磁悬浮开关磁阻电机建模与参数优化设计

Modeling and parameters optimal design of bearingless switched reluctance motor

针对磁悬浮开关磁阻电机参数设计问题,提出一种基于最小二乘支持向量机与粒子群优化算法的电机结构参数优化设计方法。采用三维有限元仿真建立样本空间,构建悬浮力、电磁转矩与绕组间互感的最小二乘支持向量机非参数模型;并基于该非参数模型,选择满足额定电磁转矩为约束条件,悬浮力最大且绕组间互感最小为优化目标,采用粒子群优化算法获取电机的最优结构参数。仿真结果表明:最小二乘支持向量机非参数模型精确度高,采用该优化设计方法设计的磁悬浮开关磁阻电机具有悬浮承载力强、耦合小、易于控制的优点,并且该优化设计方法算法简单、操作方便。

For the parameters design of bearingless switched reluctance motor（BSRM）,a structure parameters＇ optimal design method was proposed based on the least squares support vector machine（LSSVM） and the particle swarm optimization（PSO）.It obtained sample space by 3D finite element simulation and then built LSSVM nonparametric models of radial levitation force,torque and mutual inductance.Based on these models,it chose rated torque reached as constraint condition,and selected maximal radial levitation force,minimal mutual inductance as optimal objective.And then,the optimal parameters of BSRM were obtained by PSO searching.The simulation results prove that the LSSVM nonparametric models have high accuracy and the optimized motor has strong suspension bearing capacity,weak coupling,and simple control by simple and handy arithmetic.