ansys chu y chicago modeling and simulation of brushless dc motor drive system
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ansys--chu y--chicago-modeling-and-simulation-of-brushless-dc-motor-drive-systemTRANSCRIPT
Ansys Convergence Conference - Chicago
Modeling and Simulation of Permanent Magnet
Brushless Motor Drives
Piyush Desai, Ph. D.
PD Consulting Inc.
+1 312 505 7805
Presented at the 2014 ANSYS Regional Conference Chicago May 23, 2014
Ansys Convergence Conference - Chicago
Services:
•Design & development of inverters
•Design and virtual prototyping of electric machines
•Analyses, modeling, and simulations of electro-mechanical systems
•Development of control algorithms for motor drives and servo systems
•System design and layout of large utility scale PV solar plants
About PD Consulting
20+ years of experience in R & D, project management, and
product development
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Ansys Convergence Conference - Chicago
History of Motors
1819: Danish scientist Orsted
observed that a current-carrying
wire produces a magnetic field
M. Faraday devised an
experiment to demonstrate this
1883: Nikola Tesla
invented a practical AC
motor
1832: William Sturgeon
invented commutator 1831: Joseph Henry’s
improved version
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PM Brushless Motor: BLDC, PMAC, PMSM
PM on the Rotor
Laminated Stator with Windings Position Sensor
Encapsulated Design
http://www.danahermotion.com/education/learn_about_mc/servohandbook/motor/comparison/brush_vs_brushless.php
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Choices to Make
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• Motor: BDC, BLDC, PMAC
• Controls: Trapezoidal, sinusoidal, field oriented
• Switching: Hysteresis, PWM (sine triangle,
space vector)
• Modeling approach: o Simple model: motor as 2nd order ODE; inverter as gain
o Detailed model: 3-phase motor as 5th order ODE; switching
inverter; detailed modeling of the controls
o Multi-physics simulation: co-simulation of FEA motor model and circuit based inverter
Objective: converge to an optimal design
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Torque-Speed Curve
Torque
Speed
Motor capabilities for requirement verification Motor capabilities for requirement verification
An important metrics for relative comparison An important metrics for relative comparison
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PM Machine Theory
Mag
ne
tic F
ield
B
Mag
ne
tic F
ield
B
Shaft/Pivot
Fo
rce F
i
Fo
r ce
Fi
Fo
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F
Fo
rce F
r
_
= where = 2 t tT K I K N r Sin B L
2 e ee K where K N r B L Sin
ec
eb
ea
LaRa
LbRb
LcRc
Moto
r T
erm
ina
ls
n
0 0 0 0
0 0 0 0
0 0 0 0
an a a a
bn b b b
cn c c c
V R i L i ed
V R i L i edt
V R i L i e
DCV
R L
Back-emf
Load
+
_
emT
LT
I
em L
dT T J
dt
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dt
b ee K
= tT K I
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Ansys Convergence Conference - Chicago
Options for BLDC Machine Model
Purely Analytical RMxprt
Maxwell FEA © PD Consulting 8
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When RMxprt / Maxwell?
RMxprt Maxwell FEA
Fast Motor Design &
Model Generation
Design Studies
Fast Circuit Simulations
High Fidelity Simulations
Calculating Losses
Accounting for Saturation
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Simple Model
Electrical System Mechanical
System
Electrical/Mechanical Constants
Simplorer Implementation
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Simple Model Simulation Results
Motor Speed
DC Current
Simple “average – DC” model and reflects 2nd order nature of motor model
Does not take in to account commutation and inverter switching
Insensitive to number of pole pairs
Torque vs. Speed
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Detailed BLDC Drive Model
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Ansys Convergence Conference - Chicago
Comparison: Torque-Speed Curves
More than 10% reduction in Capability Curve
Simple Model
Detailed Model
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Phase Current
Phase A Current
Phase ABC Current
Current Ripple due to
Commutation
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Output Torque
Commutation Current Ripple Torque Ripple
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Quantitative Analysis of Torque
Commutation Ripple
Frequency in Hz
Torque in Nm
DC (Average) Torque Switching Ripple May 23, 2014 © PD Consulting 16
Ansys Convergence Conference - Chicago
Comparison of 4 and 6 Pole Motors
Torque vs. Speed
4-pole Motor with Simple Model (Red)
6-pole Motor with Simple Motor (Blue)
4-pole Motor with Detailed Model (Green)
6-pole Motor with Detailed Model (Magenta)
High Speed Motor
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4-pole Motor with Simple Model (Red)
6-pole Motor with Simple Model (Blue)
4-pole Motor with Detailed Model (Green)
6-pole Motor with Detailed Model (Magenta)
Torque vs. Speed
Industrial Motor
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Comparison of 4 and 6 Pole Motors
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Summary of both the Modeling Approaches
Simple Model:
• Simple, quick, good enough for basic understanding
• Commutation and # of poles not accounted for
• Needs ample margin in the design
Circuit simulations:
• Longer simulation time, more accurate (capability curve, current and torque ripples, efficiency estimation, # of poles, etc.)
• Can capture the system dynamics and transients: filter delay, digital sampling, IGBT/MOSFET switching
• Commutation effects reduction in the capability curve; current and torque ripple
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Baseline Model
• Results must show typical/generic ‘real-world’ responses
• Should be easily adaptable/configurable
• Validated and verified o Validation: ‘tweak’ the model to match with one set of
experimental data
o Verification: match the simulation results with another set of experimental data
Now you have a good model that can be used for optimization
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Optimization Case Study
Requirements:
• Efficiency at an operating point
• Torque ripple
• No load speed
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SPM Lower Inductance higher current ripple higher torque ripple
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Optimization Step – 1
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Optimization Step -2
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BLDC (Red)
FOC with Sine PWM (Blue)
FOC with SVM (Magenta)
Torque vs. Speed
FOC-SVM with Inductor: Needs Little more No Load Speed
(SPM Field Weakening is Not Efficient)
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Optimization Step-3
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Optimize Inductor Size & Switching Frequency
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Thank you !!
Questions?
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