基于替代模型的旋转磁耦合器磁心结构优化

doi:10.19595/j.cnki.1000-6753.tces.240061

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Abstract During the design process of rotary magnetic couplers, many magnetic cores are typically employed to achieve magnetic constraint, enhance coupling performance, and reduce magnetic leakage. However, decreasing the cost, self-weight, and volume of rotary magnetic couplers is challenging, and power density needs to be improved. In some special applications, it may also affect the reliability of the equipment. Current research mainly relies on engineering experience and trial-and-error methods for magnetic core structure design, causing issues such as imprecise parameter design and extensive simulation workload. This paper proposes a magnetically optimized method based on surrogate modeling to meet the lightweight design requirements of magnetic core structures for rotary couplers. This method can reduce the usage of magnetic cores while ensuring stable transmission performance.
The structural parameters of the rotary magnetic coupler are first determined, a Latin hypercube sampling method is employed to sample different structural parameters randomly, and a dataset is constructed. A surrogate model is constructed using the extreme random forest algorithm to predict system coupling coefficients for different magnetic core structures. The predictive accuracy of the surrogate model is validated using a test dataset. Finally, combining the surrogate model with a multi-objective particle swarm optimization method, an optimization approach for the magnetic core structure of the rotary magnetic coupler is presented. This approach provides optimal magnetic core design solutions considering the usage of the magnetic core.
Simulation results indicate that the maximum error between the simulated coupling coefficient and the output results of the surrogate model is 0.001 38, with a maximum relative error of 0.161% and an average relative error of 0.096%. The parameter set based on this surrogate model decreases magnetic core volume by 32.15%. The volume of the magnetic core significantly decreases when the coupling coefficient is allowed to fluctuate during the design process of the magnetic core structure. When the coupling coefficient decreases by 1.74%, the volume of the magnetic core decreases by 66.63%. In the experiment, with the same energy efficiency design objectives, the proposed optimization method decreases the utilization volume of magnetic cores by 29.47% compared to traditional methods. The experimental setup achieves a power transmission of 3 kW with an efficiency of 97%. In addition, the rotary magnetic coupler designed in this paper maintains almost constant output power and efficiency under angular variation. Therefore, the rotary magnetic coupler exhibits stable output performance under rotational conditions.
The main contributions of this paper are as follows. (1) A surrogate model for the magnetic core structure and coupling coefficient of the rotary magnetic coupler is constructed based on extreme randomized trees (ERT), achieving an R² value of 0.999 65. This surrogate model accurately captures the nonlinear relationship between the magnetic core structure parameters and the coupling coefficient. (2) A magnetic core structure optimization method is proposed for rotary magnetic couplers, considering magnetic core usage volume and coupling coefficient, which effectively reduces the usage of magnetic cores and maintains the system's energy efficiency.

Key words： Wireless power transfer rotary magnetic coupler magnetic core structure optimization extreme random forest multiple objective particle swarm optimization

Received: 08 January 2024

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TM724

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	Feng Yuchen
	Sun Yue
	Deng Deqiang
	Hu Hongsheng
	Hu Han

Cite this article:

Feng Yuchen,Sun Yue,Deng Deqiang等. Optimization of the Core Structure for the Rotary Magnetic Coupler Based on Surrogate Model[J]. Transactions of China Electrotechnical Society, 2025, 40(4): 997-1008.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.240061 OR https://dgjsxb.ces-transaction.com/EN/Y2025/V40/I4/997

