., 2000).
2.2.2 Hydrogen Fuel Cell
Hydrogen fuel cell was a very promising option for green transportation.
Hydrogen fuel required the conversion set up of other fuels on board mounted in the
vehicle. Extracting hydrogen to supply in the fuel cell had been under research for
many years. In accordance with the usual natural gases (methanol, methane, propane,
octane are usually used), some research were accomplished in using a combination of
oxidation and steam reforming in the conversion process. These conversion methods
produced a substantial amount of pollution such as CO2. To avoid this CO2 emission,
the electrolysis method could be used to produce hydrogen which is involved with
mainly solar and wind energy. But this method was not cost effective to be
implemented widely (Lixin, 2009, Van Mierlo and Maggetto, 2007, Jain, 2009).
2.2.3 The Full Electric Vehicle
The full electric vehicles or battery electric vehicles consisted of electric
motor for power generation and the battery for storing of the generated power. It did
not include any engine or engine driven accessories for the drive train of the vehicle.
It possessed zero emissions. The commercialization of full EVs required huge
development in infrastructure for the charging facility of the battery. In this case, the
lack of infrastructure, limited range and high upfront costs were discouraging the
potential consumers. To date, EV’s in comparison with ICE vehicles, HEVs,
hydrogen fuel cells had intrinsic advantages such as EVs emit no tailpipe pollutants,
although the power plant producing the electricity might emit them. To meet the
lower carbon constraints target, commercialization of EV required more attention.
The commercialization of EV had two factors for consideration. One was the new
production of EVs and another one was the retrofitting which was the converting of
existing ICE vehicles to the full EVs. New EV from manufacturer was relatively
expensive in comparison with conventional ICE vehicles as automotive OEM’s were
not going for mass production of new EV due to adaptation issues. Because of the
cost concerns, new production of EV was not getting commercialized as required. At
16
this stage, retrofitting of existing vehicles to electric drives was a feasible solution
for rapid adaptation of EV as cost and time involved in retrofitting was much lower
than that of new production. Though retrofitting of the vehicle required further
research on the performance of the vehicle in terms of range, infrastructure,
durability and maintenance. But for the time being, concerns regarding vehicle
performance, cost and infrastructure were still vital in case of retrofitting (Chan,
2007, Lixin, 2009).
HEVs eliminated the "range anxiety" associated with Full-EVs, because the
combustion engine could work as a reserve when batteries to be depleted. In these
circumstances, technology, economic context, and environmental issues were all
aligning to create a more commercial backdrop for EVs.
2.2.4 Vehicle System Architecture
The evaluation and determination of vehicle system architecture was
important for the retrofitting of a vehicle. In the case of retrofitting, it was preferable
to avoid modifications of the automobile body or the existing arrangement of other
systems such as brakes and suspension to avoid cost escalation and associated
handling risk. The retrofitting process involved the removal of engine-driven
accessories and the instalment of electric-drive components to replace the drive train.
It was important to check if the existing suspension, brakes system was able to
handle the modified vehicle load after replacing the engine driven accessories. In this
process the vehicle system architecture was required to be evaluated and analysed to
attain the optimum solution for the retrofitting condition. Vehicle system architecture
included vehicle propulsion system, electric motor and controllers, outer dimensions
and power requirement of the vehicle, brakes and suspension system (Islam, 1999).
Previous works focused on the evaluation of electric propulsion system, motors,
outer body dimension etc. though the evaluation based on the retrofitting criteria in
this research was needed.
2.2.4.1 Electric Propulsion System
Electric propulsion system chose the orientation of the drive components in
the vehicle. It selected the quantity of each item, position of them and connecting
17
diagram of the components. While retrofitting it was very important to select the
position of all EV drive train components because allocation of space required for
each item was the main concern (M. Ehsani; K., 1997). During retrofitting the more
compact the power train selected then the more space could be allocated for batteries
to ensure the maximum range for a single charge. Power train had some design
factors such as, power requirement to propel the vehicle, power to weight ratio of the
motor etc. These factors determined the number of motor required for propulsion
which was very important for the space allocation while retrofitting of the vehicle.
Another significant consideration was the transmission types (direct or indirect
drive). It decided the position of the motor in the power train. It also determined the
requirement of transmission gear and the position of it in the drive train. Depending
on the position of the electric motor, the number of motors and transmission types
(direct or indirect), conventional, by-wheel (direct or indirect drives), in-wheel
(direct or indirect drives) propulsion system were evaluated in many articles (King,
1997, Tseng and Chen, 1997).
Conventional propulsion included the electric motor at the centre with the
transmission system connected to the front and rear axles and the wheels. The power
generated from the motor was transmitted to the drive wheels through the
transmission gear box. Space requirement of conventional propulsion system to
accommodate on board was more than other propulsions because transmission gear
box needs to be installed. One of the disadvantages with conventional propulsion
system was power losses caused during transmission of power to the wheels. In by-
wheel drive train system there were two motors installed one on each wheel as the
motor is fitted by the wheel. In this type each motor ran individually to supply power
and drive wheel. There was less transmission loss found in this system compared to
conventional type propulsion. Advantage of this propulsion system was it did not
require any packaging unlike in-wheel drive train propulsion. In-wheel motor drive
has the maximum torque generation, as the motor was fitted inside the wheel. A
major advantage of in-wheel motors was energy efficiency. Having a motor inside
the wheel reduced losses during power transmission, since the packaging of
gearboxes, differentials and drive shafts became redundant. This simplified design,
thus reduced weight, volume and space. Regenerative breaking could also be
18
incorporated more effectively as each drive wheel could be operated independently
(Rahman et al., 2006, Caricchi et al., 1994, Rahim et al., 2007, Chung, 2008, Cakir,
2006).
2.2.4.2 Electric Motor
The main component of the EV system was considered its electric motor.
Vehicle operation consisted of three segments: the initial acceleration, driving at
vehicle rated speed, cruising at the maximum speed of the vehicle. These were the
basic design constraint of EV system. While retrofitting, there were some design
variables which needed to be taken under consideration: electric motor power rating,
motor rated speed, size of the motor, motor weight, motor maximum speed,
maintenance requirement, constant power speed range beyond the rated speed etc.
An electric motor was also an important selection criterion for vehicle architecture in
terms of weight, size, efficiency and the power required. Vehicle performance was
mainly depended on the acceleration of the vehicle which was evaluated by the time
required to accelerate from zero speed to a given speed and the highest speed that the
vehicle could reach. In EVs, electric motor delivered the torque to the drive wheels.
Hence, vehicle performance was completely based on the power and efficiency
characteristics of the electric motor. Weight was another crucial consideration in this
case. As the motor was to be mounted inside the wheel, the motor weight became a
significant factor of the un-sprung weight of the retrofitted vehicle. To suit the in-
wheel technology, motor size was also an important consideration. Based on power,
efficiency, cost, weight, size and maintenance requirement, several electric motors
such as the brushed DC motor (BDC Motor), induction motor (IM), Permanent
Magnet (PM) and switched reluctance motor (SRM) were evaluated by many
researchers. For the similar amount of power generation, weight and efficiency of
these motors were focused in comparison. The BDC motor could achieve high torque
at a low speed, which was suitable for the traction requirement and costs less. It
could be wired directly to DC power, which made the controller simple. A 100 KW
BDC motor was typically 75-85% efficient. It weighed about 70 kg, but the power to
weight ratio, maintenance requirements due to brushes and the size of this motor
made it inappropriate for in-wheel technology as it created electromagnetic noises.
19
IM was an asynchronous AC motor where the shape of the rotor bars determined the
speed-torque characteristics. IM’s were well-known for their low maintenance, lower
cost and durability. The efficiency of a 90-125 KW IM was found around 93-95%
and weight was 40-45 kg. However, it had a low starting torque and its speed was
determined by supply frequency, which made the controller costly. PM possessed a
compact design, long life-span and low maintenance as there were no brushes. PM
motor design required high quality permanent magnets that were expensive and use
rare-earth materials. Use of cheaper permanent magnets led to poor motor
performance, particularly in an automotive environment where extreme ambient
temperatures caused significant variation in magnet strength. A 100 KW PM Motor
was around 88-93% efficient and 30-35 kg weight. The construction of SRM had no
brushes or permanent magnets, and the rotor had no electric currents. Instead, torque
was generated from a slight miss-alignment of poles on the rotor with poles on the
stator. The efficiency of a 100 KW SRM was about 90-92% and the weight was
around 50 kg. In the literature, it was noticeable that the difference among these
motors in terms of different characteristics for the similar power generation (Lee,
2001, Rahman et al., 2000, Ehsani, 1999, Zeraoulia et al., 2006, Terashima et al.,
1997, Xue, 2008, R., 2001).
In-wheel motor system using hall sensor type BLDC motor was developed
and applicability of this on electric vehicle needs performance testing (Chung, 2008).
By early 2000 many research were carried across globe for EV drive trains and in
wheel designs using permanent magnets (Caricchi et al., 1996, Terashima et al.,
1997). Different motors were compared for switched reluctance type and technology
was made available to be extended across to EV technology (Giesselmann, 1996).
Six poles slot less axial-flux PM motor prototype was used in electrical scooter, had
45 Nm peak torque, 6.8 kg active materials weight, and is coupled directly to the
scooter rear wheel (Caricchi et al., 1994, Caricchi et al., 1996). Switch reluctance
motors were developed and prototyped for EV trials. The new developed outer-rotor-
type multipolar SRM was simulated for experiments on suitability for EVs (Goto et
al., 2005). The outer rotor and inner rotor motors were compared in terms of thermal,
dynamic behaviours to evaluate their performance in context of EV technology
(Hennen and De Doncker, 2007). The stem developed included a liquid-cooled axial
20
flux permanent-magnet designed to meet the direct-drive requirements. Permanent
magnet motor was designed in the form of an axial flux inner stator-non slot type to
use it as compact high torque motor for in wheel direct drive technology (Patel N
(Cypress CA) et al., September 22, 2009 , Rahman et al., 2000). During time many
researchers also focused on analysis and performances of drive trains using computer
aided validations, Matlab etc. (Butler et al., 1999, He et al., 1999, M. Ehsani; K.,
1997, Tseng and Chen, 1997) There were many challenges posing to EVs such as
economically viable and integrated performance of electromechanical parts including
motors, suspensions, brakes etc. A novel axial flux permanent magnet (AFPM)
machine with a Segmented-Armature Torus (SAT) topology was investigated to be
used in EV drive technology (Rahim et al., 2007). Permanent magnet electric vehicle
embodying an axial flux traction motor directly coupled to motors were developed.
Use of transverse flux machine (TFM) for in-wheel motor applications was discussed
by Baserrah (Baserrah et al., 2009). This method compared different TFM based on
FEA results on constraints, such examples would be construction dimensions,
electric and magnetic loading etc. The in-wheel motor developed was composed of
an outer rotor with a rare earth permanent magnet (Sm-Co) and an inner stator. It ran
a maximum speed of 176 km/h a range of 548 km per charge at a constant speed of
40 km/h and acceleration from 0 to 400 m in 18 seconds. Simulation showed that
performance of fuzzy PID controller in steering using two hub motors was better
than non-controller type (Chen et al., 2009).
2.2.4.3 Electric Motor Used in Commercial EVs
The electric motors used by the commercially available EVs were also
considered as a background for choosing the suitable motor in this research. The data
was collected from the vehicle manufacturer’s handbooks. According to data from
the, The Nissan Leaf used an 80 kW (110 HP) and 280 N-m front-
mounted synchronous electric motor driving the front axle. The Tesla Roadster was
powered by a 3-phase, 4-pole, and induction electric motor with a maximum output
power of 185 kW (248 HP). Its maximum torque of 200 lb-ft (270 N-m) was
immediately available and remained constant from 0 to 6,000 rpm; nearly
instantaneous torque was a common design feature of electric motors and offered one
21
of the biggest performance differences from internal combustion engines. The motor
was air-cooled. The model of 2009 i-MiEV consisted of a single permanent magnet
synchronous motor mounted on the rear axle with a power output of 47 kW and
torque output 180 N-m. The motor was water-cooled and there was a conventional
automobile radiator in the front of the car with an electric fan. The coolant (with
antifreeze) level was monitored via a tank under the rear load platform on the left
hand side of the vehicle.
According to the automobile OEM’s newsletter, the best-known early vehicle
to employ wheel motors was designed by a young ‘Ferdinand Porsche’ in the employ
of coachbuilder Lohner and was known as the Lohner-Porsche Mixte Hybrid. At
Lohner he created two noteworthy vehicles, including the first front-wheel drive
vehicle in history. With time the conventional drive trains gained popularity and hub
motors were mostly disappeared from the landscape until companies such as
Crystallite started putting them in bicycles in more recent times (release). Michelin
displayed an ingenious arrangement of active Wheel’s compact drive motor and
integrated suspension system. Also, Michelin were displaying their increasing range
of low rolling resistance tires. The Active Wheel was a standard wheel that housed a
pair of electric motors. One of the motors spined the wheel and transmitted power to
the ground, while the other acted as an active suspension system to improve comfort,
handling and stability. It had also enabled designers to fit a standard brake disc
between the motors (VIJAYENTHIRAN, May 10, 2008).
2.2.4.4 Evaluation of Existing Vehicle Architectures
Not all types of vehicle parameters were suitable for this retrofitting
procedure. Hence, the evaluation of existing vehicle architectures was significant for
the selection of suitable outer parameter of the vehicle for retrofitting. These
parameters included the engine size, power requirement, torque profile, brakes and
suspension system, outer dimension of the vehicle, total weight of the vehicle, tyre
profile, wheelbase (longitudinal distance between the wheels), track width (lateral
distance between the wheels) etc. The approach was to compare and evaluate the
data collected for different vehicle sectors from the market. Different vehicle sectors
were defined in market research based on their size, kerb weight and power rating
22
(Nakano-cho, 2008). Mostly small vehicle sector concluded the hatch-back models;
medium vehicle sector concluded the sedan models.
In small sized vehicles, Hyundai Getz 1.6 SX Hatch-Back, Holden Barina
Spark CDX 1.2 Hatch-Back, Ford Fiesta 1.4 Hatch-Back, Toyota Yaris YRS/YR 1.5
Hatch-Back, Suzuki Swift 1.6 Hatch-Back were very promising according to the
market research in terms of power rating, tyre profile and kerb weight of the vehicle.
Maximum small vehicles had the kerb weight of around 1000 kg. Most of the
vehicles had ventilated disc brakes at front and drum brakes at rear. In case of
suspension system in small vehicles, Macpherson struts at front and torsion or twist
beam coil spring at rear for most of the vehicles were commonly used. Outer
dimension of the vehicle were in the range of 3.5 – 4 m in length, 1.5 – 1.7 m in
width and 1.4 -1.6 m in height. Advantages of using small latest vehicles would be
light weight structure and inclusion of latest technologies. Using medium size
vehicles was advantageous in some instances such as space availability for packaging
of motor, batteries and other ancillaries associated with it. Models considered for
evaluation procedures in mid-size vehicles were Hyundai Sonata, Mazda 6, Toyota
Camry, Suzuki SX4 and Holden Cruze. Maximum medium vehicles had the kerb
weight of around 1500 kg. Most of the vehicles have ventilated disc brakes at front
and solid disc at rear. In case of suspension system in small vehicles, Macpherson
struts at front and torsion or twist beam coil spring at rear for most of the vehicles
were the most common options, though there were some vehicles with multi-link
anti-roll bar at rear suspension. Outer dimension of the vehicle were in the range of 4
– 4.9 m in length, 1.7 – 1.9 m in width and 1.4 -1.6 m in height. Small SUVs were
not any different to medium size vehicles in total weight. However they were more
powered than medium vehicles which could not be identified till prototypes would be
built to evaluate SUV with in wheel design concepts. Nissan Dualis, Hyundai I35
were few possible SUVs to be modified to EV drive trains. Maximum SUVs had the
kerb weight of around 1550 kg. Most of the vehicles had ventilated disc brakes at
front and solid disc at rear. In case of suspension system in small vehicles,
Macpherson struts at front and multi-link anti-roll bar at rear suspension were
commonly used. Outer dimension of the vehicle were in the range of 4.3 – 4.6 m in
length, 1.7 – 1.9 m in width and 1.6 -1.7 m in height. Like medium vehicle sector,
23
more space allocation for wheel would be attained with small SUV sector, but power
requirement and weight of vehicle were not suitable for in wheel motor packaging
requirement at this point in time. All the data was collected from the corresponding
vehicle manufacturer’s web page.
2.2.4.5 Brake System
Braking system of the vehicle was another concern for retrofitting, since the
weight of the vehicle would go up during the conversion. The braking system of the
vehicle needed to be reliable for the added weight of the vehicle. Especially the
thermodynamic behaviour of the disc brakes in an operating condition was analysed
in previous literatures (Zetterstram, 2002). Many researchers have used FEA (Finite
element analysis) techniques to obtain the stress, thermal strain of the disc brakes. In
many researches, simplified model of disc brakes were used avoiding the variation of
contact pressure and temperature with time. Some researchers simplified the disc
geometry by modelling only the disc applying the rotational velocity on it. It was
also shown in previous research that brake pad also undergoes thermal deformation
and temperature distribution along the disc is not uniform. But some researchers also
simplified the analysis of the thermal behaviour of the brake system by taking only
the disc under CAD geometry consideration. There were some mathematical models
as example Lagrangian approach to simulate the frictional heating of the disc brakes
with rotational speed relative to the brake pads which could help getting the realistic
analysis results. But considering the high computational time and resources due to
the simultaneous execution of thermodynamic and mechanical analysis, some
literatures considered the disc brake as a solid with a given operating condition to
check the deformation, stress and thermal strain through the analysis (Jerhamre,
2001. , Kubota, 2000, Giorgetti., November 28 2000., Koetniyom, 2000, Weichert.,
2003). The thermal and structural coupling was studied in previous literature for the
ventilated disc rotor and pad. Mechanical stress and thermal stress were obtained and
compared to verify the module coupling in ANSYS (Ali Belhocine, 2013).
2.2.4.6 Suspension System
Suspension system was also an important concern with the increment of total
weight of the vehicle and the position change of the significant weight items of the
24
vehicle. Currently many suspension systems were used in automotive engineering
which could support vehicle dynamics by dependent and independent ways. Among
the available types of suspension systems such as traverse leaf spring, molten rubber
suspensions, multi-link systems, the McPherson Strut has been the most popular
because of its light weight and compact size. Previously many studies were
accomplished considering the suspension model consisting of control arm, tie rod,
spindle, piston rod, coil spring, damper and the road model including camber,
roughness of the road-surface. In some research, the Macpherson suspension was
modelled and the FEA was carried out for assessing the deformation of the different
components of the suspension system. Some researches were to estimate the dynamic
parameter of the suspension. Some researchers considered the specific manoeuvring
condition and varied the roll centre to get the kinematic behaviour of different
components of the suspension system in different road models. Some employed the
displacement matrix method to analyse the system behaviour and a comprehensive
kinematical and dynamic analysis of the Macpherson strut suspension system (Y. I.
Ryu1, 2010, M. S. FALLAH, 2008).
2.3 Vehicle Dynamic Analysis The vehicle dynamic characteristic of the vehicle was considered primarily
governed by the centre of gravity (CG) and the polar moment of inertia, which was
regulated by the placement of the EV components along longitudinal, lateral and
vertical directions. The tendency of the vehicle towards different dynamic
characteristics in different manoeuvring conditions such as acceleration, braking,
cornering was studied in many researches. Some research focused on different
variables such as side-slip, tire forces to improve the vehicle safety, handling and
comfort. Some research was based on analysing the stability of the vehicle in sudden
manoeuvre which is very essential to prevent the road accidents. Vehicle
performance was also based on the road friction magnitude. The potential trajectories
of the vehicle were studied in some researches to obtain the better management of
vehicle control system and electronic stability controller (ESC). Some researchers
approached towards the modelling of vehicle based on different software. The
25
modelling of a road vehicle was found very complex. To simplify the model some
researchers avoided the road model and different features of the road surface and
environment such as camber angle, wind speed, wind direction etc. (Frendo, 2007,
Rajamani, 2006, Gillespie, February 1992).
The dynamic behaviour of the vehicle depending on the longitudinal motion
was studied by many researchers. According to the literature review, the longitudinal
vehicle motion was governed by the forces acting on the vehicle such as longitudinal
tyre forces, rolling resistance, forces due to the gravitation, aerodynamic drag etc. In
some models, the road inclination angle was considered zero to simplify the vector
calculation of the forces. To get the magnitude of longitudinal tyre forces, some used
the experimental data. In some cases, the simulation results data obtained from the
sensors were used to model the effect of the forces acting on the vehicle (Gillespie,
February 1992).
Some studies were accomplished to describe the characteristics of ground
vehicle in terms of performance handling and ride. The tendency of the vehicle to
overcome the obstacle on the road at a fast driving condition and to continue the
vehicle motion against the external disturbances was denoted as the performance
characteristics. The ride characteristics were defined as the road-tyre interface
friction and its impact on the passenger and goods on the vehicle. Handling
characteristics were defined by the response of the vehicle towards the driver’s input
to the steering, accelerators and brakes. The relationship of these characteristics was
also discussed in some articles as the driver’s usual reaction to the accelerators and
brakes and vehicle reaction to the road obstacles regulating the handling and stability
condition of the vehicle (Frendo, 2007).
2.3.1 Configuration of tyres
Previous research concentrated on the pneumatic tyres used for road vehicles
as it served the requirement of performance, handling and riding quality of the
vehicle. The two basic concerns of the mechanics of the tyres were analysed in the
literature that the mechanics of the tyres on hard and deformable surfaces such as on
the gravel road. Different types of tyre construction to serve the requirements of
vehicle riding and handling were also discussed in some research such as bias ply
26
tyres, radial ply tyres and carcass ply tyres. With the change in constructions types,
the tyre response of rolling resistance, overturing moments, tractive force, lateral and
normal force, aligning torque of the vehicle towards the direction of wheel travel
changed. The magnitude of the slip angle developed in the tyre also differs with the
difference in tyre profile (Müller, 2002, Sylvain DETALLE, 1997).
2.3.2 Road Surface Friction
The tyre road surface friction was studied in some articles (Müller et al.,
2003, Pasterkamp and Pacejka, 1997, Rajamani et al., 2010, Shim and Margolis,
2004, Wang et al., 2004). The texture of different types of pavement surface such as
polished concrete, new concrete, rolled asphalt with mixed aggregate rounded in
different states like coarse, medium or medium-coarse and asphalt with coarse seat
coat according to the society of automotive engineers (SAE). Inflation pressure of the
tyre was considered in some research as the significant factor for the calculation of
rolling resistance and the flexibility of the tyre. The deflection of the tyre under
different condition of the vehicle was also depended on the inflation pressure. The
deflection of the tyre controlled the movement of the tread elements and the contact
patch area at the static and dynamic loaded condition. Temperature effect on the
running condition of the tyre was discussed in the literature as the temperature has a
great impact on the coefficient of rolling resistance. SAE research concentrated on
the complex relationship between the design and operational parameter of the tyre
and its rolling resistance. The basic intention was to keep the rolling resistance as
low as possible, but the tyre endurance, life were also significant considerations.
SAE recommends the procedures of calculating rolling resistance for different types
of tyres in different road surfaces according to the SAE handbook. Based on the
experimental data, many empirical formulas were proposed to calculate the rolling
resistance coefficient depending on the velocity of the vehicle. Analysing different
methods, the velocity range was set for different passenger vehicles. Literature
review referred that in the initial stage of the vehicle performance calculations, the
velocity was assumed to be ignored and the value of rolling resistance coefficient
was established for different operating condition of the vehicle as given in
Automotive Handbook, 4th edition, Bosch.
27
The height of the point of application of the aerodynamic resistance was
calculated in different articles and considered to formulate the equation of vehicle
motion. This point was denoted as haero in the textbook on vehicle dynamics
(Rajamani, 2006).
2.3.3 Aerodynamic Drag
The aerodynamic drag coefficient was discussed in different articles. Drag
coefficient was considered in many researches as varied with the value of vehicle
speed, flow direction and fluid properties such as density and viscosity. According to
the fluid flow theory, for streamlined body the aerodynamic drag coefficient can be
reduced. The aerodynamic body shape for the vehicle was studied in many
researches to reduce the drag coefficient. From the experimental results in the wind
tunnel, the drag coefficient for the different vehicle shapes and types were formed
according to the automotive handbooks. The frontal area calculation was also
proposed in some research. For the passenger vehicle, the frontal area varies in the
range of 79-84% of the area calculated from the overall vehicle width and height.
Based on the data collected for the passenger vehicles with the mass range of 800-
2000 kg the empirical formula was developed in the literature (Rajamani, 2006,
Rajamani et al., 2010, Wei et al., 2014, Xu et al., 2014).
2.3.4 Vehicle Model and Simulation
Vehicle dynamic estimation has been done in different literatures. Some
researchers were focused on vehicle and road modelling simultaneously and some
researchers presented the dynamic behaviour of the vehicle separately in vehicle-
body dynamics and road-vehicle interface modelling to simplify the complexity of
modelling road and vehicle body together. They calculated the dynamic
characteristics of the vehicle such as longitudinal and lateral forces; slip angles, side-
slip etc. Some studies carried out to obtain the effect of cornering stiffness on the
dynamic behaviour of the vehicle. They applied the mathematical model based on
Kalman Filter estimation and used different sensors integrated in modern road-
vehicles to measure yaw rate, longitudinal-lateral accelerations, steering angle and
angular wheel velocities (Doumiati et al., 2012). Some literature proposed tyre-force
28
model which can accommodate the magnitude of the road-friction as variable so that
the vehicle model could work for different road surface condition (Gillespie,
February 1992, Rajamani, 2006, Rajamani et al., 2010).
The distribution of weight in the vehicle was a very significant factor for the
location of CG of the vehicle. Literature explained that the front and rear weight
distribution determined the position of longitudinal position of CG and left-right
weight distribution determined the lateral position of CG. The ratio of load
distribution regulated the tendency of the vehicle towards different handling
characteristics of the vehicle such as under-steering, over-steering etc. In some
literature, it was shown that in critical speed cornering the formula car faces different
lap time for different load distribution. The lateral acceleration was also varied with
the weight distribution of the vehicle when maximum speed cornering was
performed in a driving simulator (Chen, 2014, Ramirez Ruiz and Cheli, 2014, Zhang
et al., 2014, Milleville-Pennel, 2008). The movement of the load between inside and
outside wheels during the critical cornering was measured and compared for different
weight distribution. The mathematical model displayed the amount of lateral load
transfer depended upon the cornering force, the CG height and the track width of the
vehicle. Lowering the CG would decrease the load transfer between inside and
outside wheels during cornering. And widening the track width of the vehicle would
decrease the load transfer of the vehicle. When a vehicle turned at a corner, the
lateral force generated was found at the contact patch of the wheel. As the CG of the
vehicle located above the ground, it required the outside wheel to carry more load
than the inside to balance the extra torque generated due to the forces on the vehicle.
According to the theory the tyre grip to the road surface increased with the increment
of the lateral load transfer of the vehicle. But after reaching to a certain level of load
transfer the tyre grip started to drop which was considered as a very critical situation
for the dynamics of the vehicle (Chen et al., 2012, Doumiati et al., 2009).
Some literatures focused on the estimation of the roll angle and the one-side
lateral load transfer with the calculation of the vertical forces on the wheels by
instrumenting the model vehicle with some sensors. They tested the concept with the
prototype of the model vehicle in the lab. The prototype vehicle was used as a
demonstration of the theoretical approach with the comparison of the simulation
29
results with the experimental data. The problem of describing the understeer-
oversteer behaviour of a general vehicle, such as one with locked differential or
tandem rear axle, was addressed taking a new perspective. The well-known handling
diagram and the associated classical understeer gradient might be inadequate, mainly
because they were no longer unique. The new concept of handling surface and a new
definition of understeer gradient, which was indeed the gradient of the handling
surface and a vector, were presented. It was also shown how the new concepts were
related to and generalize the classical ones. Finally, a procedure for the experimental
measure of the new understeer gradient was outlined (Frendo, 2007, Sharp and Dodu,
2004).
Previous research referred that the polar moment of the vehicle is a very
important factor for the stability and handling of the vehicle. The polar moment was
considered dependent on the mass, momentum and the force applied at a distance
from the centre of the vehicle. Literature revealed that the polar moment varied with
the turning intention of the vehicle when the direction changes with varying the load
and its position in the vehicle. If the load on the vehicle was far from the centre of
rotation the polar moment increased. The magnitude of polar moment regulated the
response time of the vehicle to the changes in steering (Akiyama et al., 1987, Dvorak
and Fitzhorn, 2008, Marqués-Bruna, 2011).
