为了提高永磁同步电机（PMSM）的性能，选取磁钢厚度、偏心距和极弧系数作为变量，优化电机的齿槽转矩和气隙磁密畸变率。首先通过正交设计法仿真获得各变量的样本空间，然后采用支持向量机(SVM)对仿真数据集进行拟合，得到齿槽转矩和空载气隙磁密畸变率的拟合模型，最后应用多目标文化差分进化（MOCDE）算法进行优化。以一台48槽8极的PMSM为例进行仿真验证，分析结果表明基于SVM的模型准确可靠，结合MOCDE算法能有效优化齿槽转矩和气隙磁密畸变率。

In order to improve the performance of permanent magnet synchronous motor (PMSM), the magnetic steel thickness, eccentric distance and pole arc coefficient are selected as variables to optimize the cogging torque and air-gap magnetic density distortion rate of the motor. Firstly, the sample space of each variable is obtained through orthogonal design method simulation. Secondly the support vector machine (SVM) is used to fit the simulation data set to obtain the fitting model of cogging torque and no-load air gap magnetic density distortion rate. Finally, multi-objective cultural differential evolution (MOCDE) algorithm is used to optimize the model. A 48-slot 8-pole PMSM is taken as an example for simulation verification. The simulation results show that the model based on SVM is accurate and reliable, and combined with MOCDE algorithm, it can effectively optimize the cogging torque and air-gap magnetic density distortion rate.