Multi-Objective Optimization of High-Speed Permanent Magnet Synchronous Motor Based on Multi-Physical Field Coupling

High-speed permanent magnet synchronous motors (HSPMSMs) possess distinct attributes, including high frequency, high rotational speed, and high loss density. Thus, in-depth research on each parameter’s optimization is crucial to attain maximum performance and reliability. Based on the mechanism of multi-physical field coupling (MPFC), this paper discusses an experimental design method for optimizing a 60,000 rpm, 30 kW motor through multi-objective optimization based on generalized sample space. Special attention is paid to multi-physical field factors such as motor loss, rotor dynamics, and cogging torque. The results demonstrate a considerable improvement in the motor’s performance, including its “goodness” function and cost. Furthermore, the uniform design (UD) method utilizing a genetic algorithm demonstrates high efficiency. Ultimately, the experiment gauging performance and motor temperature rise confirmed a maximum error of 4.2% between simulated and measured results, demonstrating the optimization algorithm’s accuracy in multi-physical field coupling scenarios.