The radius of the curvature path and the trajectory of the vehicle were very
significant in dynamic analysis. Previous work on computing the curvature path of
vehicle referred that several mathematical models were analysed to compute the
optimal path for the vehicle. But there were so many assumptions such as vehicle
moving only forward, turning fully right or fully left etc. The mathematical model
showed that the radius of curvature path varies with the CG position, steering angle,
total mass, turning speed of the vehicle and the cornering stiffness of the wheels
(Frendo, 2007, Rajamani, 2006).
The measurement of tyre longitudinal slip and the lateral slip angle were
taken under considered in many researches for vehicle dynamic control system.
Literature review focused on different approaches to control the slip and slip angles.
Some research was based on estimating vehicle dynamic states and self-aligning
moment relies on a tyre model. The research presented the model of a vehicle body
30
independent of the tyre slip controller to avoid the complicacy of the control design.
Some research proposed the estimation model of tyre side slip angle based on the
relationship with lateral acceleration, yaw rate and velocity of the vehicle
independent of steering angle input. Literature review showed that at large slip angle,
the impact of the steering angle on the yaw rate of the vehicle. The yaw control
system gave different behaviour of the vehicle in different road friction magnitudes.
The limit of vehicle slip angles varied from the dry and snowy roads with different
friction coefficient. Many researchers used yaw control approach for simulating
vehicle dynamic behaviour by lowering the vehicle slip angle (Fukada, 1999,
Guillaume Baffet 2009, Gustafsson, 1997, Gustafsson, 1998, Junmin Wang, 2006,
Lee et al., 2004, Li et al., 2007, Takeshi Iijima, April 2010, You et al., 2009).
2.3.5 Tyre Model for longitudinal, lateral and normal forces
Previous literature developed a number of tyre models which were relating
the tyre forces with the tyre deflections simulate lateral dynamics of the vehicle.
These models were to demonstrate the physical properties, elastic deformation in
terms of control design of the vehicle and lateral forces and slip angles of the tyre
under specific criteria. Among these models, the magic formula tyre model and the
Dugoff’s tyre model were well-known in simulating vehicle dynamic characteristics.
Many researchers focused on the programming these models according to the vehicle
dynamic analysis requirement. Literature showed the parameter of the tyre model
could be altered to verify with the specific condition of the vehicle dynamic
behaviour. Some researchers established the tyre model by coupling the Michelin
magic formula adapting the low velocity of the vehicle, significant loads and high
side slip angles. Some researchers used dynamic friction model adapting the Lugre
model to simulate the road/tyre interaction for ground vehicles. They focused on the
traction control system which enhanced the stability and controllability of the vehicle
in low tyre friction situation by reducing the tyre slipping and sliding during vehicle
acceleration. Some literatures focused on the magic formula for the tyre modelling
which was based on the length and width of the contact patch in loaded condition of
the tyre. Front and rear slip of the tyre was also considered in this magic formula (Li
et al., 2007, Lidner, 1992, Müller, 2002, Sylvain DETALLE, 1997).
31
Previous research developed and tested a "slip-based" method to estimate the
maximum available tire-road friction during braking. The method was based on the
hypothesis that the low-slip, parts of the slip curve used during normal driving could
be able to indicate the maximum tire-road friction coefficient. Experimental results
were collected to support the hypothesis. The friction estimation algorithm used data
from short braking with peak accelerations of 3.9 m/s 2 to classify the road surface as
either dry or wet. Significant measurement noise made it difficult to detect the subtle
effect being measured, leading to a misclassification rate of 20% (Pasterkamp and
Pacejka, 1997).
The relationship between the slip angle and the cornering force on the tyre
was investigated extensively in different literatures. The cornering stiffness of the
tyre varies with the normal load acting on the tyre. From the experimental results, the
value for cornering and the longitudinal stiffness of the tyre were found in different
operating conditions of the vehicle. The research referred that the cornering forces
acting on the tyre was proportional to the slip angle generated. The lateral load
transferred from the inside to the outside tyres during cornering of the vehicle
reduces the total cornering force that a pair of tyres can develop. Stiffness also
depends on the inflation pressure of the tyre according to the literature (Bakker et al.,
1987, Bevly et al., 2006, Peng and Tomizuka, 1990, Sienel, 1997). Damping
coefficient was also an important factor for the vehicle dynamic analysis which was
based on the inflation pressure and the speed of the vehicle. The damping effect of
the tyre was a significant factor for the efficiency of the suspension system for the
unsprung mass of the vehicle. The damping of a pneumatic tyre depends on the
material properties of the tyre. But the damping coefficient was calculated for
different tyre and road condition from the experimental results of drop test (Chen et
al., 2014, Tong and Hou, 2014, Warczek et al., 2014).
2.4 Structural Safety Analysis of Battery Packaging 2.4.1 EV Batteries
It was predicted in the previous research that EVs would be going to lead the
automobile market and the battery was considered as the key to this revolutionary
32
change. EV batteries were different from the industrial ones and the laptop and cell-
phones batteries. The main concern with EV batteries was handling high power (up
to a hundred KW) and high energy capacity within a narrow space and weight. The
price of the batteries was also an important factor as the commercialization of EV to
the mass market is subjected to the cost issues associated with it (Burke, 2007, Chalk
and Miller, 2006, Jung et al., 2012). Different technologies have been used for EV
batteries since last 20 years of EV development. Various chemistries for the batteries
were studied previously for the EVs. The market research focused on the use of
different batteries for EV propulsion such as Using Li-Ion for GM Chevy-Volt, Ford
Escape PHEV, Chrysler 200C EV, BMW Mini E (2012), BYD China E6, Daimler
Benz Smart EV (2010), Mitsubishi IMEV (2010), Nissan Leaf EV (2010), Tesla
Roadster (2009), Think Norway EV etc. and Ni-MH for GM Saturn Vue Hybrid,
Ford Escape Fusion MKZ HEV, Toyota Prius, Honda Civic Insight, BMW X6,
Daimler Benz ML450 S400, Nissan Altima etc. For the higher specific energy and
energy density with required space constraints, the adoption of Li-ion batteries was
growing fast in case of BEVs as discussed in the literature. The most preferred type
of battery used for electric vehicles was li-ion due to its high energy to weight ratio,
high voltage and good stability. Literature review showed that li-ion batteries had a
slow rate of discharge while not in use. The commercial EVs used li-ion batteries for
powering EV drive train (Kennedy et al., 2000, Matthe et al., 2011, Will, 1996).
The required configuration of the EV battery depended on the propulsion
power required by the vehicle. The powertrain of an EV was required providing
power in all road conditions and driving modes. EVs also needed to consider the
regenerative braking so that the kinetic energy of the moving vehicle could be stored
and applied for future use. The power required to serve for the driving of the vehicle
was determined from the product of propulsion force depending on the vehicle
weight, aerodynamic drag, wind velocity, rolling resistance and the velocity of the
vehicle. The road condition such flat or inclined road was an important factor for
calculating the power required for the vehicle to drive. Average power required for
the vehicle to accelerate and brake up to a given range was found as defined in the
vehicle manual. It could be noticed from the data that the power required for braking
was more than that of accelerating the vehicle because the deceleration might happen
33
in a very shorter period of time and in a distance as short possible. The EV battery
required meeting the demand of supplying the power at the driving condition and
storing the energy at the same time. According to the US urban dynamometer driving
schedule, typical energy consumption of a mid-sized vehicle for urban driving is 165
wh/Km and 137 wh/km for highway. However, there were many more factors for
this energy consumption rating such as the vehicle weight, size, aerodynamic shape
of the body, the driver’s input etc. According to the data obtained from the literature
the gasoline had a theoretical specific energy of 13000 wh/kg which was over 100
times higher than the Li-ion batteries (120 wh/kg). To generate the similar amount of
specific energy the required battery pack to propel the vehicle would be of huge
weight and high volume which would not be very practical. Some researchers
considered the energy efficiency of the internal combustion engine propulsion and
the electric propulsion as the electric propulsion is much more efficient than ICE.
From the experimental data, some researchers applied the energy requirement of the
electric propulsion would be 80% of the ICE propulsion and the energy storing
capacity of the electric propulsion system would be one-fourth of the regular ICE
propulsion for the same mileage (Hcdrich et al., 2008, Stockar et al., 2010).
2.4.2 Batteries Used in Commercial EVs
According to the market research data provided by the vehicle manufacturers,
the typical energy required for a vehicle to drive a mile ranges from 0.25 kWh (GM’s
EV-1) to 0.30 (GM’s Volt) and 0.33 kWh (Tesla’s Roadstar). As an example
calculation, a 200-l (50 gallons) battery pack with an energy density of 230 Wh/l
stored 46 kWh of energy and travelled 200 miles between charges. Another factor,
power density, was important for acceleration and for the collection of regenerative
energy from braking. The battery pack mentioned above, assuming a discharge
power density of 460 W/l, can generate 92 kW (123 hp), which was acceptable for a
typical passenger vehicle. The 24 kWh battery pack in the Nissan Leaf consisted of
48 modules and each module contains four cells, a total of 192 cells, and was
assembled by Automotive Energy Supply Corporation (AESC). Tesla Motors
referred to the Roadster's battery pack as the Energy Storage System or ESS. The
ESS contained 6,831 lithium ion cells arranged into 11 "sheets" connected in series;
34
each sheet contained 9 "bricks" connected in series; each "brick" contained 69 cells
connected in parallel (11S 9S 69P). Tesla focused a great deal of effort on the safety
of the battery pack through both its engineering as well as its industry involvement.
In the Mitsubishi i-MiEV the 16 kwh lithium-ion battery pack consisted of 88 cells
placed under the base floor. The pack had 22 cell modules connected in series at a
nominal voltage of 330 V. There were two 4-cell modules placed vertically at the
centre of the pack and ten 8-cell modules placed horizontally. The entire pack had a
specific energy 80 wh/kg.
Different materials for the EV applications were studied in many researches.
The Li-ion battery cathode and anode material was compared and mentioned
different properties for those. LiCoO2 with 160 mAh/g specific capacity and 3.7V
voltage were mostly used in consumer products; good capacity and cycle life with
high cost and unsafe in case of high charging rate. LiMn2O4 (130 mAh/g specific
capacity and 4V voltage) were commonly used in automobile with low cost and
acceptable rate capability, but poor cycle of life and durability. LiFePO4 (140 mAh/g
specific capacity and 3.3V voltage) included low cost, improved abuse tolerance,
good cycle life and power capability, but low capacity and durability (Bruce et al.,
2008, Kang and Ceder, 2009, Scrosati and Garche, 2010).
As described in the report of US-China battery workshop based on energy
efficiency and renewable energy organized by US department of energy (DOE),
battery affordability and performances were critical advances that were needed in
order to achieve the EV everywhere grand challenge. The workshop categorized the
commercial EVs by the battery configuration and the price associated with it. The
Chevy volt included 40 miles electric range HEV (32 mpg/300 miles; 16 kwh/120
kw battery) and the cost of the battery around $8000. The Nissan Leaf comprised 75
miles electric range and more than 24 kwh/ 80 kw battery with $12000 cost. The
Tesla Roadster included 250 miles electric range with 85 kwh/ 270 kw battery which
was around $35000.
2.4.1 Packaging of EV Batteries
The design of the packaging arrangement of the battery was modelled in
different automobile project. The conceptual design approach was implemented in
35
preparing the design model. According to the description stated in different
researches, the conceptual design consisted of the understanding the root problem
addressed by the requirements, identifying and exploring a broad range of alternative
solutions based on the requirements, evaluating the alternative solutions and
combining the best aspects of each and selecting a combination of alternatives
considering the design constraints. The Nissan Leaf's design located the battery, the
heaviest part of any EV, below the seats and rear foot space, keeping the centre of
gravity as low as possible and increasing structural rigidity compared to a
conventional five-door hatchback (Loing, 2009).
To test the reliability and durability of the battery packaging arrangement
design, Finite Element Analysis (FEA) has been used widely in engineering. Some
researchers worked on the reliable design and test procedure to guarantee the service
length under the operating conditions and full functioning of the product. According
to the literature the crucial part of the FEA was determining the magnitude of load
acting on the structure. And if the load would be a function of time with the
operating temperature of the structure the FEA would be considered as the
complicated analysis. Some researchers simplified the analysis at the design
geometry and some researchers simplified the analysis by making the assumptions at
the analysis settings such as ambient temperature, independence with time factor, the
magnitude of load as an arbitrary value (Chan et al., 2006, Krein et al., 1994, Loing,
2009, Peters, 2000).
To perform the analysis of the structure at real time environment, some
researchers analysed the vehicle safety at a crash situation. Now-a-days crash
simulation of a vehicle has become an important safety analysis tool for automobile
industry to shorten the time to market and lower the vehicle manufacturing cost. The
battery electric vehicles have possessed a great dependency in terms of safety of the
passenger during the crash due to the huge battery on board. LS-DYNA has been a
well-accepted non-linear dynamic analysis program developed by Livermore
Software Technology Corporation (LSTC) integrated with ANSYS (Takezono, 2000,
Wriggers, 2006). It has been able to analyse large deformation behaviour in
structures by the explicit time integration method and vehicle crash can be modelled
in it to check the safety features of different components of the vehicle. In the LS-
36
DYNA model, the vehicle has been divided into lots of nodes and elements. The
behaviour of the vehicle, forces, displacements and stress developed at each node
and element of the vehicle could be calculated from the K-file generated by the
model in ANSYS mechanical APDL product launcher. The crash simulation of the
vehicle has been widely used for simulating the safety features installed in the
vehicle such as air-bags, seat-belts etc. Dummies at the position of passenger were
placed to check the safety during crash along with the action of safety features.
Vehicle crash could be simulated in different ways according to the literature. The
safety of the vehicle could be checked in a frontal impact situation when colliding
with an obstacle (rigid wall), in a collision with another vehicle or in a side impact
situation when colliding with a rigid obstacle or a moving vehicle during lane
changing (Bathe, 1998, Baykasoglu et al., 2012, Kirkpatrick et al., 1999, Zhang et
al., 2009).
2.4.2 Analysis of Battery Packaging Design
The use of structural analysis in checking the feasibility of the structure for a
given amount of load from a defined direction was applied in different types of
complex engineering design according to the literature. Failure analysis was also
used for different structures to reduce the stress concentration in case of different
materials. Some researchers applied different conditions such as repetitive load,
moving load, sudden change of temperature, change of temperature with time steps
etc. The design structures were analysed including the deformation, stress and
thermal strain which presented the actual loaded condition of the design. In the CAD
geometry, the direction of load applied was considered very crucial for the analysis
results. Research has been done analysing the failure mechanism of the Li-Ion
battery when small internal short circuit spots generated in the separator in a
controllable and repetitive manner. Deformation developed in the separator was
measured by the FEA analysis model. The deformation of different structures was
also calculated by considering different material such as aluminium alloy. Several
modelling approaches including flow stress-strain curves, the equation model and
processing map were used to characterize the deformation found in the structural
analysis. In some cases, the torsion has been applied to obtain the thermal-
37
mechanical behaviour of the structure under pure tension and compression. Some
researchers investigated the deformation due to the change of thermal expansion
coefficient in the analysis and compared the relationship between thermal expansion
and the equivalent Von-Mises stress of the structure (Tremblay and Dessaint, 2009,
Yang and Knickle, 2002).
2.5 Battery Cooling System & Thermal Analysis The state of charge (SOC) was considered as the critical condition parameter
for the battery health which was based on the load current and the operating
temperature of the battery. Accurate gauging of the battery SOC was found critical to
know when to stop charging the battery. Literature referred to the state of health of
the battery based on the operating temperature. When it came to batteries for electric
vehicles, the thermal management system that ensured batteries operate within a
certain temperature range would be crucial to helping electric vehicles drive greater
distances for a longer period of time. If batteries were to have a long service life,
overheating must be avoided. According to the literature, a battery’s comfort zone
lied between 20°C and 35°C. But driving in the mid-day heat of summer in Australia
would push a battery’s temperature beyond that range. The damage caused could be
crucial. Literature referred that operating a battery at a temperature of 45°C instead
of 35°C halved its service life. Temperature affected the operation of the
electrochemical system, round trip efficiency, charge acceptance, power, energy,
safety, reliability, life and life cycle cost of the battery. The thermal management was
needed for the battery pack to regulate the desired operating temperature range for
optimum performance, reduced uneven distribution of temperature in the cell of the
battery and eliminated the potential hazards related to uncontrolled temperature. That
is why it was found important to keep them cool. According to the literature, the
capacitor modules for EVs were subjected to heavy duty cycling conditions and
therefore significant heat generation occurs. High temperature caused accelerated
aging of the double layer capacitors and hence reduced lifetime. To investigate
the thermal behaviour of double layer capacitors, thermal measurements during
charge/discharge cycles were performed in previous research. These measurements
38
showed that heat generation in double layer capacitors was the superposition of an
irreversible Joule heat generation and a reversible heat generation caused by a
change in entropy (Schiffer, 2006, Bennion and Kelly, 2009, Chu, 2009, Zolot et al.,
2001).
2.5.1 Air and Water Cooling System
Thus far, air cooled conventional cooling systems had not yet reached to its
full potential as found in previous literature. There were two types of thermal control
using air ventilation, one was active air-cooling another was passive air cooling.
Passive air-cooling process was very simple as the outside air passed through the
battery pack and exhausted from the pack using a fan. There was another way to
form a passive air cooling system. The outside air would be passed through an
installed vehicle cooler or heater cores and the cooled air entered into a cabin where
the battery pack was placed. The hot air was then taken away by the exhaust fan and
passed it to the cabin air again. If the exhausted air could be totally moved out from
the system and always the outside air could be used for cooling of the battery then
the system could be denoted as the active air cooling system. The efficiency of the
active system was more than the passive system. But air could absorb only very little
heat and was also a poor conductor of it. Moreover, air cooling required big spaces
between the battery’s cells to allow sufficient fresh air to circulate between them
(Fan et al., 2013, Park, 2013).
The liquid-cooling systems were still under research and development.
Though their thermal capacity exceeded that of air-cooling systems and they were
better at conducting away heat. According to the National Renewable Energy
Laboratory report, there were three types of thermal control using liquid circulation.
Those are: passive, moderate active and active cooling system. In the passive
cooling system, the liquid coolant was pumped to the battery pack after passing
through the heat exchanger in the outside air with exhaust fan. In the moderate active
cooling, after flowing through the battery pack the cooling liquid was pumped to the
liquid heat exchanger where the general vehicle engine coolant was applied for
cooling. After the heat exchanging process, the liquid coolant returned to the battery
pack again. In the active cooling system, the coolant passed through a dual stage heat
39
exchanger. At the first stage, vehicle engine coolant was in use for moderate cooling.
At the second stage, an AC heat exchanger was in use with either air from evaporator
or refrigerant from the condenser. The active cooling system with AC heat exchanger
was found more efficient than the others. But the downside of the liquid cooling
system was the limited supply of liquid in the system compared with the essentially
limitless amount of air that can flow through a battery. Another backdrop of the
liquid cooling over the air-cooled system was the cooling media could be used
directly in case of air cooling as air did not have any chemical reaction or electrical
hazard with the battery whereas liquid coolant needs to be jacketed to avoid the
electrical hazards (Sabbah, 2008, Kandlikar and Hayner, 2009, Kevala, 1990, Yeow
et al., 2012).
2.5.2 Cooling System Used in Commercial EVs
The Nissan Leaf was powered by a 24 kilowatt-hours lithium ion battery pack
rated to deliver up to 90 kilowatts (120 hp) power. The pack contained air-cooled,
stacked laminated battery cells with lithium manganate cathodes. The battery and
control module together weighed 300 kg and the specific energy of the cells was
140 Wh/kg. Tesla motors used liquid cooling system for the battery pack of the
Roadster model. A fully charged ESS stored approximately 53 kWh of electrical
energy at a nominal 375 volts and weighed 992 lb (450 kg). The pack was designed
to prevent catastrophic cell failures from propagating to adjacent cells (thermal
runaway), even when the cooling system was off. Coolant was pumped continuously
through the ESS both when the vehicle was running and when the car was turned off
if the pack retained more than a 90% charge. The coolant pump drew 146 watts.
Appropriate cell temperature levels were maintained by a proprietary liquid-cooling
system which included sensors within the pack monitored by the battery management
system of the vehicle. Liquid coolant was pumped through the pack to enable
effective heat transfer to and from each cell. The cooling system was so effective that
the cells on opposite sides of the battery pack stay within a few degrees of each
other. This was important for maximizing battery life, optimizing performance and
safety. In the Mitsubishi i-MiEV the battery had a forced air cooling system to
prevent overheating during high charge and discharge rates and consequent damage.
40
There was an integral fan in the battery pack. For rapid charging, the battery pack
was additionally cooled with refrigerated air from the air conditioning system of the
vehicle. General Motors for its Volt and Ford’s line of hybrids and EVs selected to
use liquid for battery temperature regulation. Coda Automotive, meanwhile, used an
air cooling system for its Coda Sedan.
2.5.3 Use of PCM as Cooling Material
As the cooling material suitable for the automotive battery, the phase change
material (PCM) was also considered in some research. Battery thermal management
using PCM had potential to bring benefits, such as passively buffering against life-
reducing high battery operating temperatures according to the report by National
Renewable Energy Laboratory, US. 18650 Li-Ion cells were surrounded by a high-
conductivity graphite ‘sponge’ that was saturated by a PCM (‘wax’). The matrix held
the PCM in direct contact with the cells, and the latent heat capacity to melt the PCM
was intended to absorb the waste heat rejected by the cells during periods of
intensive use. The advantages found from the research were reduced peak
temperature, better uniformity of the temperature and reduced system volume. And
the backdrops found were the heat accumulation, additional weight of the system and
undesirable thermal inertia (Pesaran, Dec 2-5, 2007). The thermal conductivity of
paraffin wax was increased by two orders of magnitude by impregnating porous
graphite matrices with the paraffin. The graphite matrices were fabricated by
compacting flake graphite that had been soaked in a bath of sulphuric and nitric acid
then heat-treated at 900 °C. The properties of the graphite matrix and paraffin phase
change material (PCM) composites were measured for graphite matrix bulk densities
ranging from 50 g/L to 350 g/L. The properties studied included
the thermal conductivity in directions parallel and perpendicular to the direction of
compaction, paraffin mass fraction, and the latent heat of fusion of the composite
samples (Mills, 2006). The effectiveness of passive cooling by PCM was compared
with that of active (forced air) cooling in previous literature. Numerical simulations
were performed at different discharge rates, operating temperatures and ambient
temperatures of a compact Li-ion battery pack suitable for plug-in hybrid electric
vehicle (PHEV) propulsion. The results were also compared with experimental
41
results. The PCM cooling mode used a micro-composite graphite-PCM matrix
surrounding the array of cells, while the active cooling mode used air blown through
the gaps between the cells in the same array. The results showed that at stressful
conditions, i.e. at high discharge rates and at high operating or ambient temperatures
(for example 40-45 °C), air-cooling was not a proper thermal management system to
keep the temperature of the cell in the desirable operating range without expending
significant fan power. On the other hand, the passive cooling system was able to
meet the operating range requirements under these same stressful conditions without
the need for additional fan power (Sabbah, 2008, Kizilel, 2009, Mills, 2005, Al-
Hallaj, 2002).
2.5.4 Thermal Management of Batteries
The cooling system was analysed in many literatures for different solid
structures. When the temperature of the solid was dependent on the temperature of
the fluid, the fluid solid interface analysis was applied by many researchers (Chen et
al., 2005, Gu and Wang, 2000, Pals and Newman, 1995, Srinivasan and Wang,
2003). In case of lithium ion batteries, many researchers analysed the interface
between the electrode and the separator. The electrolytes were considered as the
interface for this analysis (Lee, 2014). Electrochemical properties of the graphite
anode and the LiFePO4 cathode, working together with the 1 M LiPF6 in TMS
(sulphone) at 90°C were studied. The general aim of the investigation was to
demonstrate a potential application for a Li-ion cell working in the cooling system of
a vehicle heat engine (90°C) (Lewandowski, 2014). Research was done exploring the
use of heat pipe as cooling device for a specific HEV lithium-ion battery module.
The evaporator blocks of heat pipe modules were fixed to a copper plate which
played the role of the battery cooling wall. A flat heater was glued to the other
surface of the copper plate and reproduced heat generated by the battery. The
temperature at the cooper plate/heater interface corresponded to that of
the battery module wall (Tran, 2014). Battery thermal management system for BEVs
based on the impact of climate both directly on the battery temperature and indirectly
through the loads of cabin was studied. The findings of the study was the primary
challenge to cold-climate BEV operation to be inefficient cabin heating systems, and
42
to hot-climate BEV operation to be high peak on-road battery temperatures and
extreme degradation of the battery. Active cooling systems appeared necessary to
manage peak battery temperatures of aggressive, hot-climate drivers, which could
then be employed to maximize thru-life vehicle utility (Neubauer, 2014, Bandhauer,
2011).
3D thermal model has been developed in previous research to examine
the thermal behaviour of a lithium-ion battery. The model considered the layered-
structure of the cell stacks, the case of a battery pack, and the gap between both
elements to achieve a comprehensive analysis. Both location-dependent convection
and radiation were adopted at boundaries to reflect different heat dissipation
performances on all surfaces (Chen, 2005). Mathematical modelling of heat
generation and transport in lithium/polymer-electrolyte batteries for electric vehicle
applications has been conducted in the previous research. Under high discharge rates
of the battery, the thermal management system was considered as very crucial
because the temperature of a battery might increase remarkably under the
consideration of the thickness of a cell stack exceeding a certain value. Also, due to
the low thermal conductivity of the battery material, the improvement of cooling
conditions was not an effective means of improving heat removal for large-stack
systems. For a required operational temperature range and a given discharge rate,
model predictions could be used to design appropriate battery structures and to
choose a suitable cooling arrangement (Chen, 1993, Al-Hallaj, 2002, Chen, 2005,
Esfahanian et al., 2013, Lee, 2014, Lewandowski, 2014, Ng and Dubljevic, 2012,
Schiffer, 2006).
The previous research investigated consequences of integrating PHEVs in a
wind-thermal power system supplied by one-fourth of wind power and three-fourth
of thermal generation. Four different PHEV integration strategies, with different
impacts on the total electric load profile, have been investigated. The study showed
that PHEVs could reduce the CO2-emissions from the power system if actively
integrated, whereas a passive approach to PHEV integration was likely to result in an
increase in emissions compared to a power system without PHEV load. The
reduction in emissions under active PHEV integration strategies was due to a
reduction in emissions related to thermal plant start-ups and part load operation.
43
Emissions of the power sector were reduced with up to 4.7% compared to a system
without PHEVs, according to the simulations. Allocating this emission reduction to
the PHEV electricity consumption only, and assuming that the vehicles in electric
mode was about 3 times as energy efficient as standard gasoline operation, total
emissions from PHEVs would be less than half the emissions of a standard car, when
running in electric mode. The previous research indicated that
the thermal management of traction battery systems for electrical-drive vehicles
directly affected vehicle dynamic performance, long-term durability and cost of
the battery systems. In the literature, the battery thermal management method using a
reciprocating air flow for cylindrical Li-ion cells was numerically analysed using a
two-dimensional computational fluid dynamics (CFD) model and a lumped-
capacitance thermal model for battery cells and a flow network model.
The battery heat generation was approximated by uniform volumetric joule and
reversible (entropic) losses. The results of the CFD model were validated with the
experimental results of in-line tube-bank systems which approximates the battery cell
arrangement considered for this study. The numerical results showed that the
reciprocating flow can reduce the cell temperature difference of the battery system
by about 4 °C (72% reduction) and the maximum cell temperature by 1.5 °C for a
reciprocation period. Such temperature improvement attributed to the heat
redistribution and disturbance of the boundary layers on the formed on the cells due
to the periodic flow reversal. (Göransson, 2010, Mahamud, 2011).
The efficiency of the cooling system was investigated in the previous
research using CFD analysis for the coolant liquid. There different methods of using
CFD to analyse the flow of the fluid. In some research the fluid flow in dynamic
condition with the velocity, acceleration and turbulence was investigated. In some
cases, the fluid flow analysis was simplified by analysing it in the static condition. In
case of air-cooled system, the flow was considered as non-linear in cascades and
analysed by using a harmonic balance technique (Blazek, 2005, Munson, 1994).
