DESIGN OF THE PERMANENT MAGNET SYNCHRONOUS MOTOR USED IN ELECTRIC VEHICLES WITH THE HELP OF THE PARTICLE SWARM ALGORITHM AND ANSYS-MAXWELL

Abstract

Performance and efficiency are among the most important parameters in electric motors. Improvements to the engine not only increase engine performance, but also affect production costs. Permanent Magnet Synchronous Motor (PMSM) is a motor widely used in electric vehicles with its high torque density, high efficiency and production advantages. In this study, 110 kW (Adjust-Speed Permanent Magnet Synchronous Motor) AS-PMSM was designed for electric vehicle applications. The results of ANSYS-Maxwell and Particle Swarm Optimization (PSO) algorithms and the calculations of the optimized design were compared in line with the obtained data. In the design study, theoretical calculations, PSO algorithm and finite element method (FEM) based ANSYS-Maxwell software were used. Based on these values, the computer aided design of the engine was carried out. First of all, the basic design and performance criteria of the engine were determined. Parameters of the motor such as torque ripple, iron loss, efficiency and electromagnetic analysis were analyzed and optimized with ANSYS-Maxwell. Then, electrical, magnetic and performance analyzes of the motor were made. How the engine performance changes with the methods used has been examined in detail. Efficiency values were determined under various operating conditions in engine performance studies. The validity of the improvement study and the verification of the design study were examined by comparing the ANSYS results with the PSO algorithm results. The analysis results showed that the designed electric motor met the desired power values and design performance criteria.