飞轮储能用永磁同步电机气隙磁通密度波形优化

Optimization of air gap flux density waveform of permanent magnet synchronous motor for flywheel energy storage

为了优化气隙磁通密度波形的幅值与正弦畸变率2个关键指标,提出了一种基于Kriging模型与差分进化算法(differential evolution algorithm,DEA)相结合的多目标优化方法。首先,通过对飞轮储能用永磁同步电机(permanent magnet synchronous motor for flywheel energy storage,FPMSM)有限元模型进行拉丁超立方体采样(Latin hypercube sampling,LHS),取得样本数据,并引入Kriging算法建立对应的替代模型;其次,利用DEA对影响气隙磁通密度波形的关键结构参数进行全局优化,给出Pareto最优解;最后,对Pareto最优解集的3种优化方案与原始方案进行对比分析和有限元验证。结果表明,所提FPMSM气隙磁通密度波形多目标优化方法能够使气隙磁通密度波形在幅值提高的同时,正弦畸变率显著降低。

In order to optimize the amplitude and sinusoidal distortion rate of air gap flux density waveform,a multi-objective optimization method based on Kriging model and differential evolution algorithm(DEA)is proposed.Firstly,the sample data are obtained by Latin hypercube sampling(LHS)of the finite element model of permanent magnet synchronous motor for flywheel energy storage(FPMSM),and the Kriging algorithm is introduced to establish the corresponding alternative model.Secondly,the DEA is used to globally optimize the key structural parameters affecting the air gap flux density waveform,and the Pareto optimal solution is given.Finally,the three optimization schemes of Pareto optimal solution set are compared with the original scheme and are verified by the finite element method.The results show that the proposed multi-objective optimization method of air gap flux density waveform of FPMSM can elevate the amplitude of air gap flux density waveform and significantly reduce the sinusoidal distortion rate.