基于响应面模型与遗传算法的无轭分块电枢轴向磁场永磁电机齿槽转矩优化

无轭分块电枢轴向磁场永磁电机（Yokeless and Segmented Armature Machine，YASA）是一种高功率密度、高效率的电机，适于电牵引驱动特别是电动车的轮毂和轮边直驱。本文针对基于软磁复合材料（SMC）的YASA电机的齿槽转矩进行研究。首先比较了基于SMC和叠压硅钢材料的YASA电机齿槽转矩波形，然后分析了永磁体极弧系数、永磁体斜极、定子齿靴宽度系数以及定子齿靴偏移对基于SMC的YASA电机齿槽转矩的影响，在此基础上建立响应面模型并利用遗传算法对齿槽转矩进行优化，最后，通过3-D FEM验证了优化结果的准确性。结果表明，在选取一定极弧系数的前提下，存在最优的永磁体斜极角度、定子齿靴宽度系数和定子齿靴偏移角度组合能够使电机的齿槽转矩降为最小，且优化前后电机的其他性能基本保持不变。

Optimization of cogging torque of yokeless and segmented armature machine based on response surface model and genetic algorithm

Yokeless and segmented armature (YASA) machine is a high-power density, high-efficiency motor, suitable for electric traction drive especially electric vehicle hub and wheel edge direct drive. In this paper, the cogging torque of YASA motor based on soft magnetic composite is studied. The cogging torque waveform based on SMC and laminated silicon steel material is first compared. Then, the influence of magnet pole-arc ratio, magnet skewing, stator shoe width ratio and stator tooth, and stator shoe shifting on cogging torque is analyzed, based on this, the response surface model is established and the genetic algorithm is used to optimize the cogging torque. Finally, the accuracy of the optimization results is verified by 3-D FEM. The results show that the optimum angle of the magnet, the width ratio of the stator shoe and the shifting angle of the stator shoe can minimize the torque of the motor, and the other performance of the motor before and after the optimization is basically unchanged