Research on the Application of Genetic Algorithm in Improving the Torque Density of Permanent Magnet Synchronous Motor

The application of GA in the improvement of the maximum torque output capacity and the action density of PMSM is studied. The PM synchronous motor is widely used in many fields because of its high efficiency and high-power density. The basic structure parameters and high overload operation characteristics are analyzed. The key parameters of the motor are optimized by genetic algorithm, and the algorithm parameters are set in detail. The optimization procedure is designed. The ANSYS Maxwell and MATLAB are used to analyze and simulate the results. The results indicate that the maximum torque output of the optimized motor is increased by 30%, the efficiency is increased by 5%, and the other performance indexes are improved obviously. It is proved that GA has remarkable superiority in the optimization design of electric machine and can increase the action density effectively. The study provides an efficient way to design PMSM with high performance, and provides a basis for the future Mult objective optimization and actual application.