In order to reduce the thrust ripple caused by the detent force and improve the thrust capacity of the permanent magnet linear synchronous motor (PMLSM), a flat‐type PMLSM is taken as the study object to globally optimize the motor parameters. Firstly, an analytical model for PMLSM is established. The end effect force based on the virtual displacement principle and the cogging force using the equivalent air gap length are considered when analyzing the model. The detent force is found that closely related to the relative position of the primary and secondary, the end air gap volume and the equivalent air gap length. Then, a motor structure optimization method based on parameter classification is proposed in this paper. By sensitivity analysis, the parameters are divided into two types. For parameters with high sensitivity, the response surface methodology (RSM) is used to establish the second‐order regression equation between parameters and response, and then these parameters are optimized by the multi‐population genetic algorithm (MPGA) to improve thrust capacity and reduce thrust ripple. The optimal values of parameters with low sensitivity are obtained by the parametric search. Finally, the optimized motor is used to predict its thrust performance by the finite element method (FEM). The prediction results show that the optimized motor not only performs better but also improves the design efficiency through parameter classification. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.
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