Ultra-High-Dimensional Multi-Level Optimization Strategies for Electrical Machines

Abstract

Electrical machine optimization is normally a high-dimensional nonlinear multi-objective optimization problem. To improve the efficiency, multi-level optimization strategy is currently used, where sensitivity analysis is required for dividing design parameters into different groups. However, the conventional multi-level optimization strategy cannot handle ultra-high-dimensional optimization problems. To attempt this challenge, this paper proposes a sensitivity analysis method with variable weighted intervals to calculate the sensitivity coefficient in the parameter design range. Three improved multi-level optimization strategies based on different optimization algorithms and sequential sensitivity strategy are proposed, analyzed, and compared with the conventional multi-level optimization strategy. Through a case study of a synchronous reluctance machine, it can be seen that the proposed optimization strategies can improve the optimization results and efficiency of ultra-high-dimensional optimization of electrical machines.