44
2.6 Retrofitting of EVs A battery electric vehicle was developed by converting a VW Lupo 3L.
Researchers were trying to optimize the energy storing capacity of the vehicle with
the consideration of the vehicle weight. The original VW Lupo was compared to the
BEV Lupo in terms of the vehicle performance in this research (I.J.M. Besselink,
2010). MESDEA 200-200W water cooled AC induction motor (24 kW nominal/50
kW peak) and MESDEA TIM 600W water cooled inverter (80 to 400 V, 236 A
nominal/400 A peak) were installed in this EV conversion centrally with the Carraro
fixed ratio reduction (8.654:1) for the transmission.
University of California, San Diego developed a conversion design of an
internal combustion engine to an electric vehicle powered by batteries comprises
many steps from choosing the vehicle, sizing a motor, and the type of batteries. This
project takes a 1980 Datsun 280zx and converts it to an all-electric car with DC
motor and lead acid batteries. The power steering and power assist are reused as well
as air conditioning components (California, 2009).
Solar Electrical Vehicles has developed a prototype PV Prius to help answer
that question. The PV Prius is fitted with a custom moulded fiberglass photovoltaic
module. Solar Electrical Vehicles has applied for a patent on the PV Prius solar
system. The photovoltaic module is rated at 215 watts at AM 1.5. The module is
connected to a DC-DC converter and peak power tracker. The output of the converter
is directly connected to the primary motive Ni-Mh battery. The feasibility of
installing an aftermarket photovoltaic module on a Toyota Prius has been shown. The
economic return from the conversion of a stock Prius to a PV Prius is dependent
upon the nominal daily trip length, the price of gasoline required to operate the
gasoline engine, actual fuel efficiency of the gasoline engine, the number of Wh/mile
and the number of Wh provided by the solar module (Edward J. Simburger, 2006).
At the Karlsruher Institute of Technology (KIT) a vehicle was converted for
full battery electric drive. The converted vehicle consists mainly of one electric
motor with water cooled power electronics that drives the front axle, 21 battery
modules controlled and managed by the battery management system, one on board
charging device and an universal control unit (Müller-Glaser).
45
2.7 Findings Many researchers studied the conversion of EVs from the combustion engine
vehicles. In previous studies, brakes, suspension systems, electronic stability
controllers, different electric motors for power, different motor controlling approach,
different battery chemistries and configuration were studied and analysed in case of
conversion of EVs. Different architectural layouts based on the load distribution of
the vehicle were not studied in terms of dynamic analysis, providing the solution for
the battery packaging arrangement and the cooling efficiency of the battery pack.
Several automotive manufacturing companies developed the battery packaging
considering the distribution of heavy weight to get the balanced dynamic stability of
the vehicle, though the vehicle was not designed for retrofitting. The new production
design can have the flexibility of modifying the chassis of the vehicle as required.
The escalation of cost does not allow the retrofitting process to modify the chassis or
the main body of the vehicle. Therefore, the initial load distribution thus the
architectural layout was focused in this research to obtain a balanced system for
retrofitting of EVs.
46
CHAPTER 3
RETROFITTED ARCHITECTURAL
LAYOUT
In case of EV conversion, it is required to select a suitable vehicle parameter
and drive train system to obtain better performance from the retrofitted EV. It was
found in previous literature that modification of the automobile body or the existing
arrangement of other systems such as brakes and suspension cause cost escalation
and associated handling risk as discussed in 2.2.4. The retrofitting process involved
the removal of engine-driven accessories and the instalment of electric-drive
components to replace the drive train. It is important to check if the existing
suspension, brakes system is able to handle the modified vehicle load after replacing
the engine driven accessories. In this chapter, the vehicle system architecture was
evaluated and analysed to attain the optimum solution for the retrofitting condition.
Vehicle system architecture included vehicle propulsion system, electric motor and
controllers, outer dimensions and power requirement of the vehicle, brakes and
suspension system. The main objective of this chapter is to find a suitable existing
vehicle parameter to apply different load distribution layouts for vehicle dynamic
analysis in case of retrofitting.
To study all the aspects of retrofitting, the architectural layout of the vehicle
needed to be designed. Load distribution of the vehicle in both longitudinal and
lateral direction was determined by the architectural layout of the vehicle.
Architectural layout included the placement of different drive train components on
board. Hence, drive train components consist of battery pack, electric motor and
motor controllers. Architectural layout also determined the weight concentration of
the vehicle. The weight concentration of the vehicle was the significant factor in
determining polar moment which was considered as an important dynamic
47
characteristic of the vehicle. Another vehicle dynamic characteristic centre of gravity
also depended on the architectural layout of the vehicle. To select the architectural
layout with best dynamic results, different layouts were designed and modelled using
SolidWorks.
To select the suitable system architecture for retrofitted EV this system
architecture components required to be evaluated. Electric propulsion system chose
the orientation of the drive components in the vehicle. It selected the quantity of each
item, position of them and connecting diagram of the components. While retrofitting
it was very important to select the position of all EV drive train components because
allocation of space required for each item was the main concern.
The main component of the EV system was considered as the electric motor.
Vehicle operation consisted of three segments: the initial acceleration, driving at
vehicle rated speed, cruising at the maximum speed of the vehicle. These were the
basic design constraint of EV system according to the literature review. While
retrofitting, there were some design variables which needed to be taken under
consideration: electric motor power rating, motor rated speed, size of the motor,
motor weight, motor maximum speed, maintenance requirement, constant power
speed range beyond the rated speed etc. Considering these design variables, a review
study was accomplished in this research to evaluate different electric motors.
According to the literature, it was noticeable that all types of vehicle
parameters could not be suitable for the retrofitting. The data collected from the
automobile market focused on the detail parameter of the vehicle in different sector
based on the vehicle size. These data was used for evaluation and a suitable
parameter was optimized to place the EV propulsion components on the retrofitted
vehicle.
3.1 EV Propulsion System Selection During retrofitting the more compact the power train selected then the more
space could be allocated for batteries to ensure the maximum range for a single
charge. Power train had some design factors such as, power requirement to propel the
vehicle, power to weight ratio of the motor etc. These factors determined the number
48
of motor required for propulsion which was very important for the space allocation
while retrofitting of the vehicle. Another significant consideration was the
transmission types (direct or indirect drive). It decided the position of the motor in
the power train. It also determined the requirement of transmission gear and the
position of it in the drive train. According to the literature review (2.2.4.1) based on
the position of the electric motor, the number of motors and transmission types
(direct or indirect), conventional, by-wheel and in-wheel propulsion system were
evaluated and compared in this study for the selection of the suitable system (Cakir
and Sabanovic, 2006, Rahman et al., 2006). A comparison based on different
considerations among these propulsion systems has been demonstrated in Table 3-1.
Table 3-1: Comparison of three EV propulsion systems
By comparing conventional, by-wheel and in-wheel propulsion system, it was
noticeable that in context of placement of the motor in the propulsion diagram,
conventional system was the most suitable choice. But when installation of
Criteria Conventional By-Wheel In-Wheel
Diagram
Connection Complicated Simple Simplest
Transmission
power loss High Low No Loss
Packaging Cost Low High Highest
Space Savings Low High Highest
Motor Packaging
Arrangement Simple Simple Complicated
Weight Impact Sprung Un-sprung
Un-sprung:
Concentrated on
Wheels
MOTOR
MOTOR MOTOR
49
transmission gear boxes, drive shafts were considered, conventional propulsion was
found to occupy space more than others. By-wheel propulsion was more appropriate
than others in terms of lower transmission loss accompanied with lower cost of
packaging the motor beside the drive wheels. But the space occupied by the motors
and packaging arrangements could be used to accommodate more battery units on
board to get maximum range possible whereas in-wheel system allowed this space.
Though in case of in-wheel propulsion, packaging of the motor inside wheel
increased the un-sprung weight of the vehicle which was a significant function of
vehicle suspension design and the construction materials used in suspension
components. High un-sprung weight also exacerbated wheel control issues under
hard acceleration or braking manoeuvre. Road surface imperfections escalated the
impact of un-sprung weight on vibration absorption of the wheels.
In this research, in-wheel technology was chosen to be used to allow more
space for other EV components. However, an in-wheel system needed to consider
packaging of the wheel-motor, making it more complex than the by-wheel system. In
the in-wheel system, as the wheel was getting heavier with a motor, an appropriate
packaging solution was required to be integrated that could accommodate the
weather protection and vehicle stability due to the high un-sprung weight.
3.2 Electric Motor Selection An electric motor was also an important selection criterion for vehicle
architecture in terms of weight, size, efficiency and the power required. Vehicle
performance mainly depended on the acceleration of the vehicle which was evaluated
by the time required to accelerate from zero speed to a given speed and the highest
speed that the vehicle could reach. In EVs, electric motor was to deliver the torque to
the drive wheels. Here, vehicle performance completely depended on the power and
efficiency characteristics of the electric motor. Weight was another crucial
consideration in this case. As the motor was to be mounted inside the wheel, the
motor weight became a significant factor of the un-sprung weight of the retrofitted
vehicle (Ehsani, 1996, Xue, 2008).
50
To suit the in-wheel technology, motor size was also an important
consideration. Based on power, efficiency, cost, weight, size and maintenance
requirement, several electric motors such as the brushed DC motor (BDC Motor),
induction motor (IM), Permanent Magnet (PM) and switched reluctance motor
(SRM) was compared in this research in terms of the data found from the previous
literature (2.2.4.2 and 2.2.4.3). For the similar amount of power generation, weight
and efficiency of these motors were focused in comparison. Figure 3-1 demonstrated
these differences of these motors. All collected data were for 100 KW motors.
Figure 3-1: Comparison based on weight and efficiency of 100 KW motors
According to Figure 3-1, PM provided maximum efficiency with the
minimum motor weight for 100 KW power. Considering all these characteristics
following weighted comparison model has been generated in order to obtain the most
appropriate choice for this application.
BDC IM PM SRM
Weight (Kg) 70 42 30 50
Efficiency (%) 80 93 92 90
0
10
20
30
40
50
60
70
80
90
100
51
Table 3-2: Comparison model of different electric motors
Criteria Scale BDC IM PM SRM
Weight 1-10 9 8 5 7
Cost 1-10 5 7 9 7
Size 1-10 9 8 6 7
Maintenance 1-10 9 8 8 8
Motor selection criteria were chosen as weight, cost, size, maintenance and
efficiency of the motor. Comparison model was built based on weighted ranking
method. Ranking range was from 1 to 10 where “1-4” was considered as poor, “5-7”
as average and “8-10” as high. However manufacturing costs favoured SRM over
PM’s as discussed in 2.2.4.2. The SRM used a smaller air-gap than the PM motor,
but magnet cost more than compensated for this. According to Table 3-2 comparison
model based on the literature review, the PM was found as the best choice for EV
applications in terms of size, efficiency and power to weight ratio and maintenance
even though cost and availability of permanent magnets were of concern. In this
research, permanent magnet brushless DC motors was chosen.
3.3 Vehicle Selection Vehicle specification was an important aspect of this design optimization
study. The vehicle was required to have enough space to accommodate the batteries
and control systems and the wheel motor was to be fitted with ease. As the weight
and size of the motor is proportional to its generated power, vehicle weight and
wheel size became very significant. The evaluation of existing vehicle specifications
was based on required power and torque, vehicle weight and wheel size with
mudguard clearance. In order to choose suitable specifications, vehicle data was
compared considering power, torque, tyre specification, vehicle outer dimension,
kerb weight, wheelbase, etc (I.J.M. Besselink, 2010).
Data from different sized vehicles were collected and studied in literature
review section 2.2.4.4. The evaluation were based on power required, weight and
mudguard clearance specifications (Wheel size). Considering weight, wheel size and
52
maximum power required, TOYOTA YARIS, SUZUKI SWIFT, HOLDEN CRUZE,
TOYOTA CAMRY ATTARA S and MAZDA 6 were compared in Table 3-3.
Table 3-3: Comparison of Different Vehicle Parameter (data collected from industry)
Engine Size
TOYOTA YARIS
1.5L Hatch
SUZUKI SWIFT
1.6L Hatch
HOLDEN CRUZE
2L Sedan
TOYOTA CAMRY
ATTARA S 2.4L
Sedan
MAZDA 6 2.5L
Sedan
Vehicle Size
L/W/H
3785/ 1695/ 1530
3765/ 1690/ 1510
4597/ 1788/ 1477
4815/ 1820/ 1480
4735/ 1795/ 1440
Wheel Base (mm)
2460 2390 2685 2775 2725
Weight (kg) 1045 1090 1522 1460 1471
Max power KW@ rpm
80@ 6000
92@ 6800
110@ 4000
117@ 6700
125@ 6000
Max Torque Nm@ rpm
141@ 4200
148@ 4800
320@ 2000
215@ 4000
225@ 4000
Tyre 185/60 HR15
195/50 R16
215/50 VR17;7.0J
215/60 VR16;6.5J
205/60 VR16;6.0J
Suspension System
MacPherson struts at
front, torsion beam, coil springs at
rear
MacPherson struts at front, Twist-beam at
rear
MacPherson struts at
front, multi-link at rear
MacPherson struts at front
and rear.
Double wishbone at Front, multi-link at rear
Brake Type
Front ventilated
disc brakes. Rear drum
Front ventilated disc brakes. Rear
drum
4 wheel disc brakes. Front
ventilated
Front Ventilated disc, Rear Solid disc
Front Ventilated disc, Rear Solid disc
Advantages of using small latest vehicle would be light weight structure,
inclusion of latest technologies. Small sized vehicles were found more promising
with Suzuki Swift sports or Toyota Yaris newer models. It was also considered that
old model of small vehicles did not have provisions for intended space requirements
for 17” wheels. Another advantage of small vehicles was less power requirement.
The data provided by the vehicle manufacturers showed that the maximum power at
53
a given RPM for small vehicles was lower than the medium sized vehicles. Medium
sized vehicles were considerable including Holden Cruze and Toyota Camry models
with latest technologies and light structured as compared to other models. In case of
medium size vehicles, more space could be achieved for in-wheel motor packaging,
but main disadvantage with this segment was power requirement higher than small
vehicles.
In-wheel motor technology required a larger wheel size and a larger clearance
between tyre and mudguard (M., 2011). Many vehicles came with a standard 16”
wheel diameter as shown in Table 3-3, which could be increased by a maximum of
2” according to the tyre and rim design regulations (Manual, 2012). An 18” wheel
diameter could accommodate a compact in-wheel PM motor. Holden Cruze had
wheel size R17 which could be increased to 19” according to the regulations. But the
torque requirement and vehicle weight was much higher. Therefore, Toyota CAMRY
Attara S 2012 model with tyre size R16 (~R18 with extension), weight 1460 kg and
maximum required torque 215 Nm at 4000 rpm was chosen for this study.
Removed weight of engine driven accessories and added weight of EV
system components determined the total weight of the retrofitted vehicle. First, it
required to specify the items to be removed from the vehicle. Engine, gearbox,
alternator, battery, radiator, hydraulic braking system was considered as the main
significant items at the front bay of the vehicle. Among these components, the
radiator was decided not to be removed so that it could be used in cooling
arrangement of the EV battery pack. And hydraulic braking system installed in the
existing vehicle was chosen to be kept same to avoid the cost escalation. As a result,
engine, gear box, alternator and battery were the removing items from the existing
vehicle. The weights of these items were measured practically from the vehicle,
Toyota Camry 2.4L Sedan which was provided in Table 3-4. Battery, motor and
controllers were also considered as added weights in the replacement of engine and
engine driven accessories. Table 3-4 below showed the selected vehicle specification
for analysis and the removed / added weight redistribution during retrofitting of the
EV.
54
Table 3-4: Vehicle specification and parameters for Toyota Camry Attara S
Vehicle Parameter & Specification
Vehicle Weight (kg) 1460 Length (mm) 4815
Retrofitted Weight (kg) 1710 Width (mm) 1820
Wheelbase (mm) 2775 Tyre R18
Track Width (mm) 1400 Ground Clearance(mm) 130
Wheel Weight (kg) 25 Height (mm) 1480
Weight Redistribution (Retrofitting)
Removed Items Weight (kg) Added Items Weight (kg)
Engine 140 Battery 330
Gear Box & Alternator 20 Motors (2) 60
Battery
10
Motor Controllers
30
3.4 Brake System Analysis Braking system for EV drive train was an important issue as weight, cost and
space required to package was a challenge. The brake analysis was done to verify the
existing brakes would be able to provide braking for the increased weight of the
vehicle. In the analysis thermal condition is also considered to obtain a stable result.
In the selected vehicle Toyota Camry Attara S 2012 model has disc brakes at
both front and rear wheels. Disc brake system was designed to take kinetic energy
and transferred it into heat energy. This heat energy was created by the driver by the
pressing of the brake pedal. The force was then converted into hydraulic pressure
which forced the piston to move inside the calliper. The piston movement forced the
brake pads in contact with the spinning disc. Friction between the brake pads and the
brake rotor generated heat which was then dissipated by hot air rising from the
surface of the disc (convection) into the atmosphere. Disc was the crucial part of the
braking system which absorbs the brake force applied by the vehicle. The magnitude
55
of brake pressure depends on the road conditions, velocity and loading condition of
the vehicle etc. as discussed in section 2.2.4.5.
3.4.1 FE Model details
The FE model contains the thermal input data in the structural analysis of the
brake disc. As the thermal input, heat flux, radiation and the convection data were
used. The FE mesh was generated using three-dimensional tetrahedral element. The
number of mesh nodes was 5003 and mesh elements was 2495. The smoothing of the
mesh was defined medium. The rigid body behaviour of the model was
dimensionally reduced. The coordinate system was defined as global.
3.4.2 Boundary conditions and input data for the analysis
The numerical simulation based on coupled static thermal-structural method
in ANSYS software was accomplished to analyse the brake disc of the existing brake
system. The parameter of brake application used for the analysis is given in the Table
3-5.
Table 3-5: Parameter used in the analysis
Disc Diameter 296 mm
Disc Thickness 28 mm
Vehicle mass 2010 kg
Rate distribution of the braking forces (Front/Rear) 55/45
The disc material used in the analysis was Grey Cast Iron. The thermo-
mechanical properties used in the analysis is given in Table 3-6. Toyota Camry
Attara has the front ventilated disc and rear solid disc. In this analysis, solid rear disc
with 25% proportion of brake pressure distribution was applied. The amount of
pressure distribution on both front and rear disc would be variable based on the
tunning of the proportioning valve. Brake force was calculated considering the
vehicle speed 110 km/hr. (30.55 m/s) and stopping time of the vehicle was 10 sec.
For the retrofitted vehicle weight 2010 kg the total brake force was calculated as
6140 N. As the rear wheels received 45% of the total brake forces, the amount of
56
brake forces at rear became 2763 N and each rear wheel received 1381.5 N brake
forces for the given condition. Now by calculating the vector components of the
forces, the resultant force, F acting on the rear disc was determined from the equation
below,
(3.1)
where, F = Force acting on the disc
= Force acting on the wheel = 1381.5 N = Radius of the tyre = 0.4572 m = Radius of the disc = 0.148 m
The force on the rear disc was calculated as 4267.7 N. The Pressure on the
brake pad was calculated using the force per unit area and the area of the brake pad
found from the CAD model was 0.00216 m2. The pressure was calculated as 0.969
MPa. In the static structural analysis, the hydraulic pressure applied on the brake pad
was 1 MPa.
Table 3-6: Thermo-mechanical properties of the disc material
Thermal Conductivity 52 (W m^-1 C^-1)
Density 7200 (kg m^-3)
Specific heat 460 (J/kg. °C)
Poisson’s ratio 25%
Coefficient of Thermal Expansion 1.1E-05 (C^-1)
Young's Modulus 1.1e+11 (Pa)
Angular velocity 157.89 (rad/s)
Hydraulic pressure 1 (MPa)
The initial temperature of the disc was 22ºC and the surface convection
condition was applied at all surfaces of the disc. Input data in static thermal analysis
module are shown in Figure 3-2.
57
Figure 3-2: Thermal load input data for the analysis
To obtain total deformation and the equivalent stress of the disc the static
thermal model was coupled with static structural module and the input data were as
shown in Figure 3-3.
Figure 3-3: Boundary conditions and load applied on the disc
58
3.4.1 Results and discussion
Figure 3-4 shows the thermal and elastic deformation of the disc. The
magnitude of the deformation varies from 0 to 0.2705 mm. The value of the
maximum deformation was recorded during the end of simulation at t=1 s. which
corresponded to the time of braking. This deformation depends on the specific heat
capacity of the material and the temperature generation of the disc in operating
condition. With the given magnitude of heat flux, convection and radiation for the
operating condition, the maximum temperature generated was 265.45ºC.
Figure 3-4: Total deformation found in the disc due to both the thermal and elastic load
Figure 3-5 presents the equivalent Von-Mises stress and the thermal strain
generated considering both thermal and elastic loading in the disc at the given
condition. The stress value varied from 0 to 533 MPa. The maximum value of the
stress was recorded at time t=1 s. The significant observation of the stress profile
would be a strong constraint near the brake pad of the disc. The maximum thermal
strain was recorded as 0.001 mm/mm which was observed in the area of applied heat
flux.
59
Figure 3-5: Von-Mises stress and thermal strain generated under the effect of thermal and elastic load
in the disc
The brake force was calculated considering an ideal condition of driving
where no slip or dynamic factors were counted. The analysis results showed that the
static thermal and structural module was fully coupled for the disc rotor and no
significant displacement or distortion was observed in the results which can affect
the safe operating condition of the disc rotor for the change of vehicle weight.
3.5 Suspension System Analysis Suspension system of the vehicle was another important design consideration.
If the existing suspension was required to be replaced or modified during retrofitting
the cost was going to escalate. This analysis was done to check the durability of the
coil spring under the effect of added weight of the vehicle. Total deformation was
analysed and compared with theoretical calculation of the maximum failure range of
the existing spring to verify the design constraint of keeping the existing suspension
for the retrofitted vehicle. System element of existing suspension was analysed to
validate the use of it after retrofitting of the vehicle as the added weight due to the
retrofitting was 250 kg. Current suspension system for Toyota Camry Attara S Sedan
included independent, MacPherson struts, coil springs and ball-joint mounted anti-
roll bar at front and independent, MacPherson struts, coil springs, dual lower
transverse links, lower trailing arm, Gas dampers and ball joint-mounted anti-roll at
60
rear. Table 3-7 presented the dimensions of coil spring and strut damper of the
existing suspension.
Table 3-7: Properties of the spring and damper
Coil spring
Coil spring wire diameter 14 mm
Coil spring outer diameter 146 mm
Free length 338 mm
Spring constant 3.85 Kg/mm
Effective turns 5
Strut damper
Piston rod diameter 22 mm
Piston diameter 36 mm
Stroke 200 mm
Analysis based on changing weight due to retrofit of the vehicle was carried
out using ANSYS. Analysis indicated that there was 250 kg increase in vehicle mass
due to addition of EV batteries and other electronic drive components. Current
suspension system was 14 mm by 146 mm with MacPherson strut. To get the force
load active on the suspension system for analysis, the weight of driver and passenger
were taken under consideration. The retrofitted vehicle weight was as 1710 kg.
Considering driver and passenger weight of 300 kg, a force load of 1005 kg (half of
total weight 2010 kg) was applied in the negative y direction from the top to
compress the spring. Current front and rear suspension includes 4 coil springs in the
vehicle. The total weight was meant to be divided into 4 portions. The magnitude of
load experienced by the spring in the dynamic condition was regulated by the road-
surface friction and the load distribution of the vehicle. To analyse the worst possible
condition half of the vehicle weight on one coil spring was used as the force load.
The spring was meshed with 10-node tetrahedrons using a global side length of 5
mm. With all the loads and fixed support applied and mesh completed, the material
61
properties were selected to be linear, elastic and isotropic. A modulus of elasticity of
30x106 psi (2109 kg/mm2) and Poisson’s ratio of 0.3 were inserted. Analysis showed
maximum deformation of the spring (Figure 3-6) for the estimated vehicle load was
125 mm and maximum stress developed was 492 Mpa as shown in Figure 3-7.
Figure 3-6: Total deformation (elastic) of the spring
Now according to the Hooke’s Law,
F = KX (3.2)
where, F = Force needed to extend or compress a spring = 1005 kg K= Spring Constant = 3.85 kg/mm X = Displacement of the spring due to the force F
From the equation the displacement of the spring was calculated as 261 mm
which was more than the actual displacement of the spring due to the load. Analysis
results indicated suitable performance with safety of more than 2 times with
increased load on vehicle.
62
Figure 3-7: Normal stress of the spring
3.6 Battery Packaging Placement of EV drive train components in the vehicle the suitable and
enough space were required to be selected. Suitable space was needed to be arranged
by modifying the automobile body or chassis in some cases. But as retrofitting
involved with the cost reducing agenda for the growing EV industry, modification of
automobile body and chassis were meant to be avoided.
In terms of space to fit in the drive train following options of places were
taken under consideration:
Front engine bay (Bonnet),
Rear boot,
Mid area under the passenger seat of the vehicle,
Drive wheels (In-wheel Propulsion),
Spare wheel bay,
Fuel Tank space.
63
3.6.1 Selection of suitable places in the vehicle
The front engine bay or bonnet of the vehicle would be empty after removing
engine, gear box, alternator and battery. This space could be utilized to accommodate
EV drive train components. It had the weather protection. Drive train components
only required the mounting arrangement in the front bay. If the battery pack was
placed in the front bay, the radiator could be used for the cooling arrangement of the
pack. It had another advantage that this set up would simplify the piping arrangement
for the cooling system and reduced the cost of that.
Choice of rear boot space would compromise the luggage capacity of the
vehicle. On the other hand, the space was well protected from weather. Placing
electronic device would be safe from rain water in this space. With the rear boot
there was a space in the spare wheel carrier. In the in-wheel propulsion system for
the front-wheel drive (FWD) vehicle spare wheel would be only for the rear wheels.
If the spare wheel could be fit in the carrier at the back of the vehicle, the spare
wheel bay could be used to place the motor controllers.
The mid area of the vehicle was a good choice for the handling and stability
of the vehicle in dynamic condition as this space was close to the centre of gravity of
the vehicle. At the mid area of the space was under the passenger seat close to the
ground. In this way, the weight of the placing items would move down the vertical
centre of gravity of the vehicle which was preferable for the balancing of the vehicle
in dynamic condition specially in cornering dynamics. Another advantage of this
space was during retrofitting the fuel tank could be removed. Toyota Camry 2.4L
sedan had 70 litre fuel capacities. There would be a suitable space to place EV
components after removing the fuel tank.
For the in-wheel propulsion system, the drive wheels could be considered as
the spaces to fit in the electric motor inside. Selected vehicle Toyota Camry 2.4L
sedan had front wheel drive system. To keep the existing steering system set up drive
wheel was decided to be front drive. Two permanent magnet brushless DC motor
were decided to be fitted inside the front drive wheels.
EV components that need to be packaged in the vehicle during retrofitting
were mainly Battery pack, electric motor and motor controllers. There were three
possible spaces to place these three components in the vehicle which were front
64
bonnet, mid area of the vehicle under the passenger seats occupying fuel tank space,
the rear boot accompanied with the spare wheel space and front wheels. Motors were
to be inside the front wheels. In this situation, battery pack and the motor controllers
could be placed in front, mid and rear space of the vehicle. As the battery pack was
of 330 kg, this weight was the significant factor of determining the load condition of
the retrofitted vehicle.
3.7 CAD model of the load distribution layouts Based on three options of spaces in the vehicle to place the battery packs and
motor controllers three architectural layouts of the vehicle were chosen for the
analysis. These three architectural layouts presented three load distributions of the
retrofitted vehicle. The CAD models were generated to demonstrate the placing of
EV drive train components on the selected vehicle. Considering front (bonnet), mid
(under the passenger seats) and rear (boot) space of the vehicle, three architectural
layouts was suggested to be evaluated through the dynamic analysis. Those are:
1. Front-loaded Layout
2. Mid-loaded Layout
3. Rear-loaded Layout
3.7.1 Geometry Considerations for the CAD Model
In CAD model, the basic dimensions of the vehicle maintained as Toyota
Camry Attara S 2012 model. Basic dimensions included chassis with wheel-base,
track width, wheel size and ground clearance of the vehicle. The outer automobile
body was modelled using surface geometry. The shape of the outer body was not
modelled according to the existing vehicle to avoid the exhaustive representation of
the surface geometry and keep it simple only for demonstration purpose. After
modelling the chassis by maintaining the basic dimensions of length width and
height, the exterior panels were modelled by simplifying the detail enormously. The
detailed surfaces needed to define their contour, including the gaps between different
panels of the body surface or identify the rigid and moving parts (automobile doors)
or metal body and glasses. The interior arrangement of the vehicle was also
65
simplified by modelling only 2 seats with the dashboard. As the CAD model was to
demonstrate the placing arrangement of the EV components, simplified model was
adopted. The chassis, dashboard with seats, bonnet, main automobile body, door,
hood, battery pack, wheel, drive shafts, and motor controllers were designed
separately in part modelling and then assembled together.
