대용량 BLDC 전동기의 영구자석 형상 최적화를 통한 최적화 기법 연구

Abstract

This paper presents a response surface method(RSM) with Latin Hypercube Sampling strategy, which is employed to optimize a magnet pole shape of large scale BLDC motor to minimize the cogging torque. The proposed LHS algorithm consists of the multi-objective Pareto optimization and (1+1) evolution strategy. The algorithm is compared with the uniform sampling point method in view points of computing time and convergence. In order to verify the developed algorithm, a 6 MW BLDC motor is simulated with 4 design parameters (arc length and 3 variables for magnet) and 4 constraints for minimizing of the cogging torque. The optimization procedure has two stages; the fist is to optimize the arc length of the PM and the second is to optimize the magnet pole shape by using the proposed hybrid algorithm. At the 3rd iteration, an optimal point is obtained, and the cogging torque of the optimized shape is converged to about 14% of the initial one. It means that 3 iterations aregood enough to obtain the optimal design parameters in the program.