基于等效磁路的PMECD变种群规模遗传多目标优化设计

基于等效磁路模型,提出了一种使用引入死亡和战争因素的变种群规模遗传算法进行永磁涡流驱动器的多目标优化设计的方法.首先建立磁场分析模型,推导关键参数的解析表达式.在此基础上,以永磁体厚度、极弧系数、铜盘厚度以及永磁体个数为变量,以输出转矩、转动惯量和驱动器体积为优化目标,提出了基于熵值权重的永磁驱动器多目标优化函数,然后应用引入死亡和战争因素的变种群规模遗传算法来优化结构尺寸.优化结果得到了实验以及有限元仿真的验证,并且与其他算法进行了比较.结果表明,相比其他优化算法,该基于解析模型的变种群规模遗传算法在结构参数优化设计中有很好的计算效果.

A Multi-objective VPGA for Optimization Design of PMECD Based on Equivalent Magnetic Circuit Model

Based on equivalent magnetic circuit model， an optimum design method of permanent magnet eddy current driver (PMECD) was proposed by the variable population-size genetic algorithm (VPGA) which taken death and war factors into account. Firstly， analytical model was built and the analytical formulas of key parameters were deduced. On this basis， by using permanent magnet thickness， pole-arc coefficient， copper plate thickness and the number of permanent magnets as variables and taking output torque， rotational inertia and the volume of the driver as optimization goals， a multi-objective optimization function with entropy coefficients and the VPGA were proposed to optimize parameters structure of the driver. The validity and feasibility of the proposed method were proved by finite element analysis and experimental results. The results confirm that compared with other two optimization algorithms， optimization design result by the VPGA based on the analytical model has good effect on optimization of structural parameters.