Shape optimization of a large-scale BLDC motor using an adaptive RSM utilizing design sensitivity analysis

Abstract

This paper proposes a new algorithm for the shape optimization of a large-scale brushless dc (BLDC) motor to reduce the cogging torque. In the algorithm, an adaptive response surface method (RSM) using the multiquadric radial basis function is employed to interpolate the objective function in design parameter space, and incorporated with (1 + 1) evolution strategy to find an optimal point. In the adaptive RSM, an adaptive sampling point insertion method is developed utilizing the design sensitivities computed by using the finite-element method to get a reasonable response surface with a relatively small number of sampling points. The developed algorithm is applied to the shape optimization of a 5-MW BLDC motor, and the cogging torque was reduced to 17% of the initial one.