关键词: 低速大转矩, 同步电机, 粒子群优化算法, 温度场, 冷却系统设计

Abstract: In response to the national energy conservation strategy and the lightweight upgrading demands of industrial equipment,an optimization design method based on Kriging surrogate model combined with multi-objective particle swarm optimization algorithm was proposed to solve the problems of low energy efficiency grade and large electromagnetic mass of existing low-speed high-torque synchronous motors. A finite element model of the motor was established. Taking efficiency, electromagnetic mass and torque as optimization objectives,and no-load back electromotive force,stator tooth flux density and stator yoke flux density as constraint conditions,multi-objective optimization design was carried out. Latin hypercube sampling method was adopted to obtain sample data, and key optimization variables were selected through sensitivity analysis. A
surrogate model was constructed based on sampling data,and the model accuracy was verified by determination coefficient. The multi-objective particle swarm optimization algorithm was used for multi-objective optimization to obtain the global optimal solution set,and the optimal parameter combination was realized. Simulation results show that the comprehensive performance of the optimized motor was significantly improved. The aiming at the high temperature problem caused by the increased power density of the optimized motor,a water-cooled cooling system was designed,and the temperature field verification analysis of the motor was conducted. The proposed optimization method is proven to be effective based on the simulation results.

Key words: low-speed high-torque, synchronous motor, particle swarm optimization algorithm, temperature field, cooling system design