Optimization on Magnetization-Regulation Performance of a Variable-Flux Machine with Parallel Permanent Magnets

Abstract

Variable-flux machine (VFM) is a promising candidate for wide-speed-range applications, such as electric vehicle, numerical control machine and railway traction. Magnetization-regulation range, which is the ratio of back electromotive forces at forward and reverse magnetization states, is an important performance of VFM. In this paper, the magnetization-regulation performance of a parallel VFM with flux barrier is analyzed, and the influences of magnetization current, split ratio, the geometries of PM pole, and the position and shape of flux barrier on the magnetization-regulation range of VFM are investigated. The best magnetization angle of VFM is explored, and a control method of forward magnetization is proposed. With the sample data obtained by finite element method, Kriging surrogate model of VFM is established to save optimization time, which is proven with good accuracy. The particle swarm optimization algorithm is utilized for optimizing the forward magnetization effect of VFM, and the optimal scheme is obtained, whose average flux density of AlNiCo PM at forward magnetization state is increased to 1.151T. The improvement measures and optimization method applied in this paper are proven effective in improving magnetization-regulation performance.