volume | PIER Journals

Abstract

This study aims to achieve the co-optimization of thrust force and thrust fluctuation using a long secondary double-sided linear flux switching permanent magnet motor (LSDLFSPM). Firstly, the motor model is constructed and derived using a theoretical approach. Subsequently, the motor parameters are subjected to sensitivity analysis using the Taguchi method to identify the significant influencing factors. Based on the screening results, the Response Surface Method (RSM) is employed to construct the test space and derive regression equations for thrust force and thrust fluctuation. The Multi-Objective Grasshopper Optimization Algorithm (MOGOA) is then utilized to iteratively optimize the regression equation for optimal parameter sizes. Finally, the optimized results are validated through finite element analysis (FEA) and compared with the original motor performance to demonstrate the effectiveness of the optimization approach proposed in this paper.

1. Zhou, Haibo, Xiaoling Wang, Zijiao Zhang, and Ji-An Duan, "A novel thrust force test method for a class of precision noncontact linear motion actuators," IEEE Transactions on Industrial Electronics, Vol. 66, No. 7, 5383-5391, Jul. 2019.

2. Hu, Chunfu, Hesong Cui, Xiongsong Li, Xiao Liu, and Shoudao Huang, "Thrust characteristic improvement of permanent magnet linear synchronous motor based on multiobjective optimization," 2021 13th International Symposium on Linear Drives for Industry Applications (LDIA), 1-5, Wuhan, China, 2021.

3. Zhao, Wenxiang, Anqi Ma, Jinghua Ji, Xu Chen, and Tian Yao, "Multiobjective optimization of a double-side linear Vernier PM motor using response surface method and differential evolution," IEEE Transactions on Industrial Electronics, Vol. 67, No. 1, 80-90, Jan. 2020.

4. Wang, Qi, Ke Wang, Yadong Hu, Dihui Zeng, and Jin Wang, "Global optimization of a complementary and modular linear flux-switching permanent magnet motor applied for urban rail transit to reduce normal force," 2023 14th International Symposium on Linear Drivers for Industry Applications (LDIA), 1-4, Hannover, Germany, 2023.

5. Zhong, Zaimin, QinghaoXiao, Xiusen Wang, Minglei Yang, and Yeqin Wang, "Optimal design of doubly-fed linear motor for high speed maglev train based on improved genetic algorithm," 2023 IEEE International Conference on Mechatronics and Automation (ICMA), 2089-2094, Harbin, Heilongjiang, China, 2023.

6. Wang, Ke, Yadong Hu, Qi Wang, and QiongXuan Ge, "Optimization of secondary iron of homopolar linear synchronous motor for traction application based on finite element method and regression model," 2023 5th Asia Energy and Electrical Engineering Symposium (AEEES), 453-459, Chengdu, China, 2023.
doi:10.1109/AEEES56888.2023.10114261

7. Shiri, Abbas and Alberto Tessarolo, "Normal force elimination in single-sided linear induction motor using design parameters," IEEE Transactions on Transportation Electrification, Vol. 9, No. 1, 394-403, Mar. 2023.

8. Wen, Cheng, Qiankai Zhao, Mingye Li, Jingna Liu, Mingwei Li, and Xingqiao Zhao, "Multi-objective optimization based on hyperparameter random forest regression for linear motor design," International Journal of Machine Learning and Cybernetics, Vol. 13, No. 10, 2929-2942, 2022.

9. Cheng, Ming, Peng Han, and Wei Hua, "General airgap field modulation theory for electrical machines," IEEE Transactions on Industrial Electronics, Vol. 64, No. 8, 6063-6074, Aug. 2017.

10. Liu, Qiang, Haitao Yu, Minqiang Hu, Chunyuan Liu, Jing Zhang, Lei Huang, and Shigui Zhou, "Cogging force reduction of double-sided linear flux-switching permanent magnet machine for direct drives," IEEE Transactions on Magnetics, Vol. 49, No. 5, 2275-2278, May 2013.

11. Wang, Yao, Jinhua Du, and Zhao Hou, "Optimization and performance investigation of high precision permanent magnet linear motor," 2022 25th International Conference on Electrical Machines and Systems (ICEMS), 1-6, Chiang Mai, Thailand, 2022.

12. Chen, Qiushuo, Ying Fan, Yutong Lei, and Xu Wang, "Multi objective optimization design of unequal halbach array permanent magnet vernier motor based on optimization algorithm," 2021 IEEE Energy Conversion Congress and Exposition (ECCE), 4220-4225, Vancouver, BC, Canada, 2021.
doi:10.1109/ECCE47101.2021.9595558

13. Kim, Woo-Hyeon, Chang-Woo Kim, Hyo-Seob Shin, Sang-Sup Jeong, and Jang-Young Choi, "Optimal design of short-stroke linear oscillating actuator for minimization of side force using response surface methodology," IEEE Transactions on Magnetics, Vol. 58, No. 2, 8201905, Feb. 2022.
doi:10.1109/TMAG.2021.3088453

14. Saremi, Shahrzad, Seyedali Mirjalili, and Andrew Lewis, "Grasshopper optimisation algorithm: Theory and application," Advances in Engineering Software, Vol. 105, 30-47, Mar. 2017.
doi:10.1016/j.advengsoft.2017.01.004

15. Mirjalili, Seyedeh Zahra, Seyedali Mirjalili, Shahrzad Saremi, Hossam Faris, and Ibrahim Aljarah, "Grasshopper optimization algorithm for multi-objective optimization problems," Applied Intelligence, Vol. 48, 805-820, 2018.

Professor Cheng Wen

Dr. Jian Cui

Dr. Mingye Li

Dr. Zhiping Wan

Dr. Yujian Chang