[1] 王旭东, 闫美存, 刘金凤, 等. 相对旋转时非接触式励磁系统磁罐变压器研究[J]. 中国电机工程学报, 2015, 35(22): 5915-5923.
Wang Xudong, Yan Meicun, Liu Jinfeng, et al.Transient analysis of contactless excitation systems with relative rotating potcore transformers[J]. Proceedings of the CSEE, 2015, 35(22): 5915-5923.
[2] 薛明, 杨庆新, 章鹏程, 等. 无线电能传输技术应用研究现状与关键问题[J]. 电工技术学报, 2021, 36(8): 1547.
Xue Ming, Yang Qingxin, Zhang Pengcheng, et al.Application status and key issues of wireless power transmission technology[J]. Transactions of China Electrotechnical Society, 2021, 36(8): 1547.
[3] 陈志鑫, 张献, 沙琳, 等. 基于频率调节的电动汽车无线充电互操作性提升方法研究[J]. 电工技术学报, 2023, 38(5): 1237-1247.
Chen Zhixin, Zhang Xian, Sha Lin, et al.Research on improving interoperability of electric vehicle wireless power transfer based on frequency adjustment[J]. Transactions of China Electrotechnical Society, 2023, 38(5): 1237-1247.
[4] 陈欣, 陈乾宏, 何广明. 强耦合条件下非接触滑环工作特性分析与控制[J]. 电力系统自动化, 2018, 42(23): 105-111.
Chen Xin, Chen Qianhong, He Guangming.Working characteristic analysis and control of contactless slipring system under strong coupling condition[J]. Automation of Electric Power Systems, 2018, 42(23): 105-111.
[5] 刘哲, 苏玉刚, 邓仁为, 等. 基于双边LC补偿的单电容耦合无线电能传输系统[J]. 电工技术学报, 2022, 37(17): 4306-4314.
Liu Zhe, Su Yugang, Deng Renwei, et al.Research on single capacitive coupled wireless power transfer system with double-side LC compensation[J]. Transactions of China Electrotechnical Society, 2022, 37(17): 4306-4314
[6] 蔡春伟, 姜龙云, 陈轶, 等. 基于正交式磁结构及原边功率控制的无人机无线充电系统[J]. 电工技术学报, 2021, 36(17): 3675-3684.
Cai Chunwei, Jiang Longyun, Chen Yi, et al.Wireless charging system of unmanned aerial vehicle based on orthogonal magnetic structure and primary power control[J]. Transactions of China Electrotechnical Society, 2021, 36(17): 3675-3684.
[7] 胡秀芳, 王跃, 吕双庆, 等. 基于谐波状态空间的无线电能传输系统建模和稳定性分析[J]. 电力系统自动化, 2022, 46(11): 121-130.
Hu Xiufang, Wang Yue, Lü Shuangqing, et al.Modeling and stability analysis of wireless power transfer system based on harmonic state space[J]. Automation of Electric Power Systems, 2022, 46(11): 121-130.
[8] Cai Chunwei, Wu Shuai, Jiang Longyun, et al.A 500W wireless charging system with lightweight pick-up for unmanned aerial vehicles[J]. IEEE Transactions on Power Electronics, 2020, 35(8): 7721-7724.
[9] Sofia A, Tavilla A C, Gardenghi R, et al.Power transfer for rotating medical machine[C]//Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2016: 2137-2140.
[10] Abdolkhani A, Hu A P, Nair N K C. A double stator through-hole type contactless slipring for rotary wireless power transfer applications[J]. IEEE Transactions on Energy Conversion, 2014, 29(2): 426-434.
[11] Xu Jiayi, Li Xingfei, Xie Ziming, et al.Design and analysis of inductively coupled power transfer system on mooring buoy with double ultracapacitor chargers using indirect control[J]. IEEE Transactions on Industrial Electronics, 2020, 67(6): 4836-4845.
[12] Wang Nan, Zhao Yifan, Li Chengfeng, et al.Design, manufacture, and experimental verification of contactless power supply coupler for rotary wireless sensor node of water-lubricated bearing[J]. IEEE Transactions on Instrumentation and Measurement, 2023, 72: 7507011.
[13] Song Kai, Ma Bingqing, Yang Guang, et al.A rotation-lightweight wireless power transfer system for solar wing driving[J]. IEEE Transactions on Power Electronics, 2019, 34(9): 8816-8830.
[14] 刘万刚, 宋述芳, 樊维超, 等. 模型替代方法在优化设计中的应用[J]. 中国工程机械学报, 2017, 15(2): 119-124.
Liu Wangang, Song Shufang, Fan Weichao, et al.Comparison of different metamodeling methods for optimization design[J]. Chinese Journal of Construction Machinery, 2017, 15(2): 119-124.
[15] 张邦富, 程明, 王飒飒, 等. 基于改进型代理模型优化算法的磁通切换永磁直线电机优化设计[J]. 电工技术学报, 2020, 35(5): 1013-1021.
Zhang Bangfu, Cheng Ming, Wang Sasa, et al.Optimal design of flux-switching permanent magnet linear machine based on improved surrogate-based optimization algorithm[J]. Transactions of China Electrotechnical Society, 2020, 35(5): 1013-1021.
[16] 龚夕霞, 李焱鑫, 卢琴芬. 模块化永磁直线同步电机考虑制造公差的推力鲁棒性优化[J]. 电工技术学报, 2024, 39(2): 465-474, 513.
Gong Xixia, Li Yanxin, Lu Qinfen.Thrust robustness optimization of modular permanent magnet linear synchronous motor accounting for manufacture tolerance[J]. Transactions of China Electrotechnical Society, 2024, 39(2): 465-474, 513.
[17] Lourenço J M, Lebensztajn L.Surrogate modeling and two-level infill criteria applied to electromagnetic device optimization[J]. IEEE Transactions on Magnetics, 2015, 51(3): 7000604.
[18] Wang Zhiyuan, Cui Shumei, Han Shouliang, et al.A novel magnetic coupling mechanism for dynamic wireless charging system for electric vehicles[J]. IEEE Transactions on Vehicular Technology, 2018, 67(1): 124-133.
[19] Cha H R, Park K R, Kim T J, et al.Design of magnetic structure for omnidirectional wireless power transfer[J]. IEEE Transactions on Power Electronics, 2021, 36(8): 8849-8860.
[20] Gu B S, Dharmakeerthi T, Kim S, et al.Optimized magnetic core layer in inductive power transfer pad for electric vehicle charging[J]. IEEE Transactions on Power Electronics, 2023, 38(10): 11964-11973.
[21] Geurts P, Ernst D, Wehenkel L.Extremely randomized trees[J]. Machine Learning, 2006, 63(1): 3-42.
[22] Kennedy J, Eberhart R.Particle swarm optimization[C]//Proceedings of ICNN'95-International Conference on Neural Networks, Perth, WA, Australia, 1995: 1942-1948.
[23] Coello Coello C A, Lechuga M S. MOPSO: a proposal for multiple objective particle swarm optimization[C]//Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02, Honolulu, HI, USA, 2002: 1051-1056.
[24] Han Honggui, Zhang Linlin, Yinga A, et al.Adaptive multiple selection strategy for multi-objective particle swarm optimization[J]. Information Sciences, 2023, 624: 235-251.
[25] Zhang Yiming, Kan Tianze, Yan Zhengchao, et al.Modeling and analysis of series-none compensation for wireless power transfer systems with a strong coupling[J]. IEEE Transactions on Power Electronics, 2019, 34(2): 1209-1215.