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Parameter Estimation of Permanent Magnet Synchronous Machines (eBook)

eBook Download: EPUB
2025
577 Seiten
Wiley-IEEE Press (Verlag)
978-1-394-28043-8 (ISBN)

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Parameter Estimation of Permanent Magnet Synchronous Machines - Zi Qiang Zhu, Kan Liu, Dawei Liang
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Comprehensive reference delivering basic principles and state-of-the-art parameter estimation techniques for permanent magnet synchronous machines (PMSMs)

Parameter Estimation of Permanent Magnet Synchronous Machines reviews estimation techniques of the parameters of PMSMs, introducing basic models and techniques, as well as issues and solutions in parameter estimation challenges, including rank deficiency, inverter nonlinearity, and magnetic saturation. This book is supported by theories, experiments, and simulation examples for each technique covered.

Topics explored in this book include:

  • Electrical and mechanical parameter estimation techniques, including those based on current/voltage injection and position offset injection, under constant or variable speed and load for sensored or sensorless controlled PMSMs, accounting for magnetic saturation, cross-coupling, inverter nonlinearity, temperature effects, and more
  • Recursive least squares, the Kalman filter, model reference adaptive systems, Adaline neural networks, gradient-based methods, particle swarm optimization, and genetic algorithms
  • Applications of parameter estimation techniques for improvement of control performance, sensorless control, thermal condition monitoring, and fault diagnosis

This book is an essential reference for professionals working on the control and design of electrical machines, researchers studying electric vehicles, wind power generators, aerospace, industrial drives, automation systems, robots, and domestic appliances, as well as advanced undergraduate and graduate students in related programs of study.

Zi Qiang Zhu is a Fellow of the Royal Academy of Engineering and the Head of the Electrical Machines and Power Research Group at the University of Sheffield, UK.

Kan Liu is the Assistant Dean of the College of Mechanical and Vehicle Engineering at Hunan University, China.

Dawei Liang is a Postdoctoral Research Associate with the University of Sheffield, UK.


Comprehensive reference delivering basic principles and state-of-the-art parameter estimation techniques for permanent magnet synchronous machines (PMSMs) Parameter Estimation of Permanent Magnet Synchronous Machines reviews estimation techniques of the parameters of PMSMs, introducing basic models and techniques, as well as issues and solutions in parameter estimation challenges, including rank deficiency, inverter nonlinearity, and magnetic saturation. This book is supported by theories, experiments, and simulation examples for each technique covered. Topics explored in this book include: Electrical and mechanical parameter estimation techniques, including those based on current/voltage injection and position offset injection, under constant or variable speed and load for sensored or sensorless controlled PMSMs, accounting for magnetic saturation, cross-coupling, inverter nonlinearity, temperature effects, and moreRecursive least squares, the Kalman filter, model reference adaptive systems, Adaline neural networks, gradient-based methods, particle swarm optimization, and genetic algorithmsApplications of parameter estimation techniques for improvement of control performance, sensorless control, thermal condition monitoring, and fault diagnosis This book is an essential reference for professionals working on the control and design of electrical machines, researchers studying electric vehicles, wind power generators, aerospace, industrial drives, automation systems, robots, and domestic appliances, as well as advanced undergraduate and graduate students in related programs of study.

List of Symbols


Symbol Description Unit
State transition matrix
Control-input model
Remanence T
, Remanence at actual and reference temperatures T
Maximum energy product kJ/m3
, Cognitive and social acceleration constants
Condition number
, -axis gain functions of VSI nonlinearity
, Average values of -axis gain functions of VSI nonlinearity
, -axis extended back-EMF V
Friction coefficient
Frequency of HF signal Hz
First-order gradient
Coercivity kA/m
Intrinsic coercivity kA/m
Identity matrix
Three-phase currents A
, , Three-phase currents A
, -axis currents A
, -axis HF currents A
, -axis currents A
, -axis HF currents A
, Amplitudes of -axis HF currents A
, Average values of -axis currents A
Resolution of sampled current A
Maximum current A
, Amplitudes of positive and negative sequence currents A
, Current perturbations in th and th coils A
Variables of injected -axis current A
Rotor moment of inertia kg m2
Index of discrete sampling instant
, PI constants
, , , , , Gains of cost functions
Gain vector of RLS estimator
Self-inductance H
Mutual inductance H
Phase self-inductance H
Phase leakage inductance H
Second-order harmonic of self-inductance H
, -axis inductances H
, -axis HF inductances H
, -axis mutual inductances H
, -axis HF mutual inductances H
, -axis apparent inductances H
, -axis incremental inductances H
, -axis incremental self-inductances H
, -axis apparent self-inductances H
, -axis apparent mutual inductances H
, -axis incremental mutual inductances H
Average mutual inductance H
Second-order harmonic of mutual inductance H
Overall time error S
Sampling number
Pole pair number
, Cost function
Covariance matrix
Model uncertainty matrix
Measurement noise covariance
Estimated synchronous rotating reference frame
On-state resistance of IGBT
On-state resistance of freewheeling diode
Iron loss resistance
Stator winding resistance
Error of estimated stator winding resistance
, Winding resistance at actual and reference temperatures
Switching pattern of three-phase legs
Clarke transformation
Active durations of space vectors and S
Actual duration of effective time S
Commanded duration of effective time S
Compensation time S
Dead time of power device S
Switch on/off time delay S
Sampling time S
Electromagnetic torque N m
Estimated torque N m
Load torque N m
Control vector in KF
, -axis voltages V
, -axis voltages V
, -axis reference voltages V
, -axis HF voltages V
, -axis HF reference voltages V
Voltage vector reference V
Maximum output phase voltage V
HF voltage signal V
System noise
Observation/measurement noise
Operator norm
Voltage vectors V
, , , Reference three-phase voltages V
, , Distorted three-phase voltage caused by VSI nonlinearity V
On-state voltage drop of IGBT V
Threshold voltage drop of IGBT V
On-state voltage drop of freewheeling diode V
Threshold voltage drop of freewheeling diode V
Variable of injected -axis voltage V
dc bus voltage V
, -axis distorted voltages due to VSI nonlinearity V
Distorted voltage term due to VSI nonlinearity V
Amplitude of injected HF voltage V
Non-zero dc offset V
Threshold voltage V
Total stored energy J
Weight in ANN estimator
Zero-mean white Gaussian system noise
Inertia weight in PSO estimator
, Characteristic roots
, Particle best and overall best locations in PSO estimator
Step variation
, Measured and predicted output variables
Output matrix of RLS estimator
Temperature coefficient of copper %/°C
Temperature coefficient of magnet %/°C
Step length of Newton algorithm
Current advancing angle Deg.
Finite positive constant
Least-square error
Optimal damping ratio
Tuning factor
Convergence...

Erscheint lt. Verlag 20.5.2025
Reihe/Serie IEEE Press Series on Control Systems Theory and Applications
Sprache englisch
Themenwelt Technik Elektrotechnik / Energietechnik
Schlagworte Adaline neural networks • current or voltage injection • electrical machines • Genetic algorithms • Gradient-based methods • inverter nonlinearity • Magnetic saturation • model reference adaptive systems • Parameter Estimation • Particle swarm optimization • PMSMs • position offset injection • Recursive Least Squares • Sensorless control • the Kalman filter • thermal condition monitoring
ISBN-10 1-394-28043-2 / 1394280432
ISBN-13 978-1-394-28043-8 / 9781394280438
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