3.7.2 Front Loaded Layout (Case I)
Front loaded layout demonstrated the major portion of the vehicle load at the
front. The removed weight from the vehicle during retrofitting was 170 kg and the
added weight was 420 kg. So, the extra weight added due to the retrofitting of the
vehicle was 250 kg. The major portion of this extra weight was the weight of the
battery pack. If the battery pack was placed in the front bay, it presented the major
load at the front side of the vehicle. The front-loaded layout was designed
accommodating the battery pack in the front bay, the control unit in the rear boot
keeping the spare wheel in the existing way, and the motor inside the front wheel as
shown in Figure 3-8. In this load distribution layout, the luggage space in the rear
boot was compromised due to the placement of the motor controller as shown in
Figure 3-8.
Figure 3-8: Front-loaded Layout
Battery
Motor Front
Rear
Motor
Controller
66
3.7.1 Mid Loaded Layout (Case II)
Mid-loaded layout accommodated the battery pack at the mid area under the
passenger seats as shown in Figure 3-9.
Figure 3-9: Mid-loaded Layout
As the size of the battery pack was large, placing it under the passenger seats
can cause the discomfort to the passengers. That’s why the fuel tank was removed
from the existing vehicle so that battery pack could be placed comfortably in there.
The motor controller was placed in the spare wheel space and the motor inside the
front wheel as the front loaded layout. In case II layout, the luggage space in the rear
boot was kept empty.
3.7.1 Rear Loaded Layout (Case III)
A significant change in the rear-loaded layout was the battery pack in the rear
boot space of the vehicle and controller in the front bay (Figure 3-10).
Battery
Front
Rear
Motor
Motor
Controller
67
Figure 3-10: Rear Loaded Layout
In case III layout, as the battery pack was placed in the rear boot, the luggage
capacity was compromised. The motors were placed inside the front wheel as other
architectural layout of the vehicle. In this layout, the space in front bay was not
utilized properly.
3.8 Load distribution of the vehicle Load distribution of the vehicle was important in improving vehicle
performance in terms of safe handling and stability. It was one of the dependencies
of locating the centre of gravity (CG) position in the vehicle. Architectural
orientation of the vehicle determined the load distribution of a vehicle. Placement of
components along longitudinal, lateral and vertical direction of the vehicle regulates
the load distribution ratio of the vehicle in each direction. In this study, longitudinal
and lateral load distribution was calculated in front, mid and rear loaded architectural
layout.
3.8.1 Longitudinal load distribution
The longitudinal placement of the EV components battery pack, motor and
motor controllers determined the longitudinal load distribution of the vehicle. It
Battery
Front
Rear
Motor
Motor
Controller
68
showed the percentage ratio of the front and rear load of the vehicle. The load
distribution of the existing vehicle Toyota Camry 2.4L sedan was 56.5:43.5 (front:
rear load distribution). Considering this load distribution of the existing vehicle, the
added and removed weight of the retrofitted vehicle and their longitudinal distance
from the centre of the wheelbase, longitudinal load distribution for each load
distribution case was calculated.
3.8.1.1 Longitudinal load distribution: case I
To calculate the longitudinal load distribution in case I following
considerations was used as described in table below:
Table 3-8: Longitudinal load distribution of front loaded layout (Case I)
Item Weight
(kg)
Distance from the centre of
the wheelbase (mm) Direction
Removed
Weight
Engine 140 1687.5 Towards Front
Gear box-
Alternator 20 1687.5 Towards Front
Battery 10 1687.5 Towards Front
Added
Weight
Battery
Pack 330 1687.5 Towards Front
Motor 60 1387.5 Towards Front
Motor
Controller 50 1500
Towards
Rear
From these data, longitudinal load distribution for case I was calculated as
58:42.
3.8.1.2 Longitudinal load distribution: case II
Longitudinal load distribution for case II was calculated from the following
data as given in table below:
69
Table 3-9: Longitudinal load distribution of mid loaded layout (Case II)
Item Weight
(kg)
Distance from the centre of the
wheelbase (mm) Direction
Removed
Weight
Engine 140 1687.5 Towards Front
Gear box-
Alternator 20 1687.5 Towards Front
Battery 10 1687.5 Towards Front
Added
Weight
Battery
Pack 330 200
Towards
Rear
Motor 60 1387.5 Towards Front
Motor
Controller 50 1500
Towards
Rear
From these data, longitudinal load distribution for case I was calculated as
49:51.
3.8.1.3 Longitudinal load distribution: case III
Longitudinal load distribution for case II was calculated from the following
data:
The load distribution of the existing vehicle – 56.5:43.5
Table 3-10: Longitudinal load distribution of rear loaded layout (Case III)
Item Weight
(kg)
Distance from the centre of the
wheelbase (mm) Direction
Removed
Weight
Engine 140 1687.5 Towards Front
Gear box-
Alternator 20 1687.5 Towards Front
Battery 10 1687.5 Towards Front
Added
Weight
Battery
Pack 330 1500
Towards
Rear
Motor 60 1387.5 Towards Front
Motor Controller 50 1687.5 Towards
Front
70
From these data, longitudinal load distribution for case III was calculated as
37:63.
3.8.2 Lateral load distribution
Lateral mass distribution of the vehicle was an important factor during
cornering for easy manoeuver. It was crucial to maintain lateral load distribution
equal to both sides. When the vehicle was starting to turn, load transfer occurred in
lateral direction towards the outside tires of the vehicle. If the load distribution would
not be equal in left and right side of the vehicle, one side of tyres faced intrinsic
amount of weight force during either left or right turn. Huge amount of weight
transferred towards one side of tires could cause skidding. In this study, all three
layouts with different longitudinal load distributions, lateral placing arrangement of
the components were maintained as 50:50 left to right. For each layout, extra weight
(250 kg) added during retrofitting was distributed equally to both the left and right
side of the vehicle. In this way the existing stability condition of the vehicle would
not be affected by the lateral load distribution after retrofitting.
3.9 Vehicle performance and Effect of CG CG is the point of equilibrium which is the mean location of all gravitational
forces acting on a vehicle. Position of CG plays an important role in improving
vehicle performance in terms of safe handling and stability. In this study,
determining the center of gravity was a complicated procedure because the load
might not be uniformly distributed throughout the object. Load distribution and CG
of the vehicle directly affected a variety of dynamic characteristics
including handling, acceleration, and traction and component life.
Placing of different EV components and drive train accessories changed the
position of CG along the vehicle and the dynamic stability of the vehicle with it. As
this study was concerned about the retrofitting of electric vehicle, load distribution
became more important in determining the CG of the vehicle than it was in case of
ICE vehicles. In case of conventional ICE vehicles, other factors such as track width,
length of wheelbase or suspension system could be changed. But due to the cost
71
effectiveness issues of EV, it was vital to maintain the systems of the vehicle body as
existing.
Except load distribution, there were other regulatory factors to control the
position of CG. Those are: vehicle track width, vehicle weight, length of wheelbase,
suspension system etc. In case of retrofitting, length of wheelbase could not be
changed. A little modification could be achieved in track width by modifying the tire
profile. Suspension system might also be changed by adding stiffer spring. So among
these factors, load distribution had an intrinsic effect in case of retrofitted EV in
determining the CG.
3.9.1 Calculation of longitudinal CG
Longitudinal position of CG included the longitudinal distance of front (lf)
and rear (lr) axle from the CG of the vehicle. ‘lf’ and ‘lr’ calculated considering all
weight items and their corresponding distance from the front axle as reference, using
the equation below:
∑ (3.3)
where, lf = Distance of CG from front axle. M = Vehicle weight. n = No. of item. m = Mass of component. lf = Corresponding CG distance of component from front axle.
In determining the longitudinal CG of the vehicle the weight items include
the added items (battery pack, motor, and controller) in the retrofitted vehicle and the
weight of the vehicle after removing the engine, gearbox, alternator and battery. The
distance of these weight items from the front axle were measured practically from the
vehicle.
3.9.2 Calculation of lateral CG
Lateral CG depended on the lateral load distribution of the vehicle directly.
As in this case, lateral load distribution was maintained as close to 50:50, the lateral
position of the CG would be at close to the centre of the track width of the vehicle.
72
The track width of the existing vehicle was 1400 mm. So the lateral distance of the
CG from the left or right wheel was found 700 mm.
3.9.3 Calculation of vertical CG
Vertical CG could be calculated experimentally in different ways. Lifting and
tilting were found very commonly used method of determining the vertical CG of the
vehicle practically according to the literature review. As in this case, retrofitting of
the vehicle was involved, height of CG (CGH) from the ground was calculated
considering all weight items and their corresponding distance from the ground as
reference, using the equation below:
∑ (3.4)
where, CGH = Distance of CG from ground. M = Vehicle weight. n = No. of item. m = Mass of component. CGH = Corresponding CG distance of component from ground.
In determining the vertical CG of the vehicle the weight items included the
added items (battery pack, motor, and controller) in the retrofitted vehicle and the
weight of the vehicle after removing the engine, gearbox, alternator and battery. The
height of these weight items from the ground were measured practically from the
vehicle.
3.10 Discussion and findings The main objective of this research was to evaluate the vehicle dynamic
behaviour in different architectural layouts of the retrofitted electric vehicle. The
basic significant factor to define the architectural layouts was the load distribution of
the vehicle which was dependent on the positions of different retrofitted weight items
in the vehicle. In this condition, selection of appropriate EV propulsion system,
electric motor and vehicle parameter were also important for retrofitting of EV. To
obtain the load distribution, the available places in the vehicle were measured from
the selected vehicle for retrofitting. After getting the required measurement from the
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vehicle, the longitudinal and lateral load distribution ratio of the vehicle was
calculated. From the weight of each component and the distance from a defined
reference the longitudinal, lateral and vertical positions of CG were calculated.
Results were presented in the Table 3-11 below according to case I, II and III. The
summery of different considerations of designing of the architectural layouts were
also associated with the load distribution and CG calculation results.
Table 3-11: EV component placement and different load properties of front, mid and rear architectural layouts
Criteria Front Loaded Layout (Case I)
Mid Loaded Layout (Case II)
Rear Loaded Layout (Case III)
Battery Location Front Bonnet Mid area
(Under the seats) Rear Boot
Motor Location Inside the Front Wheel
Inside the Front Wheel
Inside the Front Wheel
Controller Location Rear Boot Rear Boot Front Bonnet
Load Distribution Ratio (F/R) 58:42 49:51 37:63
Load Distribution Ratio (Lateral) 50:50 50:50 50:50
CG position - lf (Longitudinal)
(From Front Axle) 1165.5 1415.25 1748.25
CG position - lr (Longitudinal)
(From Rear Axle) 1609.5 mm 1359.75 mm 1026.75 mm
CG position (Lateral - From Both
Side) 700 mm 700 mm 700 mm
CG position (Vertical - From
Ground) 765.98 mm 742.62 mm 781.75 mm
In selection of suitable EV propulsion system for retrofitting, the basic
considerations were space savings for the battery pack and the rate of power loss due
to the transmission. In wheel technology was selected because it allowed more space
on board with the motor packaged inside the wheel when compared with other
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propulsions. It also provided zero transmission power loss because it redundant the
transmission gear between the motor and the drive wheel. Electric motor was
selected to suit the requirements of in-wheel propulsion system. The vehicle with
suitable parameter was also selected based on the in-wheel propulsion system. The
wheel diameter, space allocation for the battery pack and power required to drive the
vehicle were the basic considerations based on which the collected data from the
automotive industry was scrutinized and categorized. Among all the industry data on
different size of vehicles, a mid-sized vehicle was chosen. Toyota CAMRY Attara S
2012 model was selected for retrofitting in this study.
The sustainability analysis of the brake and suspension system of the existing
vehicle was accomplished to check the feasibility of the vehicle parameter selection.
The extreme thermal and elastic load condition was considered during the both brake
and suspension system analysis with the retrofitted weight of the vehicle. The brake
analysis results referred to the sustainability of the existing disc brake with the
retrofitted load at the given operating temperature. The safety analysis of the
suspension system concluded that the coil spring of the existing suspension could
carry two times more than the retrofitted weight of the vehicle.
To obtain the architectural layout the potential spaces were defined in the
vehicle described with their merits and demerits to suit the requirements. After
analysing different space options, the front bay, mid area under passenger seat and
the rear boot space were selected for the design iterations. The literature review on
the battery placement in the commercial EVs were also considered. In the CAD
model the architectural layouts based on the space selected were demonstrated in
three cases as shown in Figure 3-8, Figure 3-9 and Figure 3-10 accordingly.
The longitudinal load distribution was calculated for three cases as 58:42,
49:51 and 37:63. The lateral load distribution was maintained as the existing vehicle
to avoid the unstable dynamic condition during cornering manoeuvring. The
longitudinal, lateral and vertical CG positions were calculated for the retrofitted
weight of the vehicle as mentioned in Table 3-11. These result data were used as the
input value in the vehicle dynamic analysis in different manoeuvring conditions.
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CHAPTER 4
VEHICLE DYNAMIC ANALYSIS
Vehicle performance is considered as a function of the vehicle motion
according to the previous study. To obtain the vehicle performance data at the
dynamic condition, the analysis of the motion of the vehicle is required at a given
environment. This chapter focuses on the dynamic analysis of the vehicle
considering the three architectural layout cases demonstrated in section 3.7.2, 3.7.1
and 3.7.1.
The motion of the vehicle was based on the forces and moments acting on it
in both static and dynamic condition. These forces included the aerodynamic or air
drag force, gravitational force due to the mass of the vehicle, tractive force generated
by the electric motor and the rolling resistance caused by the friction between the
road surface and the contact patch of the tyre. The longitudinal force of the vehicle
which caused the translational motion of the vehicle was the vector sum of these
forces as discussed in literature review section 2.3. The vector direction of these
forces acting on the vehicle can be described by the following equation considering a
vehicle moving on an inclined road surface according to the literature (Rajamani,
2006):
(4.1)
where, = Longitudinal force on the vehicle = Tractive Force generated from the electric motor = Longitudinal aerodynamic drag force = Rolling resistance on the Tyres = Vehicle weight
= The inclining angle of the road
The longitudinal force acting on the drive wheel of the vehicle was the
primary force which made the vehicle move forward in a steady state driving. Forces
acting on the vehicle from tyre, gravity, aerodynamics and engine determined the
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dynamic behaviour of the vehicle. In this case electric motor used as driving force
which produced the tractive effort of all wheels causing translational motion of the
vehicle. The translational motion included both longitudinal and lateral motion.
These wheels also had resistive force working on them was known as rolling
resistance. There were some other resistive forces imposed on vehicle like grading
force and air drag force. Some vehicle components took part in dynamic behaviour
of the vehicle. The components related to vehicle motion, an overview were depicted
in Figure 4-1 to classify the acting forces based on their sources and behaviour.
Figure 4-1: Forces acting on different components
Handling characteristics of a road vehicle were considered as connected with
its response to steering commands and to environmental inputs affecting the direction
of motion of the vehicle such as wind and road disturbances. There were two basic
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concerns in vehicle handling: one was the control of the vehicle to a desired path, the
other was the stabilization of the direction of motion against external disturbances. In
case of retrofitting, placement of all EV drive train and other sub-systems required
both static and dynamic analysis for change in CG position due to different load
distributions. In this study, re-orientation of drive train components and other
subsystems in different places of the vehicle was considered to demonstrate the
effect of load distribution on dynamics of vehicle in different manoeuvring
conditions. The objective of this research was to analyse the effect of changing CG
on vehicle path while turning which would be useful to develop more robust control
strategy for vehicle stability. The stability analysis for vehicle motion relied on
vehicle dynamics. The vehicle handling and stability analysis required a vehicle
model that included all the components of vehicle dynamics those affecting on
vehicle stability. It indicated the need of a detailed and comprehensive vehicle model
to reproduce the behaviour of individual components as exactly as possible. Such a
vehicle modelling required equations of motions and interactions between
subsystems which were in the form of mathematical equations. Using these
mathematical equations, computer model was made that helped to analyse the
handling and stability of the vehicle in different manoeuvring conditions before
approaching towards controller design and prototyping.
This analysis focused on several vehicle handling features, such as polar
moment, path radius, tyre slip angle, lateral load transfer and tyre grip based on three
defined front, mid and rear load cases. Polar moment was subjected to determine the
intensity of the spinning capability of the vehicle and therefore, the reaction time
while turning. The radius of the path generated for a particular load case was to
decide the minimum radius required to perform a turn comfortably at a given speed.
A function of the slip angles of the front and rear tyres respectively defined the
behaviour of the vehicle in a targeted manoeuvre. If the ratio of the front to rear slip
angles was found nearly 1, the vehicle would tend to neutral steer. If the ratio was
calculated greater than 1(>1) and the slip angle produced by the rear tyre was greater
than the front tyre, then the vehicle would face under-steer handling. However, when
the ratio was less than 1(<1) and the front slip angle was greater than the rear slip
angle, then the vehicle would be over-steered (Pacejka).
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Figure 4-2: Forces acting on the tyres while cornering
Figure 4-2 explained the different forces acting on the tyre and their effects
on different vehicle dynamics features such as slip angle, and the actual and intended
direction of the vehicle.
4.1 Polar Moment The polar moment of the vehicle dictated the ease with which the vehicle
changes direction during steering. While vehicle changes direction in a corner, as far
away the centre of weight concentration located from the centre of gravity the
moment would be bigger. Ideal static mass distribution involved maintaining the
position of the centre of mass or centre of gravity (CG) towards the midpoint of the
vehicle in longitudinal, lateral and vertical direction. This ideal position of the CG
ensured that the centre of weight concentration was at the mid-area of the vehicle,
which improved the polar moment of inertia condition in terms of vehicle handling
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and stability in dynamic conditions. Balancing the load evenly in the vehicle
provided an even distribution for a balanced response to dynamic changes. By taking
the moment of each weight item from the centre of weight concentration, the
following equation was obtained.
W l – x W l x (4.2)
where, W = Weight of the vehicle at front W = Weight of the vehicle at rear, l = The distance of CG from the front axle l = The distance of CG from the rear axle, x = Distance of CG from weight-concentration.
4.2 Path Radius Radius of the curved path followed by the vehicle was based on the cornering
stiffness of the tyres, vehicle speed and CG position in the longitudinal direction. In
this calculation magnitude of the curved path was measured at a given speed during a
cornering situation in a certain steering angle of the vehicle. Eq. 4.3 (Rajamani, 2006)
was the governing equation to calculate the radius of the curved path.
(4.3)
where, R = Radius of the curved path,
= Longitudinal speed of the vehicle, = Cornering Stiffness of the front tyre. = Cornering Stiffness of the rear tyre.
= Steering Angle M = Vehicle weight
The retrofitting vehicle consisted of same tyre profile both at the front and
rear. So in this analysis, the cornering stiffness of the front and rear tyres were
considered as equal. Assuming equal cornering stiffness ( ) for the
front and rear tyres the equation 4.3 became:
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(4.4)
The cornering stiffness per degree of slip angle was taken to be 16.5% of the
vertical load on the tyre in each load condition The value of cornering stiffness was
assumed to be same for the both front and rear tyres in this study and maximum
speed of the vehicle was considered as 60 km/hr. Radius of the path followed by
vehicle determined a dynamic feature of the vehicle. At a given speed, the path
radius was based on the cornering stiffness of the tyre and CG of the vehicle which
were the functions of load distribution of the vehicle. The path radius determined the
intensity of the smooth response of the turning vehicle for a given speed under
different load conditions. The longitudinal CG position from the front (lf) and rear
(lr) axle value was taken from Table 3-11 in previous chapter.
4.3 Vehicle Model The control analysis and controller design for the vehicle motion relied on the
vehicle dynamic characteristics. Vehicle dynamic characteristics included the slip
angle generated by the tyres, side slip angle due to the lateral load transfer, trajectory
of the path followed by the vehicle in a certain manoeuvre etc. For an intelligent
control system design of a vehicle, it required to obtain the vehicle dynamics data in
different driving conditions based on the longitudinal, lateral and vertical position of
CG. A model based simulation consisting of different component blocks, such as
axle, wheels and body, using MATLAB SIMULINK was modelled in this study
(Hasan, 2012). The model was based on the equation of motion and interaction
between subsystems. The model was used to calculate the front and rear slip angles
and simulate the trajectory of the vehicle in load cases I, II and III. The detail vehicle
model in MATLAB Simulink is provided in appendix A.3.
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Figure 4-3: The schematic diagram of the simulation
A specific vehicle model was developed to calculate various vehicle
dynamics characteristics for a front wheel drive vehicle with the parameters selected
for retrofitting in previous chapter. The simulation was based on two manoeuvring
conditions. One was considering a sudden change in manoeuvre with accelerating or
braking and another was cornering situation of the vehicle. In both case the steering
angle of the vehicle was the significant factor for the simulation. All the components
of the model were developed in subsystems. In both case, the modelling assumptions
were same i.e. the model vehicle was simulated in same environment and road
condition. Figure 4-3 demonstrated the schematic diagram of the vehicle model.
4.3.1 Modelling Assumptions
In this simulation, some assumptions were made to avoid the complicacy of
the system. These assumptions were made for the vehicle model creation. These
defined the road condition, the intended direction of the vehicle, load condition of the
vehicle etc.
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4.3.1.1 Moving Load
The moving load on the vehicle included the passenger and luggage weight.
These load could be shifted anywhere in the vehicle. To ease the simulation process,
it was assumed that there was no moving load on any of the axles (passenger and
luggage) or on the front, mid and rear portion of the vehicle.
4.3.1.2 Camber Angle
The camber angle of the vehicle was taken as the angle between the drive
wheel and the vertical axis of the vehicle perpendicular to the ground. This angle
affected the contact patch area of the tyre directly. It changed the behaviour of the
suspension system of the vehicle. For a zero camber, maximum traction could be
attained in a longitudinally accelerating situation. To simplify the simulation, the
camber angle was considered as zero for all wheels including the driving wheels.
Another reason for considering zero camber was the MacPherson strut suspension
system. According to the automobile industry data, in Macpherson strut suspension
system the camber was being fixed. As in this retrofitting case, the existing
suspension was not replaced or modified; the adjusted camber was kept as current
condition.
4.3.1.3 Angle of Inclination
In the simulation, the vehicle was assumed to be steered on a plain road with
a zero degree inclined angle. This assumption was made to avoid the complications
due to the components of the force acting on the wheels caused by the angle of
inclination of the road.
4.3.1.4 Road Surface
The condition of road surface was determined by the friction coefficient of
the road (μ) which was also defined as the adhesive capability of the road surface.
When the tractive force acted upon the wheels this adhesive capability made the
vehicle move forward. For further increase in tractive force, the wheel would start to
slide. The frictional coefficient varied from different road conditions and the
properties of the road materials. Hence, the frictional coefficient was inserted into the
simulation as a constant value. Table 4-1 showed the average peak and sliding values
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of the frictional coefficient of the road surface in different condition and for different
material of the road as investigated in previous literature (Rajamani et al., 2010).
Table 4-1: Average values of the frictional coefficient of road surface
Surface Peak Values Sliding Values
Asphalt and concrete (dry) 0.8–0.9 0.75
Concrete (wet) 0.8 0.7
Asphalt (wet) 0.5–0.7 0.45–0.6
Grave 0.6 0.55
Earth road (dry) 0.68 0.65
Earth road (wet) 0.55 0.4–0.5
Snow (hard packed) 0.2 0.15
Ice 0.1 0.07
From Table 4-1 it was noticed that, on a dry road, the available μ could be up
to 0.9, but on a wet road, it could be 0.4 or lower not depending on a particular road
material. Here, this simulation was developed for a given coefficient of friction
(μ 0.6 .
4.3.2 Sudden Manoeuvring Vehicle Dynamics
Vehicle dynamic behaviour was simulated in sudden manoeuvring condition.
In emergency sudden unintended acceleration or brake was the main consideration in
simulating the model vehicle. The trend of the steering angle applied for this
simulation was based on the pattern of the standard stability test by Federal Motor
Vehicle Safety Standards (FMVSS). The main model was developed based on the
equation of vehicle motion. The basic consideration of this simulation model were
the vehicle moving forward with an initial velocity and sudden change of steering
input in both directions. The model could be used for both the acceleration and
braking situations. In this study, only acceleration was considered to obtain the
dynamic behaviour of the vehicle. The angular velocity, rolling resistance,
aerodynamic drag force at the frontal area of the vehicle, yaw rate, longitudinal,
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lateral and vertical or normal forces on the tyre were calculated in this simulation to
get the dynamic behaviour of the vehicle based on slip of the front and rear wheel,
longitudinal and lateral velocity, forces on the tyres due to the change of manoeuvre.
The position of CG was an important factor in this simulation which regulated the
dynamics of the vehicle for each layout. The vehicle model was presented in the
Figure 4-4.
Figure 4-4: Vehicle model in sudden maneuvering condition
4.3.2.1 The Motion Plane
The model was developed to simulate the vehicle motion on a plane which
related the vehicle body with the virtual world. In MATLAB SIMULINK, world
plane stood for the kinematic and geometric construct to define both the absolute
inertial reference frame and the absolute coordinate system. It possess that world has
a fixed origin and fixed coordinate which were defined as the positive X direction
was on the right, the gravity of the model was towards the negative Y direction and
the positive Z direction was towards out of the screen. Figure 4-5 showed the planar
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or ground joint used in this simulation to get the vehicle motion in relation to the
world plane or the absolute axis.
Figure 4-5: The Plane of the motion
4.3.2.2 Longitudinal, lateral and normal force
To analyse the effect of different load distributions on vehicle stability,
longitudinal forces generated on the drive wheel were considered in the model
vehicle. In case of cornering dynamic analysis, longitudinal forces in the X direction
was given as input data following the torque generation characteristics of an electric
motor, with a higher starting torque decreasing with time and finally fixed at constant
torque value. To find the longitudinal force ‘Fx’, the tractive force of the electric
motor Ft, aerodynamic force acting on the vehicle Fa, Rolling Resistance Force Fr
and force due to the inclination angle of the road were calculated. The limitation of
required torque to run the drive train of the vehicle caused by the retrofitting of the
vehicle was also considered. The required torque of the vehicle was 215 N-m. From
this, he required longitudinal force was calculated as 581.7 N considering the wheel
size R 18. So, the minimum longitudinal force generated from two PM motors fitted
inside the drive wheels was to be 581.7 N.
Tractive force Ft was found from the available permanent magnets
synchronous motors designed for industrial machines integration. These motors were
specially engineered to achieve the higher and higher performances required in the
automation field by a high torque capability at low speed and by the elimination of
the traditional components of the kinematic chain which allowed increasing the
precision and the efficiency of industrial machines. These types of PM synchronous
motors were available in the market with 150-300 N-m torque and 56-210 KW
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power. In this case, two PM motors of 220 N-m was considered to be sufficient to
generate the required power. A total torque 440 N-m was able to generate 1190 N
longitudinal force with the selected wheel size.
The longitudinal aerodynamic drag force Fa referred to the force required to
overcome air resistance. The equivalent aerodynamic drag force on the vehicle was
calculated using the equation 4.5 (Rajamani, 2006):
(4.5)
where, ρ = mass density of air = 1.225 kg/m3, Cd = aerodynamic drag coefficient = 0.26 [for passenger vehicle] AF = frontal area of the vehicle = 1.6+0.00056(M-765) Vwind = Wind velocity considered as zero
The frontal area of the vehicle was considered for passenger vehicles with
mass in the range of 800-2000 kg according to the empirical formula from the
literature (Rajamani, 2006). The aerodynamic drag force Fa was found as shown in
Table 4-2.
Table 4-2: The aerodynamic drag force calculated for three load cases
Fa (N) Case I Case II Case III
141.22 137.1 132.1
Rolling resistance force FR on the tyre was calculated from the model as
being proportional to the normal forces on front and rear tyres. The governing
equations (Rajamani, 2006) used for the calculation are given below:
(4.6)
where,
(4.7)
And
(4.8)
As no inclination was assumed for the road condition, the value of was
considered as zero. The value of rolling resistance coefficient CR was considered as
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0.015 which is a typical value for passenger cars with radial tyres. The height of
CGH was found from the Table 3-11 of the previous chapter and the height (ha) of
the location at which Fa acts was given as 0.75. From the simulation, FR was
calculated as 251.4 N.
