基于灰狼算法的无轴承永磁同步电机多目标优化

Multi-Objective Optimization of Bearingless Permanent Magnet Synchronous Motor Based on Grey Wolf Algorithm

为了降低无轴承永磁同步电机的悬浮脉动并提高电机的转矩,使其性能更加优越,提出了基于解析-灰狼算法对电机进行多目标优化设计。通过对比解析法和有限元法的计算结果,验证了解析法计算的准确性。将电机的气隙宽度、槽口宽度、极弧系数和永磁体厚度4个变量作为优化参数对电机进行多目标优化。对比优化前后的结果,电机的悬浮力脉动和转矩得到了明显的改善,验证了该算法的可行性。

In order to reduce the suspension force ripples and improve the torque of bearingless permanent magnet synchronous motor for better performance,a motor multi-objective optimization design method based on the analytical-grey wolf algorithm was proposed.By comparing the calculation results of the analytical method and the finite element method,the accuracy of the analytical method calculation was verified.The air gap width,permanent magnet thickness,pole arc coefficient and slot width were used as optimization parameters for multi-objective optimization of the motor.Comparing the results before and after optimization,the suspension force ripples and torque of the motor were significantly improved,which verified the feasibility of the algorithm.