Abstract：Global optimization of motor based on finite element method and modern metaheuristic optimization algorithm is computationally expensive. The surrogate-based optimization (SBO) algorithm is an effective method for expensive optimization. SBO algorithm uses infill criterion to balance local exploitation and global exploration, which will lead to global optimal result. An improved SBO algorithm is proposed in this paper, in which new infill criterion is adopted. The parallel computing is also applied to reduce optimization cycles further. Numerical experiments on test functions validate the effectiveness of the proposed SBO algorithm. A flux-switching permanent magnet linear machine is optimized with the proposed algorithm. A prototype is also used to validate the effectiveness of the simulation and algorithm.
张邦富, 程明, 王飒飒, 王伟. 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, Wang Wei. Optimal Design of Flux-Switching Permanent Magnet Linear Machine Based on Improved Surrogate-Based Optimization Algorithm. Transactions of China Electrotechnical Society, 2020, 35(5): 1013-1021.
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2020, Vol. 35 
