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Active Temperature Control of Li-ion Batteries in Electric Vehicles

B. Ji, X.G. Song*, W.P. Cao and V. Pickert

School of Electrical and Electronic Engineering, Newcastle University, United Kingdom, England, E-mail: *xueguan.song@ncl.ac.uk

Keywords: Batteries, cooling, fluid flow control, temperature control, thermal management

Abstract Due to the high reliability and cost-effectiveness, Lithium-ion (Li-ion) batteries find their wide-spread use in electric vehicle applications. However, EV batteries operate in harsh environments and the body temperature of each cell in a battery pack tends to be largely different, significantly reducing life expectancy of the batteries. The final aim of this work is to propose an active temperature control method to equalize the temperature distribution of the batteries. However, the first step at the present stage attempts to improve the unbalanced thermal problem existing in current battery packs by optimally arranging battery cells and controlling the coolant flow rate. The results show that all cells within the battery pack can be maintained within a few °C of each other during operation. Therefore, unbalanced electrical properties can be significantly alleviated between different cells so that the overall performance and maintenance of the battery pack is improved.

1 Introduction

With the increasing concerns over depletion of natural resources (e.g oil and gas) and air pollution, governments, automakers and consumers worldwide have been working together to adapt a shift to green transportation. This has spurred intense competition and ongoing revolution in the development of electric vehicles (EVs) and hybrid electric vehicles (HEVs) which are an alternative to the conventional internal combustion engine (ICE) vehicles with better efficiency and lower CO2 emissions. Among all EVs and HEVs, electrochemical batteries are core components used for energy storage, similar to the fuel tank in ICE vehicles. Compared to other types of commercial electrochemical batteries, Li-ion battery offer superior performance, including higher energy density (150-250 W·h/kg), higher power density (1800 W/kg), higher cell voltage, lower self-discharge rate (about 1.5% per month) and the absence of the memory effect [1]. However, Li-ion cells suffer from high cost, non-uniformity, narrow operational ranges and reliability issues, limiting their widespread application in automotive applications [2,3]. Moreover, when these batteries fail,

serious consequence such as fires or explosions could occur, posing a threat to the vehicle operation and human life. Table 1 lists some of the battery-induced electrified transportation incidents that have depressed both industry and customers. Causes of battery failures can be attributed to excessive heat, electrical abuse (e.g. overcharging/over discharging or short circuit), mechanical damage (e.g. denting) and manufacturing defects (e.g. poor cell design). Of them, thermal runaway is a common failure mode that can be observed in all types of electrochemical batteries. This could be particularly hazardous for Li-ion cells owing to their high energy density and flammable electrolyte [4-8].

Time Incident Fire cause Apr 2011

Zotye M300 EV taxi fire

Battery shorted and caught fire

May 2011

Chevy Volt’s crash test

Battery shorted and caught fire

May 2012 BYD e6 fire Shorted due to a

crash May 2012

Fisker Karma in a home fire Unknown

Oct 2012

16 Fisker Karmas fire

Salt water into the electrical system

Oct 2012 3 Toyota Prius fire Salt water into the

electrical system Jan 2013

Boeing787 emergency landing

Overheating of the battery

Mar 2013

i-MiEV charging fire

Battery melt and caught fire

Table 1: Examples of the recent Li-ion battery incidents Note: The data is from internet Therefore, the battery temperature must be crucially controlled to avoid any thermal runaway and improve the reliability and durability of battery. Particularly, the predominantly used electrical-chemistries battery such as lithium manganese oxide (LiMn2O4) battery and lithium iron phosphate (LiFePO4) battery should operate within a narrow temperature range for optimization and safety purposes [8]. Table 2 lists the cooling method used for batteries thermal management of recent EV/HEV. It’s clear that the active liquid cooling method has a good potential for the future EV/HEVs, so research on liquid cooling method is necessary. Commonly, the existing cooling methods (no matter liquid or air, passive or active) all pay attention to the whole

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performance, i.e. the average temperature of the battery package rather than each battery cell in the package. However, it is worth to say that it’s not the average temperature of the whole package but the average temperature of the overheated battery cells give the predominant effect on the battery performance and reliability. Inadequate thermal management only considering the whole average temperature could result in wear-out, uneven temperature distribution, and safety hazards of battery cells, which in turn, cause the failure or hazard of the whole battery package. Therefore, the final aim of the present work is to propose an active temperature control method to dynamically equalize the temperature of all battery cells in a package. However, the work in the present paper attempts to improve the unbalanced thermal problem of multiple battery cells by optimally arranging battery cells and controlling the coolant flow rate. The results show that all cells within the battery pack can be maintained within a few °C of each other during operation. Therefore, unbalanced electrical properties can be significantly alleviated between different cells so that the overall performance and maintenance of the battery pack is improved.

