Robust Multilevel Optimization of PMSM Using Design for Six Sigma

Abstract

In this paper, a robust optimization method based on design for six sigma (DFSS) is combined to the optimization of a surface mounted permanent synchronous machine (PMSM) by using multilevel genetic algorithm (MLGA). First, MLGA and DFSS are introduced in the robust optimization. Second, by taking into account the tolerances of the motor products, important input parameters could be varied with six sigma distribution and Monte Carlo simulation (MCS) method is used to reduce the calculation cost. Third, to verify the new algorithm, the presented algorithm is applied to the optimization of a PMSM. The results compared with those of traditional GA and MLGA and the discussion of the robust optimization combined with MLGA are presented.