Design and Numerical Optimization for High-Performance IPM Synchronous Motor Using PSO Search Algorithm

This paper uses particle swarm search optimization (PSO) to improve the performance behavior of the interior permanent magnet synchronous permanent (IPMSM) motor. Because of their inherent advantages, permanent magnet synchronous motors are increasingly used in high-power applications, especially in electric vehicles. There are many ways to optimize motor design, especially from the rotor side, to have optimal geometric placement of the permanent magnet to improve performance. Also, we can reduce the PM costs and improve the motor’s performance. This paper improves IPMSM performance for high torque output capabilities using permanent magnets and a high saliency ratio to operate in a wide speed range. A multiobjective optimization with PSO search algorithms is performed to determine the magnets’ optimum size and position at the magnet’s highest drop rate. This design produced a better engine in the chassis than the original specification. The FEA method was used to check the accuracy of the results. Finally, we evaluate the regenerative rotor motor structure and validate the simulations.