EV/HEV model (year)

capacity (kWh) /Max Power (kW)

Cell number /shape

Cooling method

Nissan Leaf (2013)

24/80 192/ Prismatic

Passive air

Chevy Volt (2013)

16.5/136 288/ Prismatic

Active liquid

Ford Focus (2012)

23/92 Prismatic Active liquid

Tesla Model S

85/310 7000+/ Cylindrical

Active liquid-

Fisker Karma (2012)

20.1/160 315/ Prismatic

Active air

Mitsubishi i-MiEV

16/47 88/ Prismatic

Active air

BYD e6 48/75 Active air BMW Mini E

35/150 Cylindrical Passive air

Smart ED (2011)

17.6/35 Cylindrical Active liquid-

Table 2: Li-Ion batteries used in existing EVs/PHEVs Note: The data is from internet

2. Temperature control techniques When a large energy capacity and power output are needed in automotive applications, battery cells are generally packed together and connected in parallel and in series to meet the specifications. Some existing EVs/HEVs and the batteries employed are listed in Table 2 for information. Both air cooling and liquid cooling can be found in the industry with majority transitioning to liquid cooling methods. In terms of form factor, the battery cells can mainly be categorized as cylindrical and prismatic cells. The latter offers more

dimensional flexibility and their cooling techniques are thus the focus of this paper. Typical prismatic cell liquid cooling system employs thin aluminum cooling plates sandwiched between two cells. Multiple cells and cooling plates are then stacked together to form a pack as shown in Fig. 1. In an EV configuration, liquid coolant first flows into a header and is then distributed into parallel channels. The flow rates distribution through the parallel channels are often not uniform due to their physical placement asymmetries. This can cause uneven temperature distribution which will consequently lead to unbalanced operation of battery cells in the battery pack with compromised capacity and performance. In addition, large internal current loops can form within the pack, which can drastically shorten the battery life.

Fig. 1 Configuration of a battery pack with 4 prismatic cells and 5 cooling plates

The battery thermal management is of prime importance in EV/HEV development. Its goal is to regulate the battery pack to operate in the desired temperature range and achieve uniform temperature distribution, and in turn, to enhance energy efficiency and battery’s lifetime.

3. Numerical Models

This paper models the turbulence flow and heat transfer in the liquid cooler by using CFD simulations. Two-dimensional (2-D) steady Reynolds-averaged Navier–Stokes equations and the energy equations are solved numerically. Standard turbulence model is used because it has been extensively validated for a wide range of flows including complex flows (e.g. channel and boundary layer flows and separated flows). Four conditions are assumed in the modeling of the battery heat transfer, which are: (a) the flow is turbulent and incompressible, (b) the flow is in a steady state, (c) the buoyancy and radiation heat transfer are neglected, and (d) the thermo-physical properties of the fluid are temperature independent. Therefore, the governing equations (continuity, momentum and energy equations) are established in Eqs 1-3.

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0i

i

ux

(1)

23

i j ji kij i j

j i j j i k j

u u uu up u ux x x x x x x

(2)

ieff i ij Eeff

j j j

u E p T u Sx x x

(3)

where ρ is the fluid density, ui is the velocity component, p is the static pressure, is the molecular viscosity (also referred to as the dynamic viscosity), is the Kronecker delta function, E is the total energy per unit mass, SE is the energy generation rate per unit volume, T is the temperature,

iu represents the velocity fluctuation,i ju u is the Reynolds

stress, eff is the effective thermal conductivity, and is the deviatoric stress tensor. The thermal transfer through the battery cells is indeed a conjugate heat transfer problem, which involves heat conduction and forced convection, thereby the governing equation of the solid is required.