In this simulation, the value of the longitudinal force Fx , lateral force Fy and
the vertical force Fz were obtained from the equations of motion of the vehicle body
as stated below (Rajamani, 2006):
cos sin (4.9)
sin cos (4.10)
sin cos
cos sin (4.11)
4.3.2.3 Steering Angle
The steering angle was based on variable speed and steer condition. The
angle was maintained zero for almost half of the duration of the simulation. Then the
fluctuation in the angle was applied in both directions as shown in Figure 4-6. The
magnitude of the steering angle was between +2 and -2 degree within 2 sec.
Figure 4-6: Steering angle for sudden maneuvering
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4.3.2.4 Velocity and Yaw rate
The velocity of the vehicle in both longitudinal and lateral direction and the
yaw rate were calculated from the simulation. The longitudinal and lateral forces
acting on the tyre were calculated from the tyre model by considering the cornering
stiffness and the rolling resistance. By solving the equation of vehicle motion
considering the CG position and aerodynamic force of the vehicle, the velocity and
yaw rate was calculated. The Simulink model of this calculation was displayed in
Figure 4-7:
Figure 4-7: Calculation of velocity and yaw rate
4.3.2.5 Front and Rear Slip
The wheels experienced a difference between the longitudinal velocity (Vx)
and the equivalent rotational velocity of the tyre depending on the frictional
coefficient of the tyre-road interface and the normal force acting on the tyre.
Longitudinal forces acting on the tyre was dependent on the longitudinal slip.
According to the literature, the longitudinal tyre force is directly proportional to the
slip ratio for a small slip. In case of large amount of slip, the longitudinal tyre force
needed to be calculated by non-linear mathematical model. The longitudinal slip for
front and rear tyres during acceleration was calculated for three load cases from the
equation (Rajamani, 2006) below:
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(4.12)
where, = Longitudinal Slip
= The effective radius of the wheel, = The rotational speed of the wheel
4.3.3 Vehicle Cornering Dynamics
The cornering performance of the model vehicle was simulated on a track,
where the maximum speed that a vehicle could maintain around a circular path on a
dry, flat surface was measured. The simulation of vehicle trajectory in cornering
condition of the vehicle was demonstrated in Figure 4-8. The detail of this simulation
was given in appendix 0
The main factors affecting the performance were the tyre characteristics and
the suspension system of the vehicle. The lateral acceleration, tyre traction with the
increase of vertical load and the steering angle for the cornering of the vehicle were
given as input to this simulation (Mazumder, 4-8 March, 2012, Mazumder, 2011).
Figure 4-8: Model for cornering behavior of the vehicle
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4.3.3.1 Sprung and Un-sprung Roll
Lateral forces in the y direction were generated in the simulation from the
sprung and un-sprung roll of the model vehicle at a given steering angle. In this
simulation, sprung mass represented the total mass of the car excepting the wheels
and chassis. And un-sprung mass was considered as the mass of the wheels and
chassis. Here, revolute block was inserted to one rotational degree of freedom in
which the follower body (F as noted in Figure 4-9) relative to the base body (B as
noted in Figure 4-9). And the joint spring and damper was placed in as a damped
oscillator in joint which was connecting the F and B body. This angular displacement
determined the roll of the vehicle due to the vehicle sprung and un-sprung mass on
the torsional spring joint and damper which was measured by the joint sensor and
given as input data into the wheel block of the main vehicle model to get the
cornering effect. In this joint sensor, the follower (F) and base (B) body sequence
and the joint axis determined the direction of forward motion of the vehicle.
Figure 4-9: Sprung and un-sprung roll calculation
4.3.3.2 Wheels Block
Wheels were divided into separate subsystem based on the drive wheels. In
this case, front wheels were considered as drive wheels following the similar
situation as the existing vehicle. Steering angle based on time was given as input
directly to the front drive wheels. The trend of the steering angle was chosen as
increasing with time to obtain the cornering effect on the vehicle. The maximum
steering angle was considered as 4º as shown in Figure 4-10.
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Figure 4-10: Steering angle for cornering dynamic model
Un-sprung, sprung and the wheel sensed roll (data from sensor) were
considered to calculate the force Fy for steady state cornering of the vehicle. The
lateral force Fy was then connected to the axle of the model vehicle through a joint
connector. The steering angle was entered into the drive wheel sub-system.
Figure 4-11: Lateral force on the front (drive) and rear wheels accordingly
4.3.3.3 Body Sensor Block
In this simulation, a sensor block was connected to the model vehicle body.
It was connected to define the motion of the coordinate system of the main body of
the vehicle. This sensor could measure any combination of translational position,
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velocity and acceleration; rotational orientation, angular velocity and acceleration
from which the vehicle position (x, y and z), the velocity of the vehicle (Vx, Vy and
Vz) and the angular velocity (roll, pitch and yaw) were obtained. This sensor
determined the yaw rate and therefore the direction and position of the vehicle as it
starts to roll over from which the slip angles of the front and rear tyres were
calculated in this simulation.
4.3.3.4 Vehicle Trajectory
When the drive wheels turned a different way to the desired direction, the
angle created between the actual and intended path of the vehicle was considered as
the slip angle. It was related to the lateral load or cornering force of the tyre. As the
lateral load increased due to higher cornering speeds, tyres tended to the outside of
the turn and therefore move in a direction that was different from their heading
direction. Slip angle changed proportionally with load transfer but not at a constant
rate. Tyre cornering coefficient declined as vertical load increased. The coefficient
was determined by the percentage of rated load that was represented by the actual
vertical load imposed on the tyre. Here, analysis was conducted based on the effect
of load cases I, II and III for a given cornering coefficient. In this analysis, slip angle,
α was calculated by using equation 4.13 and 4.14 (Rajamani, 2006) for front and rear
tyres:
∝ δ
(4.13)
∝
(4.14)
where, ∝ , ∝ = The front and rear slip angles,
= The steering angle, = The lateral speed of the Vehicle, = The Yaw Rate.
Here, V V and φ were generated from the vehicle model. In this analysis,
slip angles produced by the front and rear tyres were calculated with different
vertical loads on the tyre, considering the three load distribution cases.
The trajectory of the vehicle over time was calculated as a function of a
vehicle dynamic parameter. The calculation was based on the signal from the sensor
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connected to the model vehicle. The governing equation followed to obtain the
vehicle trajectories were for a front wheel steering vehicle of Ackerman steering
theory (Gillespie, February 1992) as given below:
| |
(4.15)
| |
(4.16)
Here, wheelbase (wb) and track (tr) were taken from Table 3-4 from the
previous chapter. V was the velocity of the vehicle and was considered as a control
parameter (Ackerman angle) calculated from the steering angle of the vehicle.
The trajectory of the vehicle was calculated over time starting from a location
which was plotted as the coordinate (0, 0). From the simulation, the vehicle position
in the x and y direction was plotted to obtain the trajectory of the vehicle on the
track. The sensor got the signal of the vehicle position according to the x and y
coordinates and plotted it on the track. The X-Y plot demonstrated different effects
for the three load distribution cases on vehicle trajectory. Vehicle trajectory
represented the actual and intended path of the vehicle so that handling
characteristics can be measured for a given steering angle for steady state cornering.
4.3.3.5 Lateral Load Transfer – Tyre Grip
When setting up a retrofitted chassis with an electric drive train and battery
pack, it was important to consider the lateral load transfer characteristics of the
vehicle. Traction generated by a tyre was considered as a decreasing function of
vertical load according to the literature as shown in ‘section A’ in Figure 4-12. The
detail of the simulation was given in appendix 0As the vertical load on a tyre
increased, the amount of traction went up, but at a decreasing rate. It was based on
several conditions such as camber, ambient temperature, tyre temperature and the
track surface condition, and obviously the type of tyre.
As the cornering dynamics of the vehicle was considered here, the centrifugal
force caused the vehicle leaned to outward or sideways at an increasing rate, which
was denoted as the lateral acceleration. Lateral acceleration was based on the speed
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of the vehicle, the road condition. It could be based on the timing of the driver’s
input in steering while entering the curved path which was not considered in this
simulation. In this study a function of lateral acceleration with time was considered,
referred to as section B in Figure 4-12. Lateral acceleration with time could move
under the curvilinear line shown in section B. For the current analysis the worst case
scenario was simulated by considering maximum amount of lateral acceleration that
has been used as input data. During cornering of a vehicle, the load was transferred
from the inside tyres to the outside tyres due to the centrifugal force. This reduced
the overall traction that the front and rear pairs can generate because the outside tyres
did not gain the amount of the traction force as the inside tyres lost. A subsystem of
vehicle model (Figure 4-12) for cornering dynamic analysis was created using
MATLAB-SIMULINK to calculate the amount of lateral load transfer and tyre grip
associated with it.
Figure 4-12: The calculation of Tyre Grip
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Lateral load transfer was calculated using the equation (Pacejka) below. CGH
was found from the Table 3-11 of the previous chapter.
LTL =LA M CGH/ (4.17)
where, LTL = Load transfer in the lateral direction, LA = Lateral acceleration
4.4 Results Results were obtained both from hand calculation and the vehicle model
simulation in sudden change in manoeuvring condition and during the cornering of
the vehicle. Results for different characteristics of vehicle dynamics were presented.
4.4.1 Polar moment
To get the polar moment ‘lf’ and ‘lr’ were taken from Table 3-11. The
distance of CG from the weight concentration of the vehicle, X was calculated for
three load cases from the moment equation. Therefore, the polar moment was
calculated from the product of vehicle weight and the distance of CG from the center
of weight concentration for each load condition. The vehicle weight was considered
1710 kg as stated in Table 3-4. Table 4-3 demonstrated the comparison based on
polar moment.
Table 4-3: Calculation results of polar Moment
Criteria Front-loaded
Layout (Case I)
Mid-loaded Layout
(Case II)
Rear-loaded Layout
(Case III)
Distance of Weight concentration
from CG 1.42 m 1.37 m 1.5 m
Polar Moment 2428 kg-m
2342.7 kg-m
2565 kg-m
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4.4.2 Path Radius
The radius of the curved path followed by the vehicle while driving at 20
km/hr. with 5º (left or right) steering angle were calculated as shown in Table 4-4 for
case I, II and III.
Table 4-4: Calculation results of Path Radius
Criteria Front-loaded
Layout (Case I)
Mid-loaded Layout
(Case II)
Rear-loaded Layout
(Case III)
Cornering Stiffness Equal in front and rear tyres
Equal in front and rear tyres
Equal in front and rear tyres
Path Radius 10 m 8 m 13 m
4.4.1 Velocity and Yaw Rate
The longitudinal and lateral velocity of the vehicle body was calculated from
the simulation. In three load distributions cases, Vx and Vy varied in a significant
magnitude. In each case, the variation in velocity was noticed within 8 to 12 sec time
period due to the fluctuation in steering angle at that time. The both longitudinal and
lateral velocity was presented in m/s in the figures below over time in each case of
load distribution.
Figure 4-13: Vx & Vy (m/s Vs time sec.) accordingly for front loaded layout
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Figure 4-14: Vx & Vy (m/s Vs time sec.) accordingly for mid loaded layout
Figure 4-15: Vx & Vy (m/s Vs time sec.) accordingly for rear loaded layout
The yaw rate for three cases was calculated as presented in figure below. The
magnitude of the yaw rate varied in a small amount for different load distributions of
the vehicle.
Figure 4-16: Yaw rate Vs time accordingly for front, mid and rear loaded layout
4.4.2 Front and Rear Slip
The front and rear slip were calculated from the simulation in the sudden
change in manoeuvring condition for three cases of load distribution. There was a
significant variation found in front and rear slip of the wheels for different load
distribution of the vehicle as shown in figure below.
98
Figure 4-17: Front and rear slip Vs time sec. (Front load case I)
Figure 4-18: Front and rear slip Vs time sec. (Mid load case I)
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Figure 4-19: Front and rear slip Vs time sec. (Rear load case)
4.4.3 Vehicle Trajectory
In case of demonstrating the cornering behavior of the vehicle, the X-Y plot
of the vehicle trajectory was very significant. In this simulation, slip angles generated
at the front and rear tyres were also calculated. Trajectory of the vehicle was
dependent on the slip angles occurred at the tyres. The magnitude of the slip angle of
front and rear tyres controlled the handling behavior of the vehicle while cornering.
In the 20 seconds simulation, the front tyres generated a slip angle of 0-1.3
and the rear tyres generated a slip angle of 0-1.78 degrees in case- I. The mid-loaded
vehicle (Case- II) generated 0-1.45 at the front tyres and 0-1.53 degrees at the rear
tyres. In case- III, the front tyres generated 0-1.9 and the rear tyres generated 0-0.55
degrees of slip angle within 20 seconds. From the cornering dynamic analysis, the
front slip angle was found lower than the rear slip angle in case I. For the mid-loaded
case II, the front and rear slip angles were almost equal. In the rear-loaded case III,
the slip angles created by the front tyres were greater than those by the rear tyres.
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Front and rear slip angle ratio obtained for case I, II and III are 0.73, 0.95 and 3.47
accordingly during cornering of the vehicle.
Figure 4-20: Vehicle trajectory plot (Front loaded layout)
Figure 4-21: Vehicle trajectory plot (Mid loaded layout)
Actual Path
Intended Path
Actual Path
Intended Path
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Figure 4-22: Vehicle trajectory plot (Rear loaded layout)
For case- I with 58% of total weight at the front of the vehicle, the front tyres
experienced a major portion of the vehicle weight, which caused a greater slip angle
to be created by the rear tyres than the front. The radius of the actual path of the
vehicle was much lower than the intended path as shown in Figure 4-20.
In case- II the vehicle followed a path with a radius slightly lower than the
radius of the desired path, as shown in Figure 4-21. The slip angles created by the
front and rear tyres were found almost same in this case.
In case- III, with 37% of the total weight at the front, rear tyres faced the
major portion of the vehicle weight, which caused a greater slip angle to be created
by the front tyres, as in Figure 4-22. In this condition, the vehicle followed the
curved path of a larger radius than the intended trajectory of the vehicle.
4.4.4 Lateral Load Transfer and Tyre Grip
From the results, it was evident that the tyre grip for a vertical load decreased
as the amount of load transfer increased, as shown in Figure 4-23.
Actual Path
Intended Path
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Figure 4-23: Tyre grip Vs. Lateral Load Transfer.
For case- I, the maximum tyre grip obtained was 0.95, which decreased to
0.59 at the 50th second with a lateral load transfer of 601 kg. Case- II showed a
decreased tyre grip of 0.6 at the end of the simulation, which was the maximum grip
gained in all three load cases. In case III the tyre grip obtained was 0.58 and the
decreasing rate was found to be the maximum as shown in Figure 4-23.
4.5 Discussion To achieve an optimized load distribution specifically designed for retrofitted
EV based on the vehicle dynamics characteristics, an evaluation of the three basic
load distributions was performed here considering a model vehicle for simulation.
0.5
0.55
0.6
0.65
0.7
0.75
0.8
0.85
0.9
0.95
10 100 200 300 400 500 600
Tyr
e G
rip
Lateral Load Transfer
Case I Case II Case III
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4.5.1 Analysis on polar moment and curved path radius calculation
The polar moment had a significant difference in three load cases as
presented in Table 4-3. Case- II generated the minimum polar moment among three
cases, which indicated that a mid-loaded vehicle will respond best during cornering.
The rear loaded vehicle was found very stable with slow response to the steering
input as the maximum polar moment was calculated for the case III. However, in
case of estimation of the vehicle performance very fast response to the steering input
could cause the vehicle inherently easier to spin.
The radius of the curved path followed by the vehicle while turning at an
intersection was traced by the outside front steer wheel in this calculation. This
radius was based on the given speed of the turning vehicle. Calculation results
determined that Case II vehicle could follow the minimum path radius without
skidding for a given speed as shown in Table 4-4. In this calculation, other significant
factors such as steering geometry, driver behaviour, and operational efficiency of the
system were not considered.
4.5.2 Analysis on sudden change in manoeuvre condition
The calculation of longitudinal and lateral velocity of the vehicle in case of
sudden change in steering input at a running condition presented significant variation
in three load distribution cases. The maximum longitudinal velocity Vx was 18.64
m/s for load case I vehicle and the minimum was 16.49 m/s. The mid-loaded vehicle
experienced the maximum Vx 18.35 m/s which was very close to the load case I. The
rear loaded vehicle of case III obtained the minimum Vx among three load cases
which was 18 m/s. It was noticeable from velocity analysis in case of sudden
manoeuvre that the front loaded vehicle generated the maximum forward speed. The
lateral velocity was demonstrating another important dynamic behaviour of the
vehicle during the sudden manoeuvre. Experiencing the lateral velocity at a
significant magnitude could be harmful to the stability of the vehicle. The maximum
lateral velocity Vy was calculated 0.195 m/s for the load case III. The mid-loaded
vehicle experienced the minimum Vy which was 0.12 m/s. According to the analysis
results, the load case II vehicle demonstrated the most stable handling in the sudden
change in steering condition.
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In case of yaw rate calculation, the different load cases demonstrated
different magnitudes in sudden change in manoeuvre condition. But the differences
noticed in yaw rate were not very significant. The maximum yaw rate was found in
case III in both left and right direction. The minimum yaw rate measured in load case
II was (+0.118) and (-0.192) in left and right direction accordingly as shown in Figure
4-16.
The front and rear slip were calculated for three load cases. As the vehicle
model was considered as the front drive wheel, the front wheel experienced more slip
than the rear in each load case. From the results shown in 4.4.2, it was noticeable that
the front slip generated in both left and right direction did not have significant
differences in magnitude for each load case. But the rear slip demonstrated a little
difference for the load cases and the load case I experienced the minimum slip as
shown in Figure 4-17. The maximum front and rear slip were found for load case III
and the magnitudes were 2.116 (front) and 0.0217 (rear) as shown in Figure 4-19.
4.5.3 Analysis on cornering behaviour of the vehicle
The vehicle trajectory created from the X-Y plot (Figure 3(b)) also
demonstrated that the mid-loaded case could be referred to as having neutral
handling characteristics. The front loaded vehicle showed oversteering while
cornering and the rear-loaded vehicle showed understeer handling, according to the
vehicle trajectory and slip angle ratio results. The front and rear tyre slip angle ratio
of the mid-loaded case was almost equal to 1 (0.95) that is close to neutral handling
criteria. The front and rear slip angle generated for three load cases was around 2º.
The model vehicle was simulated in a dry road condition with the frictional
coefficient (µ) of 0.6. The results referred to the stable manoeuvrability of the
vehicle according to the literature (Gillespie, February 1992) which proved that the
maximum limit of slip angle could increase up to 10º for dry road with different
values of µ.
Lateral load transfer was found to be minimum in case- II (Mid-loaded
vehicle), which gave better traction responses and tyre grip than the other two cases.
The tyre grip generated in the three cases differed slightly from each other. From this
calculation, the maximum tyre grip was achieved in the case of mid-loaded
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distribution of the vehicle. Figure 4-23 showed that tyre grip decreased with an
increase of lateral load transfer but not in the same proportion. A mid-loaded vehicle
provided a lesser decrease in the rate of tyre grip during a steering manoeuvre. When
these manoeuvring situations would happen over the recommended speed of the
vehicle, longitudinal and lateral forces could cross the limit of traction circle;
therefore wheels would start skidding and the vehicle lost stability.
4.5.4 Comparison based on dynamic behaviour of the vehicle
Table 4-5 presents the comparison based on the results found from the dynamic
analysis of the vehicle for different stability and handling characteristics in different
driving conditions.
Table 4-5: Comparison on dynamic analysis results
Dynamic Characteristics Analysis based on the results for the load cases
Polar Moment
Load case II was found as the most stable with fast response to
the steering input though the vehicle could easily spin while
cornering.
Path Radius The minimum radius of the vehicle path was calculated in load
case II
Longitudinal Velocity Vx Load case I faced the maximum Vx
Lateral Velocity Vy Load case II faced the minimum Vy
Yaw Rate Minimum yaw rate was calculated in load case II
Front and Rear Slip Load case I faced the minimum slip for front and rear wheels
Vehicle Trajectory
Case I – Over steering (small)
Case II – neutral (small oversteering)
Case III – under steering (large)
Tyre Grip Maximum tyre grip was found for case II though case I was
very close.
4.6 Findings By comparing the dynamic characteristics of the model vehicle with different
load distributions, it was noticeable that the front and mid loaded conditions had
more stable handling features than the rear load distribution. Hence, the mid loaded
condition was the best solution in terms of dynamic features. But mid loaded
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distribution was based on major portion of the added weight (battery pack) to be
placed at the mid area of the vehicle during retrofitting. Placing the battery pack at
the mid area of the vehicle included the packaging limitations such as the external
weather protection for the pack. On the other hand, placing the battery pack in the
front engine bay was more comfortable for designing the packaging arrangement.
These concerns led to proposing a new architectural layout for retrofitting. The new
layout was proposed by dividing the battery in two different locations. The layout
was based on the analysis results obtained for different dynamic characteristics of the
vehicle stability and handling as shown in Table 4-5. The layout also accommodated
the space available in mid and front area of the vehicle.
4.6.1 The proposal of a new architectural layout
The new proposed architectural layout was arranged by using the empty front
bay space after the removal of the engine and other accessories during retrofitting.
As discussed in chapter 3, the added extra weight due to the retrofitting of EV was
250 kg and the major portion of this extra weight was the weight of the battery pack.
The new layout proposed the 60% weight of the battery placed at the front bay. The
total weight of the battery pack was considered 330 kg. According to the 60% of
total weight calculation, the battery pack of around 200 kg was proposed to place at
the front bay at the conceptual stage. The weight of the selected battery pack was 65
kg per unit with connecting 25 cells of power density 0.46 kw/kg. 5 units of these
batteries were selected for the retrofitting from which 3 units were to be placed in the
front bay of the vehicle having the total weight of 195 kg. The rest 2 units of the
batteries were placed in the mid area of the vehicle. In this study, the batteries in
front bay was denoted as pack 1 and in the mid area as pack 2.
4.6.1.1 CAD Model of the proposed layout
The new architectural layout proposed the position of the weight items as:
60% of the battery pack (3 packs) in the front bay
40% of the battery pack (2 packs) in the mid area
The motor controller in the front bay
Motor inside the front wheels.
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The fuel tank was removed from the vehicle to accommodate 2 packs of
batteries in the mid area under the passenger seat. As this layout kept the rear boot
space empty, the luggage capacity of the vehicle would not be compromised in this
case. The layout was demonstrated in the Figure 4-24.
Figure 4-24: The proposed architectural layout
4.6.1.2 Load distribution
Placing the retrofitting items in different locations in the vehicle changed the
load distribution. The load distribution of the existing vehicle was 56.5:43.5.
The removing weight items from the front were engine, gear box-alternator
and the battery with the total weight of 170 kg. The distance of removing front
weight items from the centre of the wheelbase was 1687.5 mm towards front. As
mentioned earlier, there was no removing weight from the rear. The fuel tank (5 kg)
was removed from the mid area of the vehicle.
The adding weight items at the front for retrofitting were pack 1, pack 2,
motor and motor controller with the total weight of 420 kg. The Table 4-6 presented
Battery
Front
Rear
Motor
Motor
Controller
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the weight of the removed and added items and the distance of those from the centre
of the wheelbase.
Table 4-6: Load distribution of the vehicle
Item Weight
(kg)
Distance from the centre of
the wheelbase (mm) Direction
Removed
Weight
Engine 140 1687.5 Towards Front
Gear box-
Alternator 20 1687.5 Towards Front
Battery 10 1687.5 Towards Front
Fuel Tank 5 50 Towards Rear
Added
Weight
Battery
Pack 1 195 1687.5 Towards Front
Battery
Pack 2 135 200 Towards Rear
Motor 60 1387.5 Towards Front
Motor
Controller 50 1687.5 Towards Front
The longitudinal load distribution of the layout was calculated from the data
given in the table as 55:45. The lateral load distribution was maintained as 50:50 left
to right as the other layouts.
4.6.1.3 Calculation of CG
The CG in longitudinal, lateral and vertical direction was calculated for this
proposed architectural layout in case of the retrofitting of Toyota Camry Attara S
2012 as given in the table below:
Table 4-7: The longitudinal, lateral and vertical position of CG
Distance (mm) Reference
Longitudinal CG 1248.75 Front axle
Lateral CG 700 From left or right side
Vertical CG 751.57 From ground
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To validate the proposed architectural layout, experiment result data were
calculated and analysed in this study. In the experiment set up, a test vehicle was
taken under consideration due to the unavailability of Toyota Camry for retrofitting.
The test vehicle was experimented based on dynamic behaviour considering the
manoeuvring conditions from the simulation of Toyota Camry specification.
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CHAPTER 5
EXPERIMENT AND VALIDATION OF
PROPOSED LAYOUT
The front, mid and rear load distribution layouts considering Toyota CAMRY
specification were analysed and compared in terms of dynamic behaviour in different
manoeuvring conditions such as sudden change in steering and cornering of the
vehicle in section 4.5.4. The space availability and placements of EV components
during retrofitting were also evaluated in previous chapter. Dynamic analysis results
referred to the mid-loaded layout as the most suitable for vehicle stability and
handling both in sudden change in steering and cornering conditions, though it
included the difficulties in space allocation with designing a packaging arrangement
at the mid area of the vehicle under the passenger seat. On the other hand, the front
bay of the vehicle was the proper solution in terms of space availability while
retrofitting as the engine and engine driven accessories from the front were removed.
Moreover, the battery pack installed at the front did not require any extra protection
from the weather exposure in case of front load distribution. Furthermore, the
dynamic behaviour of the vehicle with front load distribution was found very much
similar to the mid loaded layout and even better in some characteristics of vehicle
handling and stability such as front and rear slip of the tyre. These concerns led to the
new proposal for the load distribution accommodating both the mid area and the
front bay of the vehicle as proposed in section 4.6.1. The new architectural layout for
EV retrofitting was proposed to obtain an acceptable solution in terms of the vehicle
handling criteria and an optimum use of space in terms of design criteria. But the
validation of the proposed architectural layout was required as the separating the
battery pack was not implemented earlier due to the wiring and cooling arrangement
complicacy. This study focused on finding an optimum solution so that the retrofitted
vehicle performance could be enhanced and well-accepted by the industry. Due to
111
the limitations of the resources, the experiment could not be set up based on an
existing Toyota Camry. This is why; the experiment was done considering a test
vehicle.
This chapter focuses on the validation of the new proposed architectural
layout based on simulation and experiment results of the test vehicle. The proposed
load distribution layout (Section 4.6.1) was applied on the test vehicle and the
experimental results are compared with the theoretical and simulation findings in this
chapter. After validation, the proposed load distribution was applied to the Toyota
Camry in simulation and the results were compared with the front and mid loaded
layout to check if the dynamic performance of the vehicle was increased.
5.1 Experiment Set up
Table 5-1: Drive train configuration of the test vehicle
Electric Motor
Power 1200W
Torque 35 n-m/282.5 rpm
Supply voltage 48V – 72V
Motor weight 12.5 kg
Speed 45/h
Sensor Type Hall sensor
Battery
Voltage 12V
Current 105 Ah
Cold Cranking Amps (CCA) 780
Length 305 mm
Width 168 mm
Height 207 mm
Terminal Height 213 mm
112
To validate the feasibility of the proposed architectural layout an
experimental platform was set up in the lab. A demonstration vehicle was designed
and built in the lab. The design of the vehicle was done using Solidworks. The
accessories of the power train of the vehicle such as electric motor, battery,
suspension springs and other commercial electronic items were bought from the
market. The electric motor was installed inside the wheel according to the in-wheel
technology. The weight items were placed to maintain the longitudinal load
distribution of the vehicle as 55:45 as proposed. To check the load distribution, the
vehicle was placed on the load measuring platform as shown in Figure 5-1. In the load
measuring platform, there were 4 load machines to collect the load on 4 wheels and
send the data to the electronic display connected to the machines. The placement of
the power train accessories is shown in Figure 5-1. Drum brakes were installed inside
the wheel of the vehicle. The other configuration of the vehicle drive train including
motor, brakes, battery etc. was as shown in Table 5-1.
