An Evolutional Topology Optimization of Electric Machines for Local Shape Modification and Visualization of Sensitivity Distribution Based on CMA-ES

This paper presents an evolutional topology optimization of electric machines, which works like gradient-based local search methods, based on the covariance matrix adaptation evolution strategy (CMA-ES). The present method enables to improve the performance of initial machine shapes without computing the deviation of the objectives. Moreover, for the resultant shapes obtained by the present topology optimization method, this paper also presents a sensitivity analysis method based on the normal distribution which is used to seek for solutions in CMA-ES. Using the present sensitivity analysis method, important parts which contribute to improve a machine characteristic can be visualized. The two present methods are applied to the optimization problem of a synchronous reluctance motor. It is shown that initial rotor shapes defined by designers can effectively be modified using the present optimization method. Moreover, it is also shown that the sensitivity distributions with respect to some machine characteristics are visualized by the present method. In addition, each machine characteristic is respectively improved by modifying the machine shape according to the respective sensitivities. (c) 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.