Research on the Optimization of Asynchronous Motor Slot Type Aiming at Efficiency

Three-phase asynchronous motors are widely used in the industrial field due to their simple structure, high reliability, strong adaptability, low cost, and easy control of weak magnetism. Motor optimization can improve motor performance, efficiency, and reliability, thereby achieving lower energy consumption. By combining the finite element method, initial three-phase asynchronous motor models are established and simulated using both Python and Ansys Maxwell software. With the aid of Genetic Algorithm, the optimization target is to reduce losses, with stator and rotor slot parameters as variables. The stator and rotor slot dimensions are optimized simultaneously. The motor models before and after optimization in Python and Ansys Maxwell are compared, and the results show that the energy loss of the motor after slot optimization is reduced by 29.17%, and the motor efficiency performance is improved, verifying the effectiveness of the induction motor slot optimization design method based on genetic algorithms.