Figure 5-1: Experiment set up of the vehicle in the lab
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The vehicle parameter used for the analysis was given in Table 5-2:
Table 5-2: Parameter of the vehicle
Vehicle Parameters
Total Weight (Without the Driver) 275 kg
Weight (With Driver) 335 kg
Wheel Base 1.78 m
Track Width 1.06 m
Battery Weight 27.4 kg
Tyre 3.00 -10”
The load on each tyre measured in the lab was:
Table 5-3: Load on each tyre
Vehicle Weight 275 kg (Without the driver)
Front Left Wheel 76 kg Front Right Wheel 75 kg
Rear Left Wheel 63 kg Rear Right Wheel 61 kg
Vehicle Weight 335 kg (With the driver)
Front Left Wheel 96 kg Front Right Wheel 95 kg
Rear Left Wheel 78 kg Rear Right Wheel 76 kg
From Table 5-3 it was noticeable that the lateral load distribution of the
demonstration vehicle was not symmetric. A very little difference was noticed when
measured the load on each tyre. The left side of the vehicle was loaded more than the
right side. The difference was around 3 kg from right to left side which was not very
significant.
5.1.1 Frictional Coefficient of the track (lab floor)
The frictional coefficient, µ of the vehicle path was dependent on the material
properties of the floor of the lab. The lab floor was made of concrete and according
to the Table 4-1, the frictional coefficient of the concrete was 0.8 – 0.9. In this case,
µ was considered as 0.9 for the analysis.
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5.1.2 CG Calculation
5.1.2.1 Longitudinal and lateral CG
The position of longitudinal and lateral CG was calculated accordingly from
the longitudinal and lateral load distribution of the vehicle from the wheelbase (1.78
m) and track width (1.06 m) of the vehicle. The longitudinal load distribution was
55:45 and the lateral load distribution was 51:49 which were calculated from the load
measured on each tyre. The longitudinal CG calculated was 0.801 m from the front
axle and 0.979 m from the rear axle. The lateral position of CG from the centre axis
of the left wheel was calculated 0.5194 m.
5.1.2.2 Vertical CG
The vertical CG (CGH) was measured from the weight of the vehicle on the
front wheels by weighing the rear side of the vehicle at 310 mm height (noted as ‘y’
in Figure 5-2) from the ground by a small crane in the lab. Lifting up the rear side at
the mentioned height made the angle of 10º with ground. The diagram of raising the
vehicle was as given here from which the equation of the CG height calculation
formed:
Figure 5-2: Diagram for CGH calculation
115
The load calculation on the front wheel when the vehicle was at horizontal
level, 1 (5.1)
From the Figure 5-2, the load calculation on the front wheel when the vehicle was
lifted,
1 (5.2)
From the geometry of the diagram,
(5.3)
Now equation (5.2) became,
1
≫ 1
≫
≫
≫
≫ (5.4)
where,
= Load on front wheel at horizontal level = Load on front wheel at inclined condition = Difference between horizontal and inclined load on front wheel
= Wheelbase =
The load, and were measured from the load calculating machine. To
consider the weight of the driver in the CGH calculation, a load bar of 60 kg was
attached on the driver seat. The Table 5-4 presented the measurement and the results
of CGH calculation of the vehicle:
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Table 5-4: Experimental data and result of the vehicle
Experimental Data and Results
191 kg
217.74 kg
26.74 kg
A 10º
1.78 m
W 335 kg
CGH 0.8058 m
The vertical CG calculation of the vehicle in the lab was shown in Figure 5-3:
Figure 5-3: Vertical CG calculation
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5.1.3 Measurement of turning radius
The intended radius of the vehicle was calculated and then the actual radius
was found by driving the vehicle to compare the experimental and theoretical results.
To get the intended radius of the vehicle, the desired steering angle was set as 4.5.
The steering angle was chosen to suit the magnitude of the radius with the lab space.
The desired radius was 4 m maximum.
From the Ackerman steering theory (Gillespie, February 1992), the intended
radius for the given steering angle is,
(5.5)
For the desired steering angle 4.5 and the value of wheelbase as 1.78 m,
the intended radius of the vehicle was calculated as 0.395 m. Then the intended path
of the vehicle was marked on the lab floor by following the calculated intended
radius.
5.1.4 Measurement of contact patch
The contact patch was calculated for front and rear tyre. The dimension of the
contact patch was demonstrated in Figure 5-4 (Rajamani, 2006).
Figure 5-4: The profile of contact patch of the tyre
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2a was the length of the contact patch, 2b was the width. The value of ‘a’ and
‘b’ were required for tyre force calculation of the vehicle from the tyre model.
From the data found for contact patch, the effective radius of the tyre, reff was
calculated from the relationship of the effective radius and the angle (∅) made by the
radial line joining the centre of the wheel to the end of contact patch. The equation
(Rajamani, 2006) used for the calculation was:
∅ (5.6)
To simplify the calculation, the contact patch area was considered as
symmetric along the longitudinal axis. The reff for 4 wheels did not have any
significant difference in the magnitude. The measured data of the tyre contact patch
and the calculated value of reff were given in the Table 5-5.
Table 5-5: Contact patch and effective radius of the tyre calculation
Length, 2a Width, 2b Effective
Radius, reff
Front left wheel 40 mm 25 mm
0.38 m Front right wheel 38 mm 24 mm
Rear left wheel 35 mm 20 mm
Rear right wheel 34 mm 19 mm
5.2 Experiment and simulation results for the test vehicle 5.2.1 Polar Moment
By taking the moment of the load on front and rear wheel from the centre of
weight concentration of the vehicle, the equation below was obtained.
(5.7)
The load on front and rear wheel and were collected from the Table 5-3.
The value of and were from longitudinal CG calculation. The distance of CG
from the centre of weight concentration, ‘x’ was calculated from the equation 27 as
0.06 m. The polar moment of the vehicle was found as 20 kg-m.
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5.2.2 Turning Radius
In this experiment, the vehicle was tested in a defined cornering track of 4 m
radius at a given speed of 10 km/hr. The vehicle was set at the steering angle of 4.5.
Experimental results presented the difference between the intended and actual radius
of turning circle followed by the vehicle. The vehicle followed a curved path which
was not very similar to the intended circular path marked on the track. The actual
path of the vehicle consisted of different radius at different points on the curve.
When the vehicle was turned left on the defined track, the average turning circle
radius followed by the vehicle was measured 3.7 m.
5.2.3 Vehicle Trajectory
Vehicle trajectory was calculated at cornering of the vehicle condition. This
calculation was done to check the findings from the experiment result of turning
radius of the vehicle. The actual turning radius of the vehicle was found lower than
the intended radius of the circular path. In the cornering dynamic simulation, the
given data was measured from the vehicle in the lab. The steering angle was given as
input according to the turning radius experiment. The slip angles at front and rear
tyres were calculated from the simulation shown in Figure 4-8. The front slip angle αf
and the rear slip angle αr were found as ‘0.727’ and ‘0.8186’ accordingly. From the
cornering model, the position of the vehicle in the X and Y coordinate was then
plotted to obtain the path followed by the vehicle while turning left. The intended
and actual path followed by the vehicle in the X-Y plot was demonstrated in the
Figure 5-5.
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Figure 5-5: Vehicle trajectory plot (Test Vehicle)
5.2.4 Tyre grip
To obtain the lateral load transfer from the inside tyres to the outside tyres
due to the centrifugal force during the cornering of the vehicle was very crucial in the
experiment for the proposed architectural layout. During the placement of the drive
train accessories of the vehicle, the lateral load distribution was not symmetric on the
left and right side. That is why the lateral position of CG also shifted slightly towards
left from the mid-point of the track width of the vehicle. As the transfer of lateral
load was a significant factor to regulate the grip of the tyre, the amount of load
transfer from the inside to outside tyres during left turning condition of the vehicle
was determined as shown in Figure 5-6.
Intended Path
Actual Path
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Figure 5-6: Lateral load transfer over time sec.
In the tyre grip calculation, the lateral acceleration with time and traction vs.
lateral load was used according to the full passenger road vehicles to consider the
worst situation for the analysis as shown in Figure 4-12. The grip of the tyre was
calculated from the ratio of the amount of traction produced by the tyre for the
corresponding vertical load. The calculated tyre grip over time was demonstrated in
Figure 5-7.
Figure 5-7: Tyre grip of the vehicle over time sec.
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5.2.5 Velocity and yaw rate
The longitudinal velocity, Vx and the lateral velocity, Vy was calculated
accordingly to the vehicle model as shown in Figure 4-7. The manoeuvring condition
considered for this calculation was sudden change in steering input of the vehicle.
The vehicle parameter and other specifications given as input in this model were
measured from the vehicle in the lab. For the calculated frontal area of the vehicle
and the given drag coefficient (Cd) depending on the vehicle dimension, the
aerodynamic force Fa was calculated as 12.46 N and the rolling resistance FR was
3.283 N. The steering input was given as shown in Figure 4-6. Based on calculated
Fa, FR and the forces on the tyre the longitudinal and lateral velocity (m/s) were
calculated as shown in Figure 5-8.
Figure 5-8: Vx & Vy (m/s Vs time sec.) accordingly for test vehicle
In case of the both Vx and Vy, the variation was noticed within 8 to 12 sec
time period due to the fluctuation in steering angle. The fluctuation noticed in the
trend of yaw rate was also at the same time period according to the steering input as
shown in Figure 5-9.
Figure 5-9: Yaw rate Vs time sec. for test vehicle
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5.2.1 Forces on tyres
To calculate the longitudinal, lateral and vertical forces on the tyres, a tyre
model was simulated following the Dugoff’s theory (Rajamani, 2006). In the
simulation the cornering stiffness Cα and the longitudinal stiffness Cσ of front and
rear tyres were given as input. The longitudinal force Fx and the lateral force Fy was
calculated from the equations stated below.
λ (5.8)
λ (5.9)
where,
λ / (5.10)
For λ a condition was applied in the simulation as, λ = (2-λ) for λ<1
and λ = 1 for λ≥1 (Rajamani, 2006). The assumptions for using Dugoff’s tyre
model were the uniform vertical pressure on the contact patch of the tyre measured
from the vehicle. The longitudinal and lateral forces (N) on each tyre were calculated
over time as shown in Figure 5-10 Figure 5-11 and Figure 5-12.
Figure 5-10: Longitudinal force, Fx (N) on each tyre over time sec.
Front left
Front right
Rear left
Rear right
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Figure 5-11: Lateral force, Fy (N) on each tyre over time sec.
The normal force on the tyre was calculated for front and rear tyre by taking
moments about the contact point of the corresponding tyre as explained in 4.3.2.2.
The Fzf and Fzr calculated for the test vehicle was shown in Figure 5-12.
Figure 5-12: Normal force Fzf and Fzr (N) on each tyre over time sec.
Front left
Front right
Rear left
Rear right
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5.2.2 Slip Ratio
For sudden change in manoeuvre the wheels experienced a significant
amount of slip. The slip was based on the effective radius of the vehicle which was
calculated from the contact patch measurement at the static loaded condition of the
vehicle in the lab. The angular velocity was calculated as shown in Figure 5-13.
Figure 5-13: Angular velocity rad/s over time sec.
The longitudinal slip, σx and lateral slip, σy was calculated for accelerating
condition. The total slip of the tyre was calculated by averaging the longitudinal and
lateral slip from the equation below as shown in Figure 5-14.
(5.11)
Figure 5-14: Total Slip, σ at front and rear tyre accordingly over time sec.
The value of slip for the complete sliding of the tyre, σm was calculated from
the equation 5.12 (Rajamani, 2006) below where the constant, θ was the function of
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tyre parameters and normal force and ‘k’ was the lateral stiffness of the tyre per unit
area from the relationship to the lateral stiffness per unit length ‘c’ as ‘k = c/2b’.
(5.12)
5.3 Analysis of dynamic results for the test vehicle The experimental data collected in the lab were given as input in the
simulation model to obtain the dynamic behaviour of the vehicle in both sudden
change in steering manoeuvre and cornering. In case of computing the turning radius
and the handling characteristics of the vehicle in cornering condition, experimental
set up was prepared and tested. During the path radius test, the vehicle was driven on
the defined track and the data collected by considering the driver weight. The other
experimental data such as contact patch, CG were collected considering the driver on
board, so that all the computational results could demonstrate the dynamic behaviour
in the same constraints.
According to the load distribution of the vehicle, the lateral load was not
symmetric from left and right side. From the polar moment calculation it was noticed
that the distance between the centre of weight concentration and the position of CG
was very small (0.06 m) which referred to the stable condition while cornering. The
results found both from simulation and experimental set up were summarized in the
Table 5-6.
Table 5-6: Summery of computational and experimental results for test vehicle
Dynamic Characteristics Proposed Layout
Lateral Load Transfer(kg) 197.4
Traction (kg) 175.2
Tyre Grip 0.8879
Polar Moment (kg-m) 20
Slip Angle ratio (Front/Rear) 0.89
Path Radius (m) 3.7
Handling Neutral (Slight Oversteer)
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5.3.1 Analysis based on cornering dynamics
In the cornering dynamic behaviour analysis, the turning radius of the vehicle
was calculated for a given steering angle and speed. It was then compared with the
theoretical circular path of the vehicle. The intended path radius of the circular track
was 4 m and the average radius of the actual path followed by the vehicle while
driving on the defined course in the lab was 3.7 m. The actual path radius was found
very close to the intended path radius. The actual path was smaller than the intended
path though the difference was not very significant. The actual curvilinear path was
not maintaining the same radius at all points of the path. In that course, two paths
were merging at some points and maintaining distance at some points. The
computational result of the vehicle trajectory also demonstrated the actual path
smaller than the intended as shown in Figure 5-5. The experimental and computational
simulation results presented the similar behaviour in cornering dynamics. In the both
cases, the handling characteristics of the vehicle were demonstrated as slight
oversteering and tend to neutral steering. Moreover, the front and rear slip angle
ratios was found 0.89 which was very close to 1. It referred to the similar vehicle
handling characteristic as tends to neutral with slight oversteering.
The maximum lateral load transfer from the inside to outside tyres while
turning left was calculated as 197.4 kg. The amount of load transfer in the lateral
direction was found big, because the vehicle was loaded more to the left side than the
right. Due to the centrifugal force acting while turning left, the left tyres were the
inside tyres of the curve. The tyre grip depending on the load on the tyre over time
was calculated as shown in Figure 5-7. The minimum grip was found 0.8879 and the
traction generated for the corresponding vertical load on the tyre was 175.2 kg.
5.3.2 Analysis based on tyre model
To develop the Dugoff’s tyre model in sudden manoeuvring change, the
components of the model were calculated using the simulation presented in Figure
4-4 and Figure 4-7.
The longitudinal and lateral velocity was calculated as 19.2 m/s and 0.55 m/s
accordingly. The results found for lateral velocity referred to the unstable condition
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of the vehicle due to the asymmetric load distribution in the lateral direction. The
yaw rate calculated was also referred to the instability in driving condition of the
vehicle, but not very significant as shown in Figure 5-9.
The longitudinal and lateral slip ratio (σx and σy) were calculated in sudden
steering change condition. From σx and σy the value of the total slip was calculated as
0.21 at front and 0.195 at rear tyres. Then the slip value (σm) for complete sliding of
the tyre was calculated and compared with the total slip (σ). The value of σ was
found lower than σm which referred to that total slip developed in the tyre was in the
limit. The maximum force F would be lower than the value of µFz. The maximum
slip occurs at the point when the maximum force developed in the tyre due to the
road-tyre friction as shown in the theory (Pacejka).
The longitudinal, lateral and vertical forces were calculated from the tyre
model developed for sudden manoeuvre. Among all the tyres, the maximum Fx and
Fy was generated at front left tyre due to the maximum vertical load on that tyre.
From the result of the normal force generated at front and rear tyre, it was noticeable
that the maximum force was generated also at front left tyre.
From the analysis results, it was established that the proposed architectural
layout was suitable for retrofitting of the electric vehicle based on the vehicle
handling and dynamic stability behaviour in different manoeuvring conditions.
5.4 Simulation of Toyota Camry based on proposed layout At this stage, the proposed layout was applied in the simulation of Toyota
Camry and compared the results with the front and mid loaded layout outcomes in
terms of vehicle dynamic characteristics.
Load distribution and calculation of CG were calculated for Toyota Camry
considering the proposed layout in section 4.6.1.2 and 4.6.1.3. The load distribution
was found as 55:45 and CG as shown in Table 4-7. These calculation results were
applied in the vehicle dynamic simulation for Toyota Camry as input data. The
substantial dynamic characteristics were analysed and compared with the front and
mid loaded layout results in the Table 5-7.
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Table 5-7: Comparison of proposed layout with front and mid loaded layout
Front-loaded Layout Mid-loaded Layout Proposed Layout
Vx (m/s) 18.64 18.35 18.58
Vy (m/s) 0.16 0.12 0.138
Front/Rear
Slip 2.15/0.015 2.13/0.018 2.11/0.0155
Drag
Force (N) 141.22 137.1 134.4
Vehicle
Trajectory
Slip Angle
Ratio (Front/
Rear)
0.82 0.95 0.9
Tyre Grip 0.59 0.6 0.598
Comparison in Table 5-7 demonstrated the significant characteristics of the
vehicle dynamic analysis in case of front loaded, mid loaded and proposed load
distribution layout. Analysis in chapter 4 showed the mid loaded layout as the most
suitable solution for retrofitting considering the dynamic behaviour of the vehicle.
The vehicle trajectory shown in Table 5-7 presented that the handling behaviour of
retrofitted Toyota Camry with the proposed load distribution layout smoother than
other layouts and the actual curved path was very close to the intended path of the
vehicle. These characteristics refer to the neutral handling of the vehicle. The rear
tyre slip for the proposed layout was found smaller than that of mid loaded layout
which refers to the better stability of the vehicle. The velocity of the vehicle in the y
(lateral) direction was found close to that of mid loaded layout which also refers to
the balanced stability of the vehicle in sudden change in steering. With the proposed
load distribution of the vehicle the aerodynamic drag force was found minimum. The
tyre grip was also found very close to that of mid loaded layout. The front and rear
Intended
Path
Actual Path
Intended
Path
Actual Path
Intended
Path
Actual Path
130
slip angle ratio was tended to 1 which refers to good dynamic handling of the
vehicle.
5.5 Findings The proposed load distribution layout was initiated by considering the
dynamic behaviour of the vehicle in sudden change in steering and cornering
conditions and to obtain the proper utilization of the space available in the existing
vehicle. The focus of this analysis was to get an optimum load distribution for the
retrofitting of the vehicle. The simulation and experiment were concentrated on the
feasibility of the proposed load distribution layout which involved 60% of the battery
pack in the front bay and the rest 40% packaged in the mid area of the vehicle under
the passenger seats. To check the feasibility of the proposal, the experiment and
simulation model were implemented in case of a test vehicle parameter and
evaluated. The proposed load distribution layout produced the acceptable results both
in simulation and experiment set up. Then the proposed layout was applied on
Toyota Camry to compare the dynamic behaviour of the vehicle with other load
distribution layouts. The results were compared with the front and mid loaded layout.
The comparison found the enhancement of the vehicle dynamic performance due to
the change in load distribution. The proposed load distribution layout in Toyota
Camry was found dynamically more stable and steady manoeuvre both in sudden
steering input and cornering conditions. The further study on designing the
packaging and cooling arrangement for the battery pack, structural and thermal
analysis of that was accomplished considering the proposed load distribution layout
of the vehicle.
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CHAPTER 6
STRUCTURAL ANALYSIS OF BATTERY
PACKAGING
The design of packaging arrangement of the battery was an important concern
of this research on EV retrofitting. The total battery pack was proposed to be
distributed into two locations as demonstrated in section 4.6.1. In this condition, the
packaging design of the battery faced a challenge due to the divided installing
arrangement of the pack. The design criteria of battery packaging arrangement
included the weather protection, the packaging for the super-controller and the
battery management system, the cooling system. Among these accessories, the
cooling system was the most important component in the design as it was required to
be installed with the battery pack. The crucial design constraint of the cooling system
was the selection of medium of the cooling. One of the limitations in retrofitting was
the space for assembling the battery packs in an EV. Hence, the liquid cooling
system was chosen for this study because of its compactness. Moreover, literature
review revealed that liquid cooling system was more effective than air cooling
system in terms of space and efficiency as discussed in section 2.5.1. In case of
retrofitting existing radiator was kept to be used for cooling. But ducting
arrangement for this system was an expensive and complicated design consideration,
as the battery pack was planned to be divided into two units and ducting was required
from the radiator in the front bay to the battery unit in the mid area.
This chapter focuses on the design of the packaging arrangement and the
cooling system for the battery pack. The design includes the CAD model and the
structural analysis results.
The safety analysis of this cooling system was required due to the liquid
coolant involved with the battery pack. To ensure the structural safety of the design it
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was required to be verified in a vehicle crash situation. To verify the structural
feasibility of the design, the vehicle crash was simulated to obtain the force,
displacement and stress experienced at the location of the battery pack during the
crash. At the conceptual stage of the design, a number of design targets and criteria
were considered. The cooling pipes were selected by following the Australian
standard for square hollow sections and the ducting arrangement of the cooling pipes
were proposed to be around the battery pack. To check the feasibility of the design,
two geometries for the design iterations were created. After the analysis, these two
design iterations were compared based on weight, overall size, equivalent stress and
deformation due to the force developed during the crash of the vehicle.
6.1 Conceptual design In conceptual design stage, the target was to combine different design criteria
to suit a range of performance requirements. Different design steps, inter-
dependencies among them and flow of the design process which characterize the
system holistically including both parallel and sequential interacting channels were
experienced in this stage in designing the cooling system of the battery.
Collaborating different design targets and accommodating the load distribution
proposal were the basic approach towards the conceptual design. The initial concept
was to design structurally safe cooling system for the battery pack. Then the concept
was clustered according to different requirements such as the feasibility of the design
during the crash of the vehicle, different design options to create different iterations.
These clusters were then categorized and scrutinized in order to devise a particular
description of each cluster. The process of the analysis was then formulated which is
demonstrated in the framework (Figure 6-1).
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Figure 6-1: Process flowchart of structural safety analysis of the battery packaging and cooling
arrangement
6.1.1 Design targets
In the conceptual design stage of the battery packaging arrangement, the
requirements of retrofitting of EV came into account. The space and volume required
for the design, the weight of the total arrangement, material used for this, the position
of the package to accommodate the pump and piping for the cooling system, the
durability of the design while experiencing the crash of the vehicle were the main
concerns in the design. To simplify the conceptual design of the battery packaging
arrangement, manufacturing considerations such as installing difficulties,
manufacturing techniques, number of components etc. was not taken under
consideration in defining the design targets. Easy setup of the arrangement was
considered during the design. Hence there were two main considerations in the
conceptual design stage which were:
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The design was to structurally survive the displacement, force and stress
generated during the vehicle - crash
The design was to operate in the heat generation due to the battery charging
and discharging
6.1.2 Geometry Definition
The increase of temperature, location of the hot spots, crucial parameters of
battery configuration, size, overall dimensions, the location of winding cooling pipes
or ducts were considered to define the geometry of the battery packaging
arrangement design. According to the literature review, the coolant pipes were not
sufficiently effective while placed at the bottom of the battery pack as the maximum
temperature was experienced near the TAB at the top of the battery. Moreover, the
cooling pipes could not be placed at the top due to the electrical hazards. So, the
piping arrangement was decided to be at the surroundings of the battery pack. To
enhance the cooling efficiency of the system the piping was around each battery unit.
The size of the piping was a crucial consideration due to the limited space available
for the battery pack. The overall dimensions of the Li-ion phosphate battery chosen
for retrofitting were as shown in Table 6-1.
Table 6-1: Outer dimensions of Li-Ion phosphate battery
Lithium Ion Phosphate Battery
Thickness [mm] 333
Length [mm] 615
Width [mm] 265
Weight [kg] 65
Some of the commercial battery packs consisted of channels at the outer
surface of the battery unit. These channels were used to place the ducting around the
unit. The thickness of the cooling pipe was another important consideration for the
geometry definition of the design. To decide this in conceptual stage, the data was
collected from the market about the standard piping dimensions. Structural cold
formed square hollow section of grade 350 was selected for which the sectional
135
properties were calculated in accordance with AS1250 (Australian Standard 1250,
Amendment no. 2).
6.1.3 Design Options
Two design options were considered in this case. Two different dimensions
of the cooling pipe were applied as design parameters. The weight of the cooling
system was an important factor for this design. Two different pipe dimensions of
grade 350 (Standard) were selected for two design options as given below.
Figure 6-2: Hollow square sections of the cooling pipe
Table 6-2: Sectional properties of Grade 350 (AU standard) steel
Dimensions Sectional Properties Design Values
d
mm
b
mm
t
mm
Nominal
mass
(kg/m)
Ext.
surface
area
(m2/m)
Ix
Gross
(106mm4)
Torsion
Constant,
J Gross
(106mm4)
Torsion
modulus
C Gross
(103mm3)
Yield
Stress
Fy
(MPa)
Ratio in
AS1250
2
Rule 4.3.2
20 20 1.6 0.873 0.0745 0.00608 0.0103 0.924 350 10.5
15 15 1.8 0.681 0.0538 0.00239 0.00431 0.491 350 6.33
136
The dimension ‘r’, corner radius of the section in the figure was applied as
‘2t’ according to the standard rule for sections with t ≤ 3mm. The design model with
pipe dimension 20x20x1.6 mm was denoted as design iteration 1 and the pipe
dimension 15x15x1.8 mm was denoted as design iteration 2.
6.1.4 Vehicle Crash Simulation
The crash test of the vehicle was simulated to get the stress developed at the
location of the battery packaging arrangement. A frontal impact test was simulated
by considering the outer shell and the chassis of the vehicle so that the stress
developed can be obtained from the finite element analysis.
The crash test was done using Ansys LS-DYNA (Mechanical APDL). To
simplify the crash test module, only vehicle outer shell and chassis were used by
removing the wheels, axles, seats and other accessories. A concrete wall was placed
in front of the vehicle and an impact velocity was applied in the vehicle initially. The
crash was prepared as a full-frontal barrier test. The material properties of the barrier
were given concrete (as given in Table 6-3) and the vehicle parts were steel.
Table 6-3: Material properties of concrete
Material Properties of concrete block
Density 2240 - 2400 kg/m3
Compressive strength 20 - 40 MPa
Flexural strength 3 - 5 MPa
Tensile strength 2 - 5 MPa
Modulus of elasticity 14000 - 41000 MPa
Permeability 1 x 10-10 cm/sec
Coefficient of thermal expansion 10-5 oC-1
Drying shrinkage 4 - 8 x 10-4
Drying shrinkage of reinforced concrete 2 - 3 x 10-4
Poisson's ratio 0.20 - 0.21
Shear strength 6 - 17 MPa
Specific heat capacity 0.75 kJ/kg K
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6.1.4.1 Boundary Conditions and Governing Equations
In this simulation, two types of contact and element formulation were
applied. One was node to node and another was node to surface. For node to node
EINTF type of mesh applied and the sliding of contact were small. To maintain near
zero penetration and slip, the Lagrange multiplier’s method was used for contacts
formulation (SESHU, 2003). This method was chosen to simplify the simulation by
avoiding dealing with the contact stiffness.
(6.1)
For the time discretization, the dynamic equation of motion was applied with
the integration of time t according to the explicit finite difference time integration
method denoting the acceleration, velocity and displacement.
(6.2)
/ / ∆ (6.3)
/ ∆ / (6.4)
where, = External nodal loads = Internal nodal loads
1/2, n, 1/2 = consecutive times ∆ = Time steps.
6.1.4.2 Nodal force, displacement and stress during the crash test
The outer shell and the chassis of the vehicle were modeled using
SolidWorks (Figure 6-3) and imported into ANSYS mechanical APDL module. Free
quad mesh was applied to the model. Material properties and other attributes were
entered into the system. Total time of the simulation was 0.5 sec. The concrete wall
was modeled using a single shell element and its velocity was set to zero. The initial
impact velocity of 18 m/s was applied to all nodes of the vehicle outer shell and
chassis.
138
Figure 6-3: CAD model of the Outer shell and Chassis for the specification of Toyota Camry
The nodal displacement, pressure and the stress developed were obtained
from the simulation. The nodes were detected from the K-file of the analysis results
according to the coordinates. The selected nodes were close to the front bay of the
vehicle as the battery arrangement at the front area was decided to be analyzed in
ANSYS transient structural module. Result file provided the X, Y and Z values of
displacement, force, rotation or moment in the coordinate system in accordance with
the selected nodes. In total 3 nodal time history outputs were defined which gave the
time history information on displacement and force transferred through the nodes.
The nodal force generated from the mechanical APDL module was given in Figure
6-4.
139
Figure 6-4: Nodal forces generated at 3 defined nodes with time
At the beginning of the simulation the system energy balance was checked to
ensure the stability of the solution. The time histories for the total energy in the
global system were found constant for the simulation.
