摘要
研究了单绕组磁悬浮开关磁阻电机电磁特性和结构优化设计方法。通过有限元分析计算得到电机悬浮力与结构参数的一般关系,以此选择定、转子极弧作为优化参数,并采用极限学习机构建优化模型,以提高悬浮力输出为目标,选用粒子群算法进行寻优。通过对比仿真结果表明所提算法的精度高、回归速度快,能够准确地寻取最优解。
The electromagnetic performance and optimization design method of a single winding bearingless switched reluctance motor( BSRM) were studied. The general relationship between the radial force and structure parameters were given based on finite element method( FEM). Accordingly,the stator pole arc and rotor pole arc were selected as the optimization parameter and the extreme learning machine( ELM) was used to build the optimization model. Besides,the particle swarm optimization( PSO) algorithm was used to search for the optimal solutions. Finally,the comparative simulation results had proved that the proposed method had high precision and fast regression speed,and the accurate optimal solutions had been achieved.
引文
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