A New Surrogate-assisted Robust Multi-objective Optimization Algorithm for an Electrical Machine Design

Abstract

For a multi-objective optimization problem applied to the electric machine design, a new surrogate-assisted robust algorithm is proposed in this research. The proposed algorithm can find a robust and well-distributed Pareto front set rapidly and precisely for robust nondominated solutions using a surrogate model and an uncertainty consideration with a worst-case scenario. The outstanding performances of the proposed algorithm are verified by test functions. Furthermore, through the application of the optimal design process of a surface-mounted permanent magnet synchronous motor for an electric bicycle, the feasibility of this algorithm is verified.