Optimization of PMSM for EV based on Vibration and Noise Suppression

Authors

  • Mingwei Zhao 1) School of Electromechanical Engineering and Automation Shanghai University, Shanghai, 200444, China 2) School of Electrical Engineering and Automation Jiangsu Normal University, Xuzhou, 221116, China
  • Xiangyu Wang School of Electrical Engineering and Automation Jiangsu Normal University, Xuzhou, 221116, China
  • Lijun Liu 1) School of Electromechanical Engineering and Automation Shanghai University, Shanghai, 200444, China 2)School of Electrical Engineering and Automation Jiangsu Normal University, Xuzhou, 221116, China
  • Xiaowei Tu School of Electromechanical Engineering and Automation Shanghai University, Shanghai, 200444, China
  • Qinghua Yang School of Electromechanical Engineering and Automation Shanghai University, Shanghai, 200444, China

DOI:

https://doi.org/10.13052/2024.ACES.J.390109

Keywords:

genetic optimization algorithm, multi-objective hierarchical optimization, PMSM, skewed slots optimization, vibration and noise suppression

Abstract

The key to the suppression of vibration and noise for PMSM is the optimization of electromagnetic excitation force. The method of motor body optimization can effectively reduce the radial excitation force of the motor, so as to suppress the vibration and noise of the motor. Firstly, the stator structure of the motor is optimized with V-shape skew slot based on the analytical modeling of the radial electromagnetic excitation force of the motor. Then, the structural parameters of the motor that affect the electromagnetic excitation force of the motor are determined, and the average torque, torque ripple and radial electromagnetic excitation force generated by tangential electromagnetic excitation force are taken as the optimization objectives. The sensitivity analysis and classification of the structural parameters of the motor are carried out. The multi-objective genetic algorithm and response surface method are combined to optimize the structural parameters of the motor. Finally, the finite element analysis, modal analysis, multi-speed vibration and noise analysis of the optimized motor are done. The performance comparisons before and after optimization have proved that the peak of equivalent sound power level have decreased by 8.65% after the optimization of V-shaped skewed slot structure. After the optimization of structural parameters, the power level of permanent magnet synchronous motor has been reduced by 9.22%. For the vibration noise caused by resonance and the main frequency of vibration noise harmonics, the suppression effects are also better than those of V-shape skewed slots optimization, and the ERPL values are reduced by 9.22% and 10.12%, respectively, in two cases. The results show that the vibration and noise of permanent magnet synchronous motor are effectively suppressed.

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Author Biographies

Mingwei Zhao, 1) School of Electromechanical Engineering and Automation Shanghai University, Shanghai, 200444, China 2) School of Electrical Engineering and Automation Jiangsu Normal University, Xuzhou, 221116, China

Mingwei Zhao was born in Shandong China, in 1975. He received the M.S. degree in power electronics and power drive from Nanjing University of Aeronautics and Astronautics, Nanjing, China, in 2012, and is currently pursuing the Ph.D. degree in control science and control engineering from Shanghai University, Shanghai, China.

Since 2006, he has been an experiment lecturer with the school of Electrical Engineering and Automation, Jiangsu Normal University, Xuzhou, China. He is the author of 10 articles. His research interests include the robot dynamic drive and cooperative control and industrial motion control system.

Xiangyu Wang, School of Electrical Engineering and Automation Jiangsu Normal University, Xuzhou, 221116, China

Xiangyu Wang was born in Jiangsu, China. He received the B.S. degree in electrical engineering from Jinling Institute of Science and Technology, Nanjing, China, in 2019, and is currently pursuing the M.S. degree in Electrical Engineering from Jiangsu Normal University, Xuzhou, China. His research interests include design and optimization of new energy electric drive system.

Lijun Liu, 1) School of Electromechanical Engineering and Automation Shanghai University, Shanghai, 200444, China 2)School of Electrical Engineering and Automation Jiangsu Normal University, Xuzhou, 221116, China

Lijun Liu was born in Shanxi, China, in 1977. She received the M.S. degree in power electronics and power drive from China University of Mining and Technology, Xuzhou, China, in 2006.

She is currently a lecturer with the school of Electrical Engineering and Automation, Jiangsu Normal University, Xuzhou, China. She has published more than 10 articles. Her research interests include design and optimization of new energy electric drive system and industrial motion controlsystem.

Xiaowei Tu, School of Electromechanical Engineering and Automation Shanghai University, Shanghai, 200444, China

Xiaowei Tu received the Ph.D. degree from University of Technology of Compiegne (UTC), France in 1987. He worked as professor in UTC, and later he became a researcher in French National Research Center (CNRS) in early 1990s. Since 1997, he has been working also as a researcher and R&D project manager in different Canadian research institutes.

He is currently a professor at the School of Mechatronic Engineering and Automation, Shanghai University, China.

Qinghua Yang, School of Electromechanical Engineering and Automation Shanghai University, Shanghai, 200444, China

Qinghua Yang was born in Shandong, China, in 1981. Ph.D., Associate professor, master supervisor. His research interests include sensor design and development, aviation ground detection and integrated Testing, industrial measurement and control system development and embedded control.

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Published

2024-01-31

How to Cite

[1]
M. Zhao, X. Wang, L. Liu, X. Tu, and Q. Yang, “Optimization of PMSM for EV based on Vibration and Noise Suppression”, ACES Journal, vol. 39, no. 01, pp. 64–80, Jan. 2024.

Issue

2024: Vol 39 Iss 1

Section

General Submission

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