基于GPR-PSO模型的永磁同步电机气隙磁密波形优化

Air-gap Flux Density Waveform Optimization of Permanent Magnet Synchronous Motor Based on GPR-PSO Model

为了使永磁同步电动机气隙磁密波形具有良好的正弦性,以气隙径向磁密波形的谐波畸变率为目标,磁钢的偏心距、极弧系数、磁钢厚度以及磁钢的充磁方向为因素变量进行优化。引进了正交实验设计的方法合理地安排了实验因素变量的搭配,利用有限元软件ANSYS Maxwell2D仿真分析得到数据样本集,采用了高斯混合回归模型(GPR)对数据样本集进行拟合,得到拟合回归模型。采用方差分析方法分析了各个因素对于谐波畸变率的影响的程度。将拟合回归函数作为适应度函数,通过粒子群算法(PSO)寻优,得到最优的磁钢参数。以一台48槽8极的永磁同步电动机为例进行仿真实验,结果表明,通过GPR-PSO模型的方法可以有效降低永磁同步电机的气隙磁密波形畸变率,使波形得到良好的改善。

In order to obtain good sinusoidal waveform of air-gap flux density of permanent magnet synchronous motor,this paper takes harmonic distortion rate of axial air-gap flux density waveform as a target to optimize factor variables such as eccentric distance,pole-arc coefficient,thickness and magnetization direction of magnetic steel.The orthogonal experiment design method is introduced to rationally arrange the collocation of experimental factor variables.The simulation analysis is carried out by ANSYS Maxwell 2D finite-element software to get the data sample set.The data sample sets are fitted by Gaussian process regression（GPR） to obtain the fitted regression model.Variance analysis method is adopted to analyze the influence degree of various factors on harmonic distortion rate.Taking the fitted regression function as the fitness function,the particle swarm optimization（PSO） is used to find optimal magnetic steel parameters.Taking a 48-slot 8-pole permanent magnet synchronous motor as an example,the simulation experiment is carried out.The simulation result shows that GPR-PSO algorithm can effectively reduce distortion rate of air-gap flux density waveform of permanent magnet synchronous motor and well improve the waveform.