Multi-objective shape optimization of Permanent Magnet Synchronous Motor based on Kriging surrogate model and design domain reduction

被引:0
|
作者
Bao, Jianwen [1 ]
Xing, Jian [1 ]
Luo, Yangjun [1 ]
Zheng, Ping [2 ]
机构
[1] Dalian Univ Technol, Key Lab Adv Technol Aerosp Vehicles Liaoning Prov, Dalian 116024, Peoples R China
[2] Harbin Inst Technol, Dept Elect Engn, Harbin 150080, Heilongjiang, Peoples R China
基金
中国国家自然科学基金; 国家重点研发计划;
关键词
PMSM; Shape optimization; Kriging surrogate model; Design domain reduction; Multi-objective optimization; DRIVES;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Permanent Magnet Synchronous Motor (PMSM) is a nonlinear, multi-physics coupled system that makes it difficult to build an accurate mathematical model to optimize design parameters. Traditional design for PMSM always relies on the experience of engineers. Although some works have been done for the size optimization of motors, the performances of PMSM still need to be improved. In this paper, a multi-objective shape optimization method is proposed for the optimal design of PMSMs. In the optimization model, the shape of slot and the size of permanent magnets are considered as design variables. The objective is to minimize the torque ripple and the loss under the constraint of average torque of motors. To obtain the accurate global solution, the Kriging surrogate model algorithm with an effective design domain reduction is used. Several novel designs that can obviously reduce the torque ripple and loss of PMSM are obtained by using the proposed method. The optimization results also indicate that using the proposed shape optimization algorithm is more effective in the optimal performance design of PMSM than using size optimization methods.
引用
收藏
页码:2378 / 2381
页数:4
相关论文
共 50 条
  • [21] Multi-Objective Optimization Design of Bearingless Permanent Magnet Synchronous Generator
    Hua, Yizhou
    Zhu, Huangqiu
    Xu, Ying
    IEEE TRANSACTIONS ON APPLIED SUPERCONDUCTIVITY, 2020, 30 (04)
  • [22] Heat dissipation analysis and multi-objective optimization of a permanent magnet synchronous motor using surrogate assisted method
    Li, Yongsheng
    Li, Congbo
    Garg, Akhil
    Gao, Liang
    Li, Wei
    CASE STUDIES IN THERMAL ENGINEERING, 2021, 27
  • [23] Multi-objective particle swarm optimization of alnico in permanent magnet synchronous motor
    Fan, Jian-Jian
    Wu, Jian-Hua
    Li, Xian-Lin
    Shen, Lei
    Dianji yu Kongzhi Xuebao/Electric Machines and Control, 2009, 13 (02): : 173 - 178
  • [24] Multi-objective comprehensive teaching algorithm for multi-objective optimisation design of permanent magnet synchronous motor
    Sun, Changle
    Wen, Feng
    Xiong, Wei
    Wang, Haitao
    Shang, Hongxu
    IET ELECTRIC POWER APPLICATIONS, 2020, 14 (13) : 2564 - 2576
  • [25] Multi-objective Optimal Design for In-wheel Permanent Magnet Synchronous Motor
    Shin, Dong-joo
    Kwon, Byung-il
    2009 INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES AND SYSTEMS, VOLS 1-3, 2009, : 562 - 566
  • [26] Multi-objective optimization of permanent magnet synchronous motor with partition between poles Halbach magnet
    Zhejiang University, Hangzhou 310027, China
    Diangong Jishu Xuebao, 2009, 9 (53-58):
  • [27] Multi-objective optimization design of permanent magnet linear synchronous machine based on stratified strategy
    Chi, Song
    Yan, Jianhu
    Guo, Jian
    Zhang, Jianjie
    Zhang, Yuxi
    INTERNATIONAL JOURNAL OF APPLIED ELECTROMAGNETICS AND MECHANICS, 2023, 71 (03) : 237 - 259
  • [28] Multi-Objective Optimization of Permanent Magnet Synchronous Motor for Electric Vehicle Considering Demagnetization
    You, Yong-min
    Yoon, Keun-young
    APPLIED SCIENCES-BASEL, 2021, 11 (05): : 1 - 12
  • [29] Kriging-Assisted Multi-Objective Design of Permanent Magnet Motor for Position Sensorless Control
    Li, Min
    Gabriel, Fabien
    Alkadri, Maria
    Lowther, David A.
    IEEE TRANSACTIONS ON MAGNETICS, 2016, 52 (03)
  • [30] Multi-objective Optimization Design of Bearingless Permanent Magnet Synchronous Motor Using Improved Particle Swarm Optimization Algorithm
    Hua Y.
    Liu Y.
    Pan W.
    Diao X.
    Zhu H.
    Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering, 2023, 43 (11): : 4443 - 4451