0s Ej j

T Sx x

(4)

wheres is the thermal conductivity of the solid and T is the

temperature. Fig. 2 shows the three-dimensional (3-D) geometry and the computational model of the battery pack. The battery pack has 8 battery cells stacked together with cooling channels between the cells. In the initial design, cooling water is arranged to flow in the 5mm-width channel between two adjacent battery cells and there is a uniform distance of 5mm between each battery cell. There are two nozzles, comprised of the inlet with a constant flow rate of 0.065Kg/s, and the outlet with zero pressure. The battery cell is assumed to have a uniform heat dissipation of 6W per cell. The inlet turbulence intensity is assumed to be 5% and smooth wall conditions have been implemented over the inside walls. The convergence criteria are assumed to be satisfied if the root mean square (RMS) residual is smaller than 10-5.

(a)

(b)

Fig. 2. Configuration of the battery package (a) structural

model and (b) CFD model

4. CFD result of the initial design

The pressure, velocity streamline and temperature distribution at the middle plane are shown in Fig. 3(a), (b) and (c), respectively. It can be seen that the further the coolant channels are away from the inlets/outlets, the higher the static coolant pressure is. Similarly, the flow rate of the coolant channels between two battery cells decreases with the accumulated pressure. Therefore, the temperature of battery cell increases gradually for a given heat loss within each cell and this leads to the inhomogeneous temperature distribution over the battery pack, which is a common and hazardous problem for the thermal management of the battery pack. The average temperature of each battery cell is tabulated in Table 3. The minimum temperature (26.62oC) exists in the first battery. The temperature of the sequentially placed battery cells increases monotonously with the minimum (26.62oC) and maximum (33.57oC) temperature observed in the first and last battery cells, respectively. The average temperature of the battery pack is 29.47oC and their standard deviation is 2.49oC.

(a)

4

(b)

(c)

Fig. 3. CFD results of the initial design (a) pressure distribution; (b) velocity streamline; and (c) cell temperature distribution

5. Optimization Formulation

Temperature affects the battery performance and its safety. This is because many electrochemical properties are related to the temperature such as charge acceptance, reaction rate, etc. Not only a reliable operating temperature region is required, but also even temperature distribution between different cells. This can optimize the power and energy density, efficiency and cyclic life of the pack.

Battery cell Temperature (oC)

initial optimized 1 26.62 27.22 2 27.03 27.03 3 27.65 27.12 4 28.52 27.07 5 29.63 26.98 6 30.72 27.29 7 32.05 27.35 8 33.57 27.48

Table 3: Average temperatures in different battery cell of initial design for initial and optimized designs

Temperature affects the battery performance and the safe operation of EV vehicles. This is because many electrochemical properties are related to the temperature such as charge acceptance, reaction rate and so forth. Not only a reliable operating temperature region is required, but also even temperature distribution between different cells. This can optimize the power and energy density, efficiency and cyclic life of the pack. Hence, to obtain uniform performance of all battery cells, the standard deviation of the 8 battery cells’ temperature is set to be the design objective , where the 9 distances as shown in Fig. 2 are set as the design variables with design range of [1.0mm~5mm]. The surrogate model-based optimization and sequential quadratic programming (SQP) method are carried out for the optimization. The optimum result is listed in Table 2, where the average temperature of these 8 battery cells is 27.19oC, and the standard deviation decreases significantly from the initial 2.49oC to 0.17oC. The corresponding design variables are:

. Fig. 4 plots the average temperature of each battery cell in the initial design and optimum design. It can be seen that the velocity streamline becomes more even between different passages, which produce the similar heat transfer performance for different battery cell, as shown in Fig. 5. It proves that uniform arrangement of battery cells in a liquid cooler may not be the best design, uneven arrangement will be better for the whole performance of battery package from the viewpoint of uniform cooling.

Fig. 4 Comparison of initial design (base design) and optimum design

(a)

5

(b)

(c)

Fig. 5. CFD results of the optimum design (a) pressure distribution; (b) velocity streamline; (c) temperature distribution

6. Conclusion This paper has proposed an optimisation method for distributing battery cells in equivalent individual cell temperature by controlling the coolant flow rate. The results show that all cells within the battery pack can be maintained within a few °C of each other during operation. Therefore, unbalanced electrical properties can be alleviated between different cells so that the overall performance and maintenance of the battery pack is improved.

Acknowledgements

The authors gratefully acknowledge the contributions of EPSRC project EP/K008552/1 on Novel calorimeter for developing high-efficiency permanent-magnet machines and power converters (NovCHEPM).

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