摘要
齿槽转矩会引起电机振动和噪声。为减小电机齿槽转矩,对电机极弧系数、偏心距、气隙长度以及磁极厚度进行了优化。首先利用有限元分析软件建立电机模型,然后设计25组正交实验得到算法所需样本空间,并基于支持向量机算法建立了目标函数数学模型,最后通过粒子群算法进行寻优,得到了一组减小齿槽转矩的优化方案。仿真结果表明,优化后的电机齿槽转矩得到了明显的削弱,优化算法是可行的。
The cogging torque in permanent magnet synchronous motor（PMSM） causes the noise and vibration.The pole-arc coefficient,polar arcs eccentricity,length of air gap and thickness of pole were optimized to decrease the cogging torque.Firstly the motor model was built by using the finite element analysis software,after that 25 sets of orthogonal tests were designed to acquire the sample space needed by the algorithm.Then the mathematical model of the object function was built based on the support vector machine（SVM） algorithm.Finally,the parameters were optimized by particle swarm optimization（PSO） algorithm.The simulating results show that the optimized cogging torque has been significantly reduced,and the optimization algorithm is feasible.
出处
《微特电机》
北大核心
2014年第4期11-13,17,共4页
Small & Special Electrical Machines
基金
国家自然科学基金资助项目(60971037)
关键词
齿槽转矩
支持向量机
粒子群算法
正交实验
永磁同步电动机
cogging torque
support vector machine （SVM）
particle swarm optimization （PSO）
orthogonal test
permanent magnet synchronous motor
