A two-stage optimization method for the design of a permanent magnet synchronous motor is presented. The method combines interactivity, an evolutionary optimization algorithm, and a two-stage approach, enabling the generation of both a set of Pareto-optimal solutions in the relevant design space region and a unique optimal solution determined by a weighted criterion. The models used to calculate target values are selected based on criteria for maximizing the reliability of results and minimizing computation time. This approach enables the construction of a Pareto frontier and the determination of an optimal solution that meets requirements and constraints within two to three days on a single modern PC. Furthermore, the obtained characteristics remain unchanged after verification using more computationally intensive models. The developed method significantly improved the performance of an electric motor previously developed using a conservative iterative approach.
Shapovalov et al. (Mon,) studied this question.