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.

中文翻译：

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平板式永磁直线同步电机制动力分析及基于参数分类的多目标优化

为了减小制动力引起的推力脉动，提高永磁直线同步电机（PMLSM）的推力能力，以扁平型PMLSM为研究对象，对电机参数进行全局优化。首先，建立了PMLSM的分析模型。在分析模型时，考虑了基于虚拟位移原理的端部效应力和使用等效气隙长度的齿槽力。发现制动力与初级和次级的相对位置、端部气隙体积和等效气隙长度密切相关。然后，本文提出了一种基于参数分类的电机结构优化方法。通过敏感性分析，将参数分为两类。对于灵敏度高的参数，采用响应面法（RSM）建立参数与响应之间的二阶回归方程，然后通过多种群遗传算法（MPGA）对这些参数进行优化，以提高推力能力，减少推力脉动。通过参数搜索获得低灵敏度参数的最优值。最后，利用有限元法（FEM）对优化后的电机进行推力性能预测。预测结果表明，优化后的电机不仅性能更好，而且通过参数分类提高了设计效率。© 2022 日本电气工程师学会。由 Wiley Periodicals LLC 出版。然后通过多种群遗传算法（MPGA）对这些参数进行优化，以提高推力能力并减少推力波动。通过参数搜索获得低灵敏度参数的最优值。最后，利用有限元法（FEM）对优化后的电机进行推力性能预测。预测结果表明，优化后的电机不仅性能更好，而且通过参数分类提高了设计效率。© 2022 日本电气工程师学会。由 Wiley Periodicals LLC 出版。然后通过多种群遗传算法（MPGA）对这些参数进行优化，以提高推力能力并减少推力波动。通过参数搜索获得低灵敏度参数的最优值。最后，利用有限元法（FEM）对优化后的电机进行推力性能预测。预测结果表明，优化后的电机不仅性能更好，而且通过参数分类提高了设计效率。© 2022 日本电气工程师学会。由 Wiley Periodicals LLC 出版。优化后的电机用于通过有限元法 (FEM) 预测其推力性能。预测结果表明，优化后的电机不仅性能更好，而且通过参数分类提高了设计效率。© 2022 日本电气工程师学会。由 Wiley Periodicals LLC 出版。优化后的电机用于通过有限元法 (FEM) 预测其推力性能。预测结果表明，优化后的电机不仅性能更好，而且通过参数分类提高了设计效率。© 2022 日本电气工程师学会。由 Wiley Periodicals LLC 出版。