The Application of Genetic Algorithm in the Structural Optimization of Permanent Magnet Synchronous Motor

Abstract

The objective and constraint conditions for the optimal design of permanent magnet synchronous motors (PMSM) are generally non-linear numerical functions and multi-extreme functions of design variables. It is difficult to obtain optimal design parameters. This paper has completed the compilation of the electromagnetic calculation program for the motor, and introduced the genetic algorithm into the optimization design program, and we specifically use the genetic algorithm to optimize the magnetization length of the permanent magnet, the width of the permanent magnet, the air gap and the pole arc coefficient in the motor, and the goal was set to obtain the maximum efficiency. From the results, the optimization effect is significant, which fully demonstrates that the genetic algorithm can effectively improve the efficiency of the permanent magnet synchronous motor and shorten the design cycle.