The nodal displacement obtained in the crash simulation was shown in Figure
6-5 .
0
5
10
15
20
25
30
35
40
0 20 40 60 80 100
Forc
e (K
N)
Time (milisec.)
Node 1 Force (KN)
Node 2 Force (KN)
Node 3 Force (KN)
140
Figure 6-5: Nodal displacement in meshed view of the vehicle
The stress developed at initial stage t = 0 and at time t = 20 millisecond were
plotted. In the contour plot (Figure 6-6) the maximum effective stress were shown.
The nodal force obtained from this crash simulation was imported into the
transient structural analysis module. The total deformation, equivalent stress (Von-
mises) and safety factor were analyzed in case of two cooling pipe dimensions.
141
Figure 6-6: Contours of effective stress (v-m) at time
6.1.5 Design Model
For the two pipe dimensions two CAD model were created to perform the
structural analysis. The channel dimension surrounding the existing commercial
battery was found 20 mm in height and 10 mm in depth. Two dimensions of the
cooling pipes were chosen by considering this channel dimension. The thickness of
the outer casing was given 5 mm. The space required to fit this pack inside the front
bay of the vehicle was verified by taking the measurement from the existing vehicle
Toyota Camry Attara S year 2012 model on site. While verifying the space available
inside the front bay, the dimensions of the super controller and battery management
142
system was also considered. The CAD models were created using Solidworks as
shown in Figure 6-7.
Figure 6-7: CAD model created using SolidWorks
6.2 Mathematical model for the transient structural analysis The design was considered as nonlinear structural dynamics as the internal
load was not proportional to the nodal displacement and also the structural matrix
was dependant on this displacement. The nodal displacement was generated from the
dynamic crash simulation of the vehicle. Moreover, the temperature profile of the
battery packs according to the time was used as input value in the analysis. To
combine the time steps with these mathematical constraints, a generalized HHT-α
form of the time integration operator was used which was obtained from the Newton-
Raphson method (Hughes., 1987). The nonlinear equations of motion for transient
structural analysis used here are given below:
∆ 0 (6.5)
143
1 ∆ (6.6)
where, [M] = Structural mass matrix [C] = Structural damping matrix u(t) = Nodal displacement vector
=
∆
=
∆
∆ = The displacement increment of (un+1) at the kth iterations = The residual vector
6.3 Computational Analysis The primary requirement of the computational analysis in time integrated
structural analysis was to ensure the convergence of the governing algorithms. The
rate of convergence of the algorithm was dependant on consistency and stability of
the characteristics defining the algorithm. The proper definition of these
characteristics was very significant to obtain the quality of the convergence. The
material properties, the meshing and the boundary conditions were defined in detail
here to describe the behaviour of the computation.
6.3.1 Material Properties
The design was involved with three different types of components.
Battery
Pipe
Casing
The material assigned for the battery was aluminium alloy. The mechanical
properties of the material are given below:
Table 6-4: Mechanical properties of Aluminum Alloy
Density 2770 kg/m3
Modulus of Elasticity 68.9 GPa
Poisson’s ratio 0.33
Tensile yield strength 276 MPa
Bearing yield strength 386 MPa
Shear Strength 207 MPa
144
The casing component was supressed to simplify the analysis part. The
material assigned to the cooling pipes was structural steel of grade 350 according to
the Australian standard. The mechanical properties of this material are given in Table
6-5.
Table 6-5: Mechanical properties of Grade 350 steel
Density 7850 kg/m3
Young’s Modulus 2e+05 MPa
Poisson’s ratio 0.33
Tensile yield strength 250 MPa
Compressive yield strength 250 MPa
6.3.2 Meshing
Mesh generation was an important factor for this analysis due to the pipe and
the battery contacts. The tetrahedral mesh was applied in this analysis. The
tetrahedral mesh provided the ability to add mesh controls at the critical zones. To
avoid the impairment during the run-time with the high element count and unsmooth
mesh shape, the refinement was applied to the critical places near the contacts of the
battery and the cooling pipes. The connectivity of the mesh was maintained
automatically. Figure 6-8 showed the tetrahedral mesh of the structure.
145
Figure 6-8: Tetrahedral mesh of the structure
6.3.3 Boundary Conditions
6.3.3.1 Battery Temperature with time steps
There were 4 time steps used to represent the change of temperature of the
pack. The temperature profile followed the operating temperature of the battery pack
while charging and discharging. Three different temperature profiles were assigned
to three battery packs to create the operating environment of the battery. The range of
temperature change of the pack was considered as 0-45º C within 20 sec as shown in
Figure 6-9.
146
Figure 6-9: Temperature of the battery pack with time
6.4 Results
In the model analysis settings, the time steps and the total duration of the
analysis were applied following the time steps showed in the temperature profile of
the battery packs. The material properties were applied to the respective components
of the model. Here, bolted and welded parts of the structure were defined at this stage
as fixed supports. The thermal condition was inserted to apply the battery pack
temperature profile. Then the nodal forces obtained from the crash analysis were
inserted into the analysis system. The direction of the force was from the front of the
vehicle as demonstrated in the crash simulation. The nodes were defined considering
the coordinates of the vehicle.
6.4.1 Total deformation
Total deformation of this structure was caused by the temperature changes of
the battery pack. Total deformation of the structure defines the strain developed due
0
5
10
15
20
25
30
35
40
45
50
0 5 10 15 20 25
Tem
pera
ture
[°C
]
Time (s)
Temperature [˚C] pack 1
Temperature [˚C] pack 2
Temperature [˚C] pack 3
147
to the thermal conditions in this case. Strain was the expression of deformation in
terms of relative displacement of particles in the body that excluded rigid-body
motions. In the continuous structure, deformation field was resulted from
a stress field induced by changes in the temperature field inside the body. Figure 6-10
showed the total deformation experienced in design iteration 2.
Figure 6-10: Total deformation in design iteration 2
6.4.2 Equivalent stress
Equivalent stress (Von Mises) criterion was based on the determination of
distortion energy in given material. According to this stress criterion, a given
structural material was safe as long as the maximum value of the distortion energy
per unit volume in that material remains smaller than the distortion energy per unit
volume required to cause yield in a tensile test specified of the same material which
is young’s modulus of the material (Kazimi, 2001). Von-Mises stress is defined as
the equation 6.7 below:
148
3 (6.7)
where, = Von-Mises Stress = Tensile yield stress of the structural material.
Figure 6-11 and Figure 6-12 showed the stress developed in design iteration 1
and 2 due to the force applied to the two models with different pipe dimensions.
Figure 6-11: Stress (Pa) developed in design iteration 1
Figure 6-12: Stress (Pa) developed in design iteration 2
Maximum stress generated at the joint of the coolant pipe to the packaging of the battery pack in both design iterations.
149
6.5 Discussion In figure, the total deformation found for design iteration 2 was 0.2 mm
maximum which was not very significant. This referred to the compatibility of the
design under the effect of the force generated during the frontal impact in accordance
with the thermal condition of the battery pack. The design model was also suitable
for this layout of the vehicle while considering the total deformation occurred in this
condition.
Figure 6-11 demonstrated the equivalent stress developed due to the impact
force and temparature changes of the pack for the design iteration 1 and 2. Most of
the surface area experienced 356.59 pa and 400.34 pa stress accordingly in case of
design iteration 1 and 2 but some coordinates were facing significant amount of
stress in this design. Some areas as shown in figure faced a large amount of stress in
this analysis.
In case of the equivalent Von-Mises stress analysis, the amount of stress
developed in iteration 1 was more than that of iteration 2. The maximum stress
developed in both case was found at the outer surface of the coolant pipe. The depth
of the channel at the main body of the battery was 10 mm and the dimension of the
square sections cooling pipe were 20 and 15 mm accordingly for iteration 1 and 2.
The iteration 1 experienced more stress due to the less support of the main body of
the battery than the iteration 2.
6.6 Findings A comparison model was established for design iteration 1 and 2 as shown in
Table 6-6. Sectional properties of the selected pipe as the geometry model, weight of
the battery packaging and cooling arrangement, volume of the coolant fluid flow
through the pipe, total elastic deformation found for the vehicle crash load and
equivalent stress of the design model considering the crash of the vehicle were
compared here. The comparison of two design iterations demonstrated the selection
process of the pipe dimension for the battery cooling system.
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Table 6-6: Comparison between two design iterations
Criteria Design Iteration 1 Design Iteration 2
Pipe Section 20x20x1.6 mm 15x15x1.8 mm
Weight 4539.13 g 3829.25 g
Volume 578233.29 mm3 409182.31 mm3
Total Deformation 0.146 mm 0.2 mm
Equivalent Stress Min – 400.34 pa Min – 356.59 pa
Max – 8.12e9 pa Max – 7.82e9 pa
The comparison model revealed that the design iteration 2 was a better choice
in terms of weight and space required to install. But the volume of design iteration 1
was more suitable for the coolant flow because it allowed more mass volume of fluid
flow through the pipe. The larger volume of coolant flow would enhance the
efficiency of the cooling system. Moreover, the surface area of the design iteration 1
was bigger than the iteration 2 which referred to a wider contact area for heat transfer
from the cooling liquid to the battery at the fluid solid interface. The volumetric flow
rate was considered as a product of flow velocity and the cross sectional area. So the
iteration 1 referred to a bigger volumetric flow rate for the coolant due to the bigger
cross sectional area of the pipe.
Table 6-6 demonstrated that the design iteration 1 experienced less
deformation in the structure than the iteration 2. In the CAD model it was noticeable
that the design iteration 1 had an interference fit in contacts between the outer
surface of the cooling pipe and the channel surface surrounding the battery. In total
deformation analysis of iteration 2 it was found that the outer surface of the cooling
pipe faced maximum deformation due to the gap.
By taking the consideration of the rate of efficiency of the cooling system
and the structural safety of the model, the design iteration 1 was chosen for the
computational fluid flow analysis to obtain the workability of the cooling system.
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CHAPTER 7
THERMAL ANALYSIS OF BATTERY
COOLING SYSTEM
Electrification of vehicle was explained as the most viable way to achieve
clean and environmentally friendly transportation according to the literature review.
In the near future, EVs including hybrid electric vehicles (HEVs), plug-in hybrid
electric vehicles (PHEVs), and full battery electric vehicles (BEVs) were expected to
lead the emission free vehicle market. In this demanding automobile industry,
retrofitting of EVs would be considered as a rapid solution in meeting the target. In
case of all of these green solutions, battery was the most important factor. The
assembly and packaging of the battery was the most concerning factor for retrofitting
of EVs. Energy storing capacity of the battery was considered as the basic regulating
aspect of the range of EV and battery performance depends on the operating
temperature of the battery while charging and discharging. The performance of a
battery changes with its operating conditions (temperature, charging or discharging
current, state of charge (SOC), etc.) and its service time vary as discussed in section
2.4.1. In order to increase the power density of battery cells, it is required to
investigate battery packs for various characteristics of battery management system
(BMS) as example the temperature of the battery.
This chapter focuses on the thermal analysis of the battery cooling system
which was demonstrated in section 6.1.5. The literature review focused on the air-
cooled and liquid cooled system as discussed in section 2.5.1. The liquid coolant was
chosen to be the medium of cooling in this research due to the compactness and
efficiency of the system. The radiator of the existing vehicle was planned to be used
for the cooling of the battery pack. The proposed cooling circuit of the battery pack
consisted of the battery outlet (hot liquid) connected to the radiator inlet and after
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passing through the moderate air-cooled radiator, the liquid (air-cooled) was returned
to the battery pack inlet. To obtain more efficiency from the cooling system, the
existing air-conditioning system of the vehicle was proposed to be used. A by-pass
circuit was designed for the liquid coolant to flow from the battery outlet to the
battery inlet through the AC heat exchanger. The proposed cooling circuit of the
battery pack was demonstrated in Figure 7-1.
Figure 7-1: Cooling Circuit in the front bay
In the AC heat exchanger the cooling temperature needed to be monitored
and regulated so that the temperature of the liquid coolant would drop below the
standard range of suitable temperature required for the proper operating condition of
the battery. A temperature sensor was planned to be installed at the battery inlet. To
regulate the coolant temperature, a modification to the main cooling circuit was
proposed to apply where the maximum amount of coolant would be travelled through
the moderate heat exchanger. A by-pass channel would be fitted through the AC heat
exchanger and the flow through it would be controlled depending on the required
temperature of the coolant. The impact of the liquid cooling system on the battery
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pack temperature of a retrofitted vehicle was investigated. This study included a
novel design of cooling arrangement and analysed the design model to obtain the
results data regarding the thermal behaviour of the battery pack. By using these data
BMS would more efficiently prevent the over or under temperature of the pack and it
might actively ensure that all the cells were kept at the same SOC, through
balancing.
The liquid cooling system of the battery pack was analysed using ANSYS.
CAD model is imported to ANSYS Geometry module. Figure 7-2 shows the flow
chart of the simulation process.
Figure 7-2: Simulation Process used in FSI analysis
The basic system of the fluid-solid interface analysis was the impact of the
steady state flow of the coolant of given temperature and velocity on the transient
state temperature of the battery pack. To create the fluid solid interface two modules
of ANSYS analysis system were coupled together. Those are Fluid Flow (CFX) and
Transient Thermal. For this, steady state fluid flow was analysed in ANSYS CFX
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and the body temperature of the fluid was imported in the transient thermal module
to obtain the temperature of the battery pack.
7.1 Battery Pack Configuration To meet the required power of the vehicle, the equivalent battery
configuration and number of pack was calculated. The rated ampere hour (Ah) was
considered as the nominal capacity of a fully charged new battery under the
conditions predefined by the battery manufacturers. The nominal condition defined
for the selected batteries was 20ºC ambient temperature and 1/20 C discharging rate.
The rated capacity (wh) was calculated from the relationship as:
Rated wh Capacity = Rated Ah Capacity × Rated Battery Voltage
Specific energy of the battery was considered as the key parameter for
determining the total battery weight for a given mileage of EV. The specific energy
and the specific power of the battery were calculated from the relationships below:
Specific Energy = Rated Wh Capacity/ Battery Mass in kg
Specific power = Rated peak power/Battery Mass in kg
Power density of the pack (the peak power per unit volume of the battery,
W/I) was 0.46 kw/kg and weight of each pack was 65 kg, which determined 5 battery
packs for the selected vehicle parameter (Toyota CAMRY). Battery packaging in
mid and front portion of the vehicle was considered here according to the proposed
architectural layout of the retrofitted vehicle. 25 battery cells were planned to be
assembled in total 5 battery packs from which 3 packs were to be packaged in the
front bay of the vehicle and 2 packs in the mid area under the passenger seat.
Table 7-1: Battery Configuration for EV retrofitting
Lithium Ion Phosphate Battery
Rated Voltage [V] 3.2
Rated Capacity [Ah] 100
Power Density [kw/kg] ≥ 0.46
Cycle Life [1C Amplification] ≥ 2500 times
Operate Temperature
Charge 0~40˚C
Discharge -20~50˚C
Storage -20~40˚C
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7.2 Mathematical Model The coolant fluid flow was in a steady state. The initial pressure and
temperature of the fluid was given. The data from the flow stream was then inserted
into the solid battery structure in transient thermal module where the coupling of the
fluid and solid structure occurred. The basic approach consisted of using the standard
viscous flow equation for constant thermal conductivity and heat capacity of the
fluid. The continuity equation of the fluid flow (White, 1991, H.Versteeg, 2007)
from the law of mass conservation was:
0 (7.1)
where, vx, vy and vz = components of the velocity vector ρ = Fluid density
In case of a Newtonian fluid, the momentum equation stated the relationship
of the stress tensor, orthogonal velocities, dynamic viscosity as a fluid property,
second coefficient of viscosity and the divergence of the velocity (Amsden., 1971).
As the coolant was a constant density fluid, the product of second coefficient of
viscosity and the divergence of the velocity became zero. The momentum equation
for the turbulent fluid flow transformed to the Reynold’s averaged Navier-Stokes
equation (White, 1991, Allmaras., February 1992) as:
(7.2)
(7.3)
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(7.4)
where, gx, gy, gz = components of acceleration due to gravity μe = Effective viscosity Rx, Ry, Rz = Distributed resistances Tx, Ty, Tz = viscous loss terms P = pressure R = gas constant T = temperature
In terms of the total (or stagnation) temperature, the energy equation
considered was:
Φ (7.5)
where, Cp = specific heat To = total (or stagnation) temperature K = thermal conductivity Wv = viscous work Qv = volumetric heat source Φ = viscous heat generation term Ek = kinetic energy
Standard k-epsilon turbulent flow was used in this analysis. The turbulent
kinetic energy equation (Spalding., 1974) was:
Φ ρϵ (7.6)
The governing equation for the dissipation rate equation was:
(7.7)
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Table 7-2: Standard Model Coefficients
Model Coefficients Default Value
C1, C1ε 1.44
C2 1.92
Cμ 0.09
σk 1.0
σε 1.3
σt 0.85
C3 1.0
C4 0
β 0
7.2.1 Fluid Structure Interaction
The interaction of the fluid and the solid structure at a mesh interface was
applied to the wall of the coolant pipe where the temperature of the fluid was acting
as an input load and the impact of that temperature flow on the solid structure. The
finite element matrix used here to analyse the interface (P. Chen, 1998, (6)) was as
given below:
(7.8)
= (7.9)
Coupling matrix [R] referred to the effective surface area associated with
each FSI node. The load quantities of the fluid and solid structure generated at the
interface surface area were the functions of the nodal degrees of freedom. By adding
these load quantities with the above equations the finite element matrix equation was
formed as given below:
0 0 (7.10)
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7.3 Computational Analysis 7.3.1 Material Properties
Coolant properties used in this study were set by considering constant values
independent of temperature change of the fluid as shown in Table 7-3.
Table 7-3: Material Properties of the coolant
Phase Liquid
Thermal Conductivity 0.405 W/(m.K)
Heat Capacity 3300 J/(kg.K)
Density 1078 kg/m3
Heat Ratio 1
Viscosity 0.00429 pa.s
The material used for the solid structure of the battery was Aluminium Alloy.
The density of the aluminium alloy was considered constant within the temperature
range considered here. The thermal properties of this material were as shown in
Table 7-4.
Table 7-4: Thermal properties of aluminum alloy
Specific heat capacity 0.896 J/g-ºC
Melting point 582 – 652 ºC
Electrical Resistivity 3.99e-006 ohm-cm
The given thermal conductivity of the material was as demonstrated in the
Figure 7-3.
Figure 7-3: Thermal Conductivity data of Aluminum Alloy
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7.3.2 Geometry
Geometry of the battery cooling system was created based on the structural
safety analysis. The selected pipe dimension of the design was 20x20x1.6 mm
hollow square section. Geometry of the battery pack cooling system was modelled in
Solidworks and imported in ANSYS CFX geometry modeller. As the battery units
were divided into 2 sets, only one set with 3 battery units was designed and analysed
in this study. Piping arrangement for the coolant was modelled surrounding the
battery units to get the maximum output. The coolant pipe consisted of single
entrance and exit to simplify the model and the pressure distribution. This single
entrance and exit set up also simplified the arrangement of the coolant flow
accessories such as the coolant pump and other related components.
Figure 7-4: CAD model of battery cooling system
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At the conceptual design stage, different positions for the cooling pipes were
taken under consideration. The most heat generating point of the battery pack was
near the TAB on the top where all the wires were connected to the BMS. The most
effective position of the cooling pipe arrangement would be near the TAB. But there
were some safety concerns to install the liquid cooling pipes close to the TAB as
there were risks of leakage. Literature review demonstrated the arrangement of the
cooling pipe at the bottom of the pack. However, in that case the maximum heat
generating area near the TAB was kept far from the cooling arrangement. Hence,
cooling arrangement was designed covering the circumference of each battery pack
so that the most effective cooling rate can be achieved.
In the CFD analysis, only the cooling pipe was considered and the solid
model of the battery was supressed to simplify the analysis. After importing the CAD
model into ANSYS design modeller, regions have been divided by selecting the
surfaces of the CAD model. Then the regions were grouped into solid and fluid part.
Figure 7-5: Flow path of coolant through the pipe
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7.3.3 Meshing
Mapped face meshing was applied to mesh the coolant fluid for the flow
analysis and solid battery pack with the coolant pipe for the transient thermal
analysis. In the turning region of the coolant, refinement has been applied to get the
better results with the fluid flow.
Figure 7-6: General Mesh of the Design Model
Figure 7-7: Mapped Face meshing with refinement for the coolant pipe
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The mesh was then checked for errors and the mesh independence test was
accomplished. For the convergence criteria of the analysis the residual type was
RMS and the target was 1.E-4 to 1.E-5.
Figure 7-8 and Figure 7-9 demonstrated the mesh independence test results in
terms of residual error and domain imbalance convergence in case of meshing with
refinement.
Figure 7-8: RMS target value with time sec.
At first, the mesh was done ensuring the convergence of the residual error to
1.E-4. After the first design iteration, the global refinement to the initial mesh size
was applied. Global refinement was chosen to have the finer cells throughout the
domain. The refinement was around 1.4 times of the initial mesh size. With this
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refinement, the convergence of the residual error dropped below 1.E-4 and the
domain presented the imbalances below 1%.
Figure 7-9: Domain imbalance with time sec. for refined mesh
7.3.4 Boundary Conditions
7.3.4.1 Fluid temperature
Heat transfer system of the fluid was selected as isothermal for this analysis.
The temperature of the fluid was 15º C.
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7.3.4.2 Flow Domain
The steady state fluid flow was considered so that fluid temperature can be
the only regulatory factor in determining the effect of cooling system of the EV
battery packs in a specific layout strategy. K-epsilon turbulent model was selected
for the analysis. The morphology of the fluid was continuous. The reference pressure
was given as 1 atm. The non-buoyant stationary domain motion was selected for the
fluid flow. Mesh deformation was specified by the regions declared in the geometry.
The initial velocity of the fluid was given as 1.5 m/s. The physics model generated
at the CFD analysis was as shown in Table 7-5.
Table 7-5: Background physics data of the analysis model
Type Fluid
Morphology Continuous Fluid
Buoyancy Model Non Buoyant
Domain Motion Stationary
Mesh Deformation Regions of Motion Specified
Mesh Motion Displacement Diffusion
Mesh Stiffness 1.0000e+00 [m^2 s^-1]
Reference Pressure 1.0000e+00 [atm]
Heat Transfer Isothermal
Fluid Temperature 1.5000e+01 [C]
Turbulence Model k epsilon
Turbulent Wall Functions Scalable
The inlet, outlet and wall of the fluid region were defined in the CFX-Pre
module. In the default domain inlet and outlet show the flow direction of the fluid as
given below:
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Figure 7-10: Inlet, outlet and wall in CFX-Pre module
The boundary conditions for the inlet and outlet regions were defined as
below:
Table 7-6: Inlet boundary conditions
Location INLET
Flow Direction Normal to Boundary Condition
Flow Regime Subsonic
Mass And Momentum Mass Flow Rate
Mass Flow Rate 3.9620e-02 [kg s^-1]
Turbulence Medium Intensity and Eddy Viscosity Ratio
INLET
OUTLET
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Table 7-7: Outlet boundary conditions
Location OUTLET
Flow Regime Subsonic
Mass And Momentum Average Static Pressure
Pressure Profile Blend 5.0000e-02
Relative Pressure 0.0000e+00 [Pa]
Pressure Averaging Average Over Whole Outlet
For the wall, the mass and momentum was based on no-slip and the wall
roughness was selected to be smooth.
7.3.4.3 CFX Solver Control
High resolution first order turbulence numeric was selected for the solver
control of the CFX-Pre. In the convergence control 1-50 iterations were considered.
7.3.4.4 Battery Temperature with Time steps
Heat generated in each battery pack as a function of time was the boundary
condition of the analysis. Figure 6-9 demonstrated the temperature of each battery
pack with time. Here, the worst case scenario was considered that the temperature of
the pack was raised at a very high rate. Within only 20 sec the battery pack reached
at its maximum temperature point.
7.3.5 Transient Thermal Analysis Module
Transient thermal analysis module determined temperatures and other
thermal quantities that varied over time. In this case, it was a linear transient thermal
analysis because the material properties such as thermal conductivity, specific heat or
density and the convection or radiation coefficients were considered to be
temperature independent. The geometry was shared in both CFX and transient
thermal module. The solution segment of the CFX module was imported into the
transient thermal set up. The fluid body temperature data was shared as the imported
load in the transient thermal analysis system. Battery temperature was given
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according to the time steps as given in the table above. The analysis system applied
in this case was as shown in Figure 7-11.
Figure 7-11: Detail flowchart of FSI analysis
To get the temperature of the battery pack temperature probes were applied at
some points of the battery packs. Temperature probes were used to determine the
exact temperature of the selected coordinate within the domain. Here, probes were
defined by picking the points within the domain. Most of the points were selected
close to the Terminal point, TAB of the battery as temperature raises the most near
the TAB. Probe 1 was placed close to the TAB and the coolant flow pipe. Probe 2
was placed close to the TAB, but not near the coolant pipe. Probe 3 was placed at the
mid area of the battery pack and close to the coolant pipe. Probe 4 was placed at the
mid area, but not near the coolant pipe. The temperature probes were placed covering
most of the crucial temperature peak and off-peak points at the battery pack.
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Figure 7-12: Temperature probes placed to get the temperature of different locations of the battery
The default initial condition of a transient thermal analysis was a uniform
temperature of 22ºC. In this case, the initial temperature of the domain was modified
according to the temperature generated at the battery pack. In the first iteration of the
analysis this temperature was used as the starting temperature of the domain. Here,
temperature probes were placed to specify the initial temperature of those
coordinates so that the output temperature probe could be placed at the same
coordinate to obtain the temperature tracks. From the steady state flow analysis, the
imported temperature load was imported into the transient thermal analysis.
7.4 Results 7.4.1 CFX Analysis
Fluid flow analysis demonstrated the behaviour of the fluid thorugh the pipe
according to the material properties of the fluid. Here, velocity and pressure of the
fluid were measured through the pipe.
Probe 2
Probe 1
Probe 3
Probe 4
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Figure 7-13: Velocity profile of the coolant fluid flow
Figure 7-14: Pressure profile of coolant fluid (inlet, outlet and wall)
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Another important factor analysed in this work was fluid temperature as an
output data. Figure 7-15 shows the change of temperature in coolant fluid. The pipe
wall is the main interface of this heat transfer. Both heat sources are sharing the pipe
wall to exert the heat. In CFX post processing section, the temperature of the coolant
pipe wall was measured.
Figure 7-15: Temperature profile of pipe acting as heating/cooling interface
7.4.2 Transient Thermal Analysis
In transient thermal analysis, the total analysis duration was 50 sec. The fluid
region of the model was supressed to avoid the complicacy during the analysis run
time. The temperature of the battery pack was measured in the solution step of the
analysis. The initial ambient temperature was set at 22º C during the analysis. Here,
the temperature generation with time was applied to the whole solid body. Figure
7-16 shows the temperature gradient of the solid body accordingly at 11.11 sec and
33.33 sec. At 33.33 sec the temperature was decreased to the minimum level under
the effect of the coolant fluid flow.
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Figure 7-16: Battery temperature magnitude ramp accordingly at 11.11 and 33.33 sec.
As heat was not generated and exerted uniformly on the whole body of the
battery pack, in this analysis temperature probes were placed to get the thermal
behaviour of the solid body at different coordinates. These coordinates were chosen
by considering the crucial area of heat generation. The location of placing the
temperature probes were based on the distance from the coolant pipe and the
maximum heat generation region, the TAB of the battery. The location of these
probes was shown in Figure 7-12. At each probe, the temperature was found with the
time steps in 50 sec duration of the analysis. The temperature data for each probe
with time steps were collected from the results and the graph was plotted as shown in
Figure 7-17.
45.245 37.875 30.505 23.134 15.764 8.394 1.0239 ‐6.3463 ‐13.717 ‐21.087
Temperature Unit: ºC
11.11 Sec. 33.33 Sec.
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Figure 7-17: Temperature data chart at four temperature probes
7.5 Discussion 7.5.1 Fluid Flow Analysis
In fluid flow analysis, velocity of the fluid was measured as shown in Figure
7-13. The figure referred that at every turning point of the path the velocity increased
due to the sharp edges. According to the velocity profile plotted here, at the most part
of the path the velocity of the fluid was very close to the initial velocity (1.5 m/s). At
the outlet it was also maintaining the same velocity with some distortions due to the
rapid turns and frequent sharp edges. The maximum velocity developed at the turns
was 2.5 – 3.35 m/s.
