Optimal design of modular dual-field modulated permanent magnet linear motors with thrust characteristics

Abstract

To reduce thrust ripple and cost and improve the average thrust of permanent magnet linear motors, a modular dual-field modulation permanent magnet linear motor was studied, and the parameters were optimized. First, sensitive parameters were selected using the Taguchi method, and then the optimal variables were sampled using the optimal Latin hypercube experimental design method and an ensemble of surrogates model of optimization objectives, and its accuracy was verified. Next, a multi-objective particle swarm optimization algorithm was used to optimize the purpose of “maximum average thrust and minimum thrust ripple”, and the Pareto front of average thrust and thrust ripple was obtained. Finite element analysis showed that the optimized modular dual flux-modulation permanent magnet linear motor (MDFMPMLM) had a 29.5% reduction in thrust ripple and a 5% increase in average thrust compared to the original motor. This study provided an effective method for improving the performance of permanent magnet linear motors.

Keywords

field modulation / thrust characteristics / finite element analysis / ensemble of surrogates model / permanent magnet linear motor / multi-objective optimization

References

[1] LI S. Report on the work of the 8th council meeting of china elevator association. China Elevator, 2023, 34(5): 14-22.

[2] FAN H, CHAU K T, LIU C H, et al. Quantitative comparison of novel dual-PM linear motors for ropeless elevator system. IEEE Transactions on Magnetics, 2018, 54(11): 8106506.

[3] MORIZANE T, MASADA E. Study on the feasibility of application of linear induction motor for vertical movement. IEEE Transactions on Magnetics, 1993, 29(6): 2938-2940.

[4] KOU B, LUO J, YANG X, et al. Modeling and analysis of a novel transverse-flux flux-reversal linear motor for long-stroke application. IEEE Transactions on Industrial Electronics, 2016, 63(10): 6238-6248.

[5] LING Z J, ZHAO W X, JI J H, et al. Overview of high-thrust permanent magnet linear actuator and its key technologies. Transactions of China Electrotechnical Society, 2020, 35(5): 1022-1035.

[6] ZONG K F, ZHAO J W, SONG J C, et al. Thrust ripple suppression of v-shaped coil permanent magnet synchronous linear motor. Proceedings of the Chinese Society of Electrical Engineering, 2019, 39(22): 6736-6746.

[7] PENG B, LI L P, ZHANG N, et al. Method for reducing cogging force ripple of double v-structure permanent magnet linear motor. Transactions of China Electrotechnical Society, 2017, 32(22): 108-114.

[8] SONG J C, DONG F, ZHAO J E, et al. Optimization design of coreless permanent magnet synchronous linear motor based on gravity neighborhood algorithm. Proceedings of the Chinese Society of Electrical Engineering, 2017, 37(12): 3594-3601.

[9] MIAO Z C, SU Y. Analysis of detent force in flat-type permanent magnet linear synchronous motor and multi-objective optimization based on parameter classification. IEEJ Transactions on Electrical and Electronic Engineering, 2022, 17(12): 1772-1782.

[10] XU X Z, FENG H C, AI L W, et al. U-shaped permanent magnet convex-pole linear motor: structure and electromagnetic characteristics. Transactions of China Electrotechnical Society, 2021, 36(6): 1179-1189.

[11] JIA Z, YANG W P, HE W, et al. Back-to-back Ω stator transverse flux permanent magnet linear motor. Proceedings of the Chinese Society of Electrical Engineering, 2022, 42(21): 7964-7972.

[12] LUO J, KOU B Q, YANG X B. Optimization and design of double alternating pole transverse flux linear motor. Transactions of China Electrotechnical Society, 2020, 35(5): 991-1000.

[13] CHUNG S U, LEE H J, WOO B C, et al. A feasibility study on a new doubly salient permanent magnet linear synchronous machine. IEEE Transactions on Magnetics, 2010, 46(6): 1572-1575.

[14] SHI C J, LI D W, QU R H, et al. A novel linear permanent magnet vernier machine with consequent-pole permanent magnets and Halbach permanent magnet arrays. IEEE Transactions on Magnetics, 2017, 53(11): 2501404.

[15] DONG X J, CHEN Q, LIU W B, et al. A systematic framework of constructing surrogate model for slider track peeling strength prediction. Science China(Technological Sciences), 2024, 67(10): 3261-3274.

[16] VIANA F A C, HAFTKA R T, STEFFEN V. Multiple surrogates: how cross-validation errors can help us to obtain the best predictor. Structural and Multidisciplinary Optimization, 2009, 39(4): 439-457.

[17] KAZEMIAN A, KHOSRAVI K, SEN S, et al. Optimizing photovoltaic thermal systems with wavy collector Tube: a response surface-based design study with desirability analysis. Applied Thermal Engineering,2025,258(PA): 124475-124475.

[18] JIN X, GUO P H, LI J Y. Multi-objective multi-variable large-size fan aerodynamic optimization by using multi-model ensemble optimization algorithm. Journal of Thermal Science, 2024, 33(3): 914-930.

[19] HAN H H,WANG J, CHEN S, et al. Product quality prediction based on RBF optimized by firefly algorithm. Journal of Systems Engineering and Electronics, 2024, 35(1): 105-117.

[20] CHEN H, LI W K, CUI W C, et al. A pointwise ensemble of surrogates with adaptive function and heuristic formulation. Structural and Multidisciplinary Optimization, 2022, 65(4): 113.

[21] XU Z X, ZHU S R. Multi-objective particle swarm optimization by fusing multiple strategies. Journal of Measurement Science and Instrumentation, 2022, 13(3): 284-299.