Another observation from the velocity profile was the velocity streamline
field increased in magnitude far from the wall. At the points close to the wall the
velocity magnitudes were started to decrease. This was happened due to the no-slip
condition applied to the wall in the boundary condition of the analysis.
0
5
10
15
20
25
30
35
40
45
50
0 10 20 30 40 50 60
Tem
pera
ture
[ºC
]
Time Steps (Sec)
Probe 1
Probe 2
Probe 3
Probe 4
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In the turbulent flow pattern, the intensity of the turbulence was noticeable.
The average turbulence intensity was found 1.2 - 1.5%. For the laminar flow, the
expected turbulence intensity would be less than 1%. However the value was still
very small and the flow could be considered close to laminar. The turbulence seemed
to be highest while approaching the sharp edges. This might be explained by the
geometry constraints considered in the CAD model of the cooling system.
Pressure contour of the coolant fluid flow in Figure 7-14 displayed the
maximum pressure generated at the inlet and the minimum pressure generated at the
outlet. The inlet pressure magnitude was 31 pa and the outlet pressure was less than 5
pa. The minimum pressure was observed at the outlet due to the given average
relative pressure at exit point as the boundary condition of the analysis. As the flow
was considered to be laminar, the turbulence k-epsilon model did not have significant
impact on the pressure profile of the fluid flow.
Figure 7-15 demonstrated the temperature profile of coolant pipe. It displayed
the interface of the heat transfer. The inner surface of the coolant pipe was
considered here. The mechanical input from the transient thermal module was
imported to the CFX module to analyse this phenomenon. In the mechanical input,
the battery temperature profile was applied to the coolant fluid flow which exerted
the heat to the pipe. The heat transferred to the inner surface of the pipe was shown.
The temperature of the coolant pipe increased maximum to 313 K [40˚C] in some
locations. But the major portion of the fluid exhibited the temperature range of 289-
297 K [15-24˚C] The initial temperature of the fluid was given 15˚C. After
experiencing the heat transfer from the mechanical input file, the temperature of the
inner surface of the coolant pipe rised.
7.5.2 Transient Thermal Analysis
The temperature gradient of the solid battery pack was facing the temperature
between 15 to 23º C at 11.11 sec as shown in Figure 7-16. 15º C was mostly noticeable
at the channel of the coolant pipe due to the temperature of the fluid.
At 33.33 sec the battery pack reached to its lowest temperature under the
effect of the coolant flow. Figure 7-16 showed that at this point of time, the
temperature of the solid body varied from 15 to 28º C. The magnitude of the
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temperature experienced in the most of the heated surface was 25 to 28º C. From the
analysis results, it was observed that area close to the fluid flow region faced the
temperature between 15 to 24º C due to the fluid temperature.
Temperature probes were placed to get the thermal behaviour at certain
coordinates of the solid body. Probes were declared at the initial condition of the
analysis to put the battery temperature as input value. At the solution step of the
analysis, the effect of coolant fluid flow was observed at those temperature probes.
Probe 2 was placed very close to the terminal (TAB) of the battery as shown in Figure
7-12 and the maximum magnitude of temperature applied on that probe was 45º C. In
the chart shown in Figure 7-17 the lowest temperature observed at probe 2 was 28º
C. The rate of cooling at probe 2 was also very low as observed in the chart. The
location of probe 2 far from the coolant pipe may cause this low decrease rate of the
temperature. Probe 1 was also placed near the TAB of the battery and same
temperature 45º C was applied initially as probe 2. But the location of probe 1 was
close to the coolant pipe. For this reason, the magnitude of the lowest temperature at
probe 1 was below 25º C and also the decreasing rate of temperature was also higher
than probe 2. Probe 4 was placed close to the mid area of the battery and the initial
temperature was given 38º C. The magnitude of the temperature dropped to 23º C.
The location of probe 4 was far from the coolant fluid region. Probe 3 was placed at
the mid area of the battery and also close to the coolant pipe. The initial temperature
at this probe was 40º C. the temperature decreased under the effect of the coolant
fluid flow to 20º C. At this probe, the decreasing rate of the temperature was high.
7.6 Findings The main concept of this cooling system design was the idea of arranging the
coolant pipe around the battery pack. The analysis results showed the coolant fluid
flow worked properly to decrease the temperature of the pack. The temperature of
the battery pack was given as averagely 40-45º C and under the effect of the coolant
fluid flow, the temperature of the battery decreased averagely up to 25º C. The
surface temperature of the coolant pipe was also decreased at 25-28º C as shown in
Figure 7-15.
175
If these design and analysis system can be tested in a real-time battery model
including the physical and chemical properties of the Li-ion battery and the heat
generation data due to charging and discharging, it can be helpful to increase the
robustness of the BMS.
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CHAPTER 8
CONCLUSIONS AND FUTURE
RECOMMENDATIONS
8.1 Conclusions Automotive industry inclined towards emission free transportation and thus
the development of EV to serve the global environmental requirements. The purpose
of this research was to find out a suitable retrofitting system with respect to the
dynamic stability of the vehicle in different manoeuvring conditions such as sudden
change in steering and cornering, the structural safety of the battery packaging
arrangement and the efficiency of the cooling system of the battery pack. As referred
by the previous literature, the interest in enhancement of the commercialization and
adaptation of EV in the automobile market has grown along with the research for the
development of it and reduction of the limitations involved in it. This study was
mainly focused on the costs and rapid commercialization issues of EV. The
retrofitting of EV and the dynamic behaviour, structural and thermal analysis of the
battery packaging and cooling system to support the proposed architectural layout for
retrofitting were studied in this research.
8.1.1 Retrofitted Architectural Layout
EV propulsion system was chosen to obtain the best available space on the
vehicle after removing the engine, alternator, gear box, fuel tank etc. In wheel
propulsion was evaluated as the best choice in terms of power generation and space
allocation, though this propulsion system had a risk of increasing the un-sprung
weight of the vehicle. The un-sprung weight has a great impact on the rotational
inertia of the wheels. The braking of the wheel is subjected to be affected due to the
delay of the stopping time after pressing the brakes caused by the big amount of
177
rotational inertia developed in the wheels. The contact patch area of the tyre will be
increased with the increment of the un-sprung weight which may affect the amount
of traction produced by the tyre at a given normal load. Un-sprung weight has an
impact on the vehicle handling as the increment of un-sprung weight may slower the
response of the vehicle to the steering input. In this circumstance, the un-sprung
weight became one of the selection constraints of the electric motor. The weight of
the electric motor was required to be lower to keep the un-sprung weight as low as
possible. The in-wheel technology delimited another selection measure that the size
of the motor was required to be compact to fit inside the wheel. Therefore, the power
to weight ratio regulated the selection of electric motor. The permanent magnet
motor was the optimum choice considering these criteria, though the costs involved
with PM motor was high due to the use of rare-earth material. According to the
efficiency and power to weight ratio provided by the electric motors, PM was the
better choice.
During the selection of vehicle parameter, the criteria were led by the in-
wheel propulsion requirement. The wheel size of the vehicle was one of the key
criteria for the mule vehicle selection. The power required to drive the vehicle was
important to check for matching with the capability of the motor as the motor power
is proportional to the weight and therefore the size of the motor. The space available
in the vehicle was considered so that the vehicle would be capable to accommodate
as many battery cells as possible. Toyota CAMRY was chosen as the mule vehicle
parameter for retrofitting. To fit the motor inside the wheel the existing wheel size of
the selected vehicle was not adequate. The regulations allowed 2” of increment to the
existing wheel diameter. In this situation, costs involved in retrofitting would rise for
two new drive wheels (front) to include the in-wheel propulsion.
In determining the weight components to be removed from the vehicle, the
requirement of battery packaging arrangement and cooling system design were
considered. The radiator and air-conditioning system of Toyota CAMRY were
decided to be kept to facilitate the cooling system of the battery pack. The weight
components to be added during retrofitting were determined as the most required and
significant weighted ones. The super-controller, battery monitoring system was not
considered in this study to simplify the analysis. Moreover, these items did not have
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significant weight which could have a great influence on the load distribution and
therefore the dynamic behaviour of the vehicle. However, the total weight of the
battery was considered as 330 kg for the CG calculation. The actual weight of the
battery was 325 kg according to the battery configuration given in Table 6-1. The extra
5 kg was considered as the weight of the cooling system for the battery.
The existing brakes and suspension were planned to be kept to avoid the cost
escalation, though the both systems were analysed based on the retrofitting concerns.
To check the reliability of the existing hydraulic braking system of Toyota CAMRY,
the disc brake was analysed under the impact of braking force generated for given
stopping time and distance. The braking force was calculated by considering the
retrofitted weight of the vehicle and the rise of temperature at the running disc was
given as input to obtain the thermal strain developed at the dynamic condition of the
brake. The rotational velocity of the disc under the effect of heat flux, radiation and
convection was also applied as input. The existing mechanical brake was found
capable of stopping the vehicle with the extra retrofitted weight. Sustainability of the
existing suspension system was checked by analysing the coil spring of Toyota
CAMRY under the effect of retrofitted weight. The geometry of the coil spring was
defined and modelled by measuring the dimension from the vehicle on site.
Theoretical displacement of the spring for the vehicle weight was calculated and
compared with the analysis result of total deformation. The suspension system was
found suitable for the retrofitted weight of the vehicle in terms of the performance
safety factor considering the spring constant. The spring constant applied in the
calculation was collected from the manual booklet of Toyota CAMRY Attara 2012
model provided by the vehicle manufacturer. For the reliability check of the
suspension system, more detail analysis could be performed which would be able to
take the sprung and un-sprung weight of the vehicle under consideration and
calculate the roll centre in the dynamic condition. The detail analysis of the
suspension system could determine the requirement of anti-roll bar during the
retrofitting of the vehicle.
Selection of suitable places in the vehicle to put the EV drive train
components was important. The potential places were analysed based on existing
facilities and advantages related to the locations. The front bay was the best place to
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package the battery for the weather protection included with it. The mid area had its
demerits as the retrofitting cost would rise to install an extra weather protecting
arrangement under the passenger seat. The rear boot area was subjected to the
compromise with the luggage space and spare wheel of the vehicle. However, three
architectural layouts were determined by considering these three places in the
vehicle. Load distribution and CG positions were calculated for the corresponding
layouts to simulate the dynamic characteristics of the retrofitted vehicle.
8.1.2 Vehicle Dynamic Analysis
The vehicle dynamic analysis was focused on the motion of the vehicle in
sudden change in manoeuvre and cornering situation. The forces acting on the
vehicle including rolling resistance, aerodynamic drag, tractive force generated from
the motor were calculated to determine the longitudinal force. The tractive force
generated by the electric motor was calculated from the motor torque data. The
aerodynamic drag force was calculated by considering an empirical formula for the
frontal area of vehicles with 800-2000 kg. The consideration of actual frontal area of
Toyota CAMRY could obtain the proper aerodynamic drag force in the driving
condition at a given velocity.
The polar moment and path radius calculated for three load distribution cases
referred to the mid area placement of the battery pack as the best solution for vehicle
stability, though the front loaded layout did not show significant difference. The
vehicle model was developed for both manoeuvring conditions under some
simplification assumptions. The chosen value of frictional coefficient was not for
standard road condition. Considering the standard road condition of frictional
coefficient 0.8-0.9 could obtain better dynamic results from the analysis. To check
the performance of the vehicle at an adverse road condition, the frictional coefficient
was chosen as 0.6. The steering angle considered was for the sudden change
manoeuvring condition was based on the FMVSS stability test data.
In the cornering dynamic analysis model, the spring and un-sprung roll was
simulated based on the spring data collected from the suspension details of Toyota
CAMRY. Hence, in the simulation tyre damping coefficient was not considered as
the actual value due to the un-availability of the tyre data. A standard tyre damping
180
coefficient for the corresponding wheel size (18”) was given as input in the
simulation. Moreover, the tyre size was subjected to change to fit the motor inside
the wheel. According to the given coil spring data, the cornering dynamic analysis
results referred to the sustainability of the suspension system of the mule vehicle for
the retrofitted weight. The analysis results for the vehicle trajectory and tyre grip, the
mid-loaded architectural layout was found as the best suitable for retrofitting.
The longitudinal velocity of the vehicle at sudden steering change
demonstrated the front loaded layout as the best choice. Comparing all the dynamic
results and considering the design constraints of retrofitting, the new architectural
layout with dividing the battery pack into two units and placing those units in two
different locations was proposed in this research. To validate the proposed layout,
experimental set up was prepared.
During the experiment, a demo vehicle was tested according to the load
distribution of the proposed architectural layout. The experiment data was collected
from the demo vehicle in the lab and given as input in the vehicle model simulation
to compare the computational and experimental vehicle dynamic characteristics. As
the demo vehicle was not in a symmetric load distribution in the lateral direction, the
results were found a little unstable at dynamic condition specifically for the
cornering dynamic analysis and percentage of error could be counted for this
distortion of loading symmetry of the vehicle. While measuring the contact patch of
the demo vehicle to calculate the slip ratio at complete sliding condition, the static
loaded condition was taken under consideration. The contact patch area would be
found different if it was measured at dynamic loaded condition and therefore the
dynamic results could have been more realistic for the demo vehicle. The actual
frictional coefficient could be different from the given one. The given magnitude of
µ was for coarse concrete, whereas the lab floor was more polished. The
experimental result for the turning radius of the curved path showed the similar
vehicle handling characteristics as found in the computational result of vehicle
trajectory. In the vehicle trajectory computed for the demo vehicle, it was noticeable
that the actual path followed by the vehicle was not entirely circular whereas the
intended theoretical path was like a complete circle. This was happened because of
the unbalanced condition of the lateral load on each tyre. The tyre model was
181
simulated for the demo vehicle from which the total slip was calculated and
compared with the slip at complete sliding of the tyre i.e. the maximum limit of slip.
The comparison found the total slip σ experienced by the tyres of the demo vehicle
was less than the maximum slip σm which referred to the dynamic stability of the
vehicle. In determining the slip ratio at front and rear tyres, only the acceleration of
the vehicle was considered. The braking of the vehicle could have demonstrated
significant changes in dynamic behaviour. However, during acceleration the
difference found between σ and σm was very large in magnitude. Considering this, σ
in braking condition was not calculated to avoid the complicacy in the tyre model.
The tyre grip developed for the demo vehicle also led to an acceptable level of
dynamic stability. According to the computational and experimental vehicle dynamic
analysis results, the proposed layout was found sustainable in both manoeuvring
conditions.
In the experimental set up, the demo vehicle was only turned left to obtain the
turning radius and the handling characteristics. As the demo vehicle was weighted
more at the left than the right side of the vehicle, the worse condition was subjected
to occur at the left turn due to the lateral load transfer from left (inside) to right tyres
(outside).
In case of sudden change in steering condition no experiment had been
accomplished due to the space facility inside the lab. Moreover, to check the sudden
change in steering the vehicle was required to be driven at least at 60 Km/h. But the
demo vehicle was not facilitated to increase the velocity up to 60 Km/h. The
experimental results for sudden change in manoeuvring condition could show a
better comparison in this study.
After validating the proposed layout, the load distribution was applied in case
of Toyota Camry. Then the simulation results were compared as demonstrated in
Table 5-7 with the front and mid loaded layout as these two layouts were found
dynamically more reliable than the rear load distribution. The comparison showed
the sustainability of the proposed layout in terms of trajectory followed by the
vehicle at a corner, the longitudinal and lateral velocity generated at each tyre.
182
8.1.3 Structural Safety Analysis of the Battery Cooling System
To validate the proposed layout in terms of battery packaging arrangement
and cooling system design, the structural safety analysis was provided in this study.
A novel design arrangement was proposed and demonstrated for the packaging of the
battery included with the cooling system. Two design iterations were analysed
differing based on the dimensions of the cooling pipe according to the Australian
Standard for square hollow sections of structural steel. The impact load condition for
the analysis was determined by the vehicle crash analysis. Vehicle crash was
simulated only for the model of vehicle outer-shell and chassis to simplify the
analysis using LS-DYNA integrated with ANSYS mechanical APDL. The nodal
forces developed during the crash was collected from the output file and entered into
the structural analysis. In the crash simulation, only three nodes were defined to
collect the force data to shorten the analysis time. Defining more nodes could obtain
an accurate average magnitude of the force and thus a smooth force curve for the
structural analysis. The temperature of the battery pack was also considered to obtain
the combined effect of the crash impact load and thermal condition of the battery.
Total deformation, equivalent stress and durability of the structure were shown as the
analysis results. The results were compared in case of two design iterations as shown
in Table 6-6. In determining the cooling pipe dimension, the mass flow rate through
the pipe was the crucial consideration. The structural analysis was accomplished for
the battery pack to be installed at the front bay. The design of the packaging
arrangement and the cooling system in the mid area under the passenger seat were
not considered in this study.
8.1.4 Thermal Analysis of the Battery Cooling System
For the cooling of the battery, a combination of active and passive cooling
system was modelled in this research. The cooling circuit diagram including the
ducting arrangement in the front bay was provided connecting with the radiator and
air-conditioning system of the mule vehicle. The cooling circuit of the battery pack
in the front bay was proposed using the radiator for passive cooling and the AC heat
exchanger for the active cooling of the coolant fluid. The coolant temperature was
considered to be 15º C under the active involvement of AC heat exchanger. The
183
proposed cooling diagram included a by-pass circuit (shown in Figure 7-1) for using
the AC system so that the energy loss could be avoided. When the required coolant
temperature can be maintained by the passive air-cooled system through the radiator,
the use of AC will cause the energy loss because the usage of AC will decrease the
energy stored in the battery pack.
The FSI analysis results were provided to demonstrate the cooling trend of
the battery temperature under the effect of the coolant flow temperature. The input of
battery temperature was given as varied with time. The thermal conductivity of the
coolant fluid was given 0.405 w/(m.k.) which was not very effective. The coolant
fluid with high thermal conductivity could have shown better results than the current
consideration. The fluid flow analysis imposed isothermal heat transfer and non-
buoyant k-epsilon turbulence model at 15º C. When the body flow temperature was
imported into thermal analysis of the battery, the pack temperature was decreased
and came down in the limit range. The maximum temperature of the battery pack
was given was 45º C which was based on the data collected from the battery
configuration.
8.2 Key Findings of the Research Based on the analytical and experimental results reported in this thesis the
following acquaintances can be claimed for the objective towards the performance
development of EVs:
The research focuses specifically on the retrofitting of the existing vehicle
with its aspects of propulsion system, motor drives, vehicle parameter etc. In-
wheel propulsion system (front wheel drive) with permanent magnet electric
motor, vehicle parameter of Toyota Camry Attara S 2012 model was selected
based on vehicle weight, space available and power required to drive the
vehicle as demonstrated in section 3.1, 3.2 and 3.3.
The research analyses the brake and suspension system of the selected vehicle
by considering the extra weight added for retrofitting and finds that the
existing brake and suspension systems are compatible with the retrofitted
184
vehicle weight and load distribution. The FE analysis results are given in
section 3.4 and 3.5.
The research considers the sudden steering change and cornering manoeuvre
to develop the dynamic behaviour of the vehicle. The simulation was
described in section 4.3.2 and 4.3.3.
Three basic three architectural layouts (front, mid and rear loaded) are studied
in this research and combination of those reveals a better solution for
retrofitting. The research re-contextualizes the applicability of the existing
theory of vehicle dynamic analysis to the retrofitting situation of the vehicle
as shown in section 4.4.
The research claims a novel architectural layout (section 4.6.1) for retrofitting
and provides experimental validation to the theoretical proposal (section 5.2).
The proposed layout applied in the selected vehicle parameter Toyota Camry
was compared with the results for basic layouts based on dynamic behaviour.
The proposed layout was found more sustainable than the other layout as
compare in section 5.4.
The study conveys a total cooling circuit using the existing radiator and air-
conditioning system of the vehicle to obtain the required temperature (15º C)
of the supplied liquid coolant as shown in Figure 7-1.
The study provides a novel design for the battery packaging arrangement and
cooling system for the battery pack as shown in section 6.1 and 6.1.5.
The pipes of the battery cooling system are located around the pack close to
the terminal of the battery where the maximum temperature arises as
described in section 7.3.2.
Two design iterations based on the standard dimensions of the cooling pipes
are verified for the structural safety analysis of the packaging arrangement
including the battery cooling system as demonstrated in section 7.6.
The research confirms the workability of the cooling system by decreasing
the battery temperature significantly from 45º C to 28º C as shown in section
7.4.2.
185
8.3 Future Recommendations Several aspects of the dynamic stability characteristics, structural safety and
thermal analysis involved in retrofitting purpose were studied in this research.
However, there are certain topics in which further investigation seems necessary and
are recommended in this section.
The proposed layout was not validated experimentally for Toyota Camry due
to the limited resources. The experimental validation using Toyota Camry would
establish this proposal and the design depending on the vehicle parameter and load
distribution stronger.
In this research, the assumptions considered in the dynamic analysis were to
simplify the vehicle model using MATLAB SIMULINK. The consideration of no
moving load may not precisely reflect the realistic dynamic results for the vehicle.
The road was considered as straight and flat with zero inclination which was not a
real-time scenario. Further study can be continued considering these assumptions to
create more effective and dynamic retrofitting solutions for EV development.
In the vehicle dynamic analysis, the tyre forces are calculated only during the
acceleration. The consideration of braking condition may establish more stable
feasibility of the system. The dynamic model can also be further developed by
considering different formula or method for the tyre model. The frictional coefficient
is considered as a constant value for the simulation in this research. The presence of
running surface irregularities may amplify the contact load on the tyres which can be
considered in further studies.
In this study, the battery pack was not modelled considering the configuration
and chemistry of the battery. Hence, the battery pack was considered as a solid
structure which exerted heat. The Li-ion phosphate battery pack could be modelled
by each cell and then connected in series to build the pack using appropriate software
as example Battery Design Studio (BDS). BDS can accommodate the power rating,
power to weight ratio, specific energy etc. data of the battery. In addition to the
temperature of the battery pack, temperature variation from module to module in a
pack could be analysed and obtained more accurate charge/discharge behaviour for
each module. The model of the battery pack could be analysed considering the
186
thermal condition under the coolant flow. In that case, the temperature generation of
the battery would be according to the actual discharging condition. Instead of
obtaining the thermal analysis results at the defined temperature probes, the whole
battery pack would demonstrate the thermal condition and thus the efficiency of the
cooling system.
In addition, the battery pack could be placed in the vehicle with the
packaging arrangement and cooling system in the crash analysis. In this study, the
magnitude of nodal force was collected from the crash analysis. If the analysis could
be accomplished as the crash worthiness test of the vehicle including the battery
pack, the results would be more holistic and actual, though it would require more
analysis time and computational resources.
The goal of this study was to portrait a suitable architectural layout for the
retrofitted electric vehicle which could be dynamically stable during manoeuvring
without modifying any specification of the existing vehicle body to avoid the cost
escalation. To support the proposed layout the battery packaging and the cooling
system were taken under consideration in terms of weight, reliability and
compatibility with the selected vehicle parameter, though the vehicle operation under
a wide range of climate conditions and providing ventilation for the emission of
potential hazardous gases from the battery were not analysed. In this study, the
experimental validation for the battery thermal management and structural safety
were not provided. The analysis model can be validated with experimental data of
different vehicle platforms. Thus, the battery thermal management and safety
analysis can be explored further to obtain a holistic system for retrofitting of electric
vehicle.
187
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APPENDIX A.1. MATLAB Programing for the Calculation of Longitudinal CG
function x =
calcCG(item1,item2,item3,item4,iniweight,m1,m2,m3,x1,x2,x3,distF,wheelbase)
itemTot=(item1+item2+item3+item4);
m4=iniweight-itemTot;
F=iniweight*distF; %weight on front axle F%,distF is the % of weight distribution
front to rear%
R=iniweight-F; %weight on rear axle R%
F1=F-itemTot; %weight on front axle after removing items%
R1=R; %for this instance no change in rear weight%
x4 = (wheelbase*R1)/(F1+R1);
calweight =F1+R1+m1+m2+m3;
x = ((m1*x1)+(m2*x2)+(m3*x3)+(m4*x4))/calweight; %x1 is forward side of front
axle%.
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A.2. MATLAB Programing for the Calculation of Vertical CG
function z =
calcCGz(item1,item2,item3,item4,iniweight,m1,m2,m3,z1,z2,z3,gc,vheight)
itemTot=(item1+item2+item3+item4);
m4=iniweight-itemTot;
z1a=z1+ gc; %Adding of ground clearance to calculate the CG from ground%
z2a=z2;
z3a=z3+ gc;
z4a= vheight*0.30; %Assuming after removal of items CG of the rest of the vehicle
is located at the 30 % of vehicle height%
M= m1+m2+m3+m4;
z= ((m1*z1a+m2*z2a+m3*z3a+m4*z4a)/M) + gc;
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A.3. Vehicle Dynamic Analysis using Simulink
Considering a vehicle moving on a flat road at a given velocity, the external
longitudinal forces, gravitational forces, aero-dynamic drag forces, rolling resistance
are calculated. Here, frontal area of the vehicle is considered for the passenger
vehicle with 800-2000 kg. In the simulation, there is no input for the throttle angle.
197
A.4. Steering Angle Input and Calculation of Torque
The steering angle input is collected for a FMVSS test simulation result based
on a similar vehicle parameter. The steering angle signal is imported to the Simulink
vehicle model and converted according to the requirement of the model. As the
simulation considers 4 wheels separately, the torque calculated for the vehicle is
distributed by applying DEMUX to get the magnitude of torque experienced by each
wheel.
198
A.5. Calculation of longitudinal and lateral forces acting on the front and rear tyres
The longitudinal and lateral forces are calculated from each tyre. The lateral
forces from each tyre are combined to observe the total lateral movement of the
vehicle. The velocity of the vehicle in the longitudinal and lateral direction and yaw
rate of the vehicle are calculated for the sudden change in angle of intention.
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A.6. Vehicle Body Dynamics
The model below demonstrates the calculation of vehicle body dynamics
considering the longitudinal and lateral forces on each tyre, the position of CG in the
longitudinal, lateral and vertical direction, rolling resistance, steering input as the
angle of intention and aerodynamic forces. The mgsinθ noted in the figure below is
the function of road inclination. The magnitude of θ is considered as zero according
to the assumptions made for the vehicle model creation.
200
A.7. Wheel Dynamics and Calculation of normal forces acting on the front and rear tyres
The normal forces acting on the tyres are calculated in the model below.
Torque and wheel inertia is given as input here. This calculation is done for each tyre
subjected to the front wheel drive consideration for the vehicle model. The effective
radius of the tyre, reff is calculated as a function of angular velocity, ww of the wheel
and the longitudinal velocity of the vehicle. Longitudinal velocity Vx is considered in
the direction of longitudinal vehicle motion and (reffww - Vx) is in the opposite
direction. The longitudinal tyre stiffness Cσ for the front and rear tyre are calculated
from the longitudinal tyre force as a function of slip ratio.
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A.8. Vx, Vy and Yaw rate calculation
Vx, Vy and Yaw rate is calculated by using the vehicle body equations as
shown in equation 4.9, 4.10 and 4.11 accordingly. Vx, Vy and Yaw rate constitute
three degrees of freedom related to the vehicle.
202
A.9. Tyre grip and lateral load transfer calculation
To calculate the tyre grip and the lateral load transfer of the vehicle while
cornering, the magnitude of traction generated by the tyre as function of vertical load
acting on it. The data is then linear interpolated to obtain the magnitude for a
calculated lateral load at a given condition. The lateral acceleration is given as input
over time which creates the graph of tyre grip over lateral load transfer for the acting
lateral acceleration at that time.
203
A.10. Cornering Dynamics calculation
For the cornering dynamics of the vehicle a sensor is applied to the vehicle
model body. It senses three data to demonstrate the dynamic characteristics. The
(x,y) coordinate of the vehicle on the track, the velocity of the vehicle in longitudinal
and lateral direction and the yaw rate of the vehicle. As the model is to plot the
trajectory of the vehicle and the front-rear tyre slip ratio, the yaw rate data is
terminated as shown in figure below. In the Fx generator, the data is followed by the
trend of motor power data.
204
A.11. Wheel Dynamics and lateral force calculation
The sprung and un-sprung roll is calculated to get the position of the vehicle
in the track considering the cornering dynamics. Data sensed from the wheel is
converted into force. The steering angle data is given only for the front wheels and it
is imported to the axle. The sprung, un-sprung and wheel sensed data is combined in
a math function to calculate the lateral force on the tyre while cornering.