Design and Multi-Objective Optimization for Improving Torque Performance of a Permanent Magnet-Assisted Synchronous Reluctance Motor

Abstract

Permanent magnet-assisted synchronous reluctance motors (PMA-SynRMs) are widely used in various industries as a relatively inexpensive and high-performance energy conversion device. The model proposed in this article relies on a magnetic pole-biased permanent magnet synchronous reluctance motor with a magnetic focusing effect. Two types of models with Halbach array and magnetic focusing effect have been proposed, which increase excitation and make the internal magnetic circuit of the rotor more saturated, thereby achieving higher electromagnetic torque. Through finite element simulation analysis and verification, the motor characteristics of the basic and proposed permanent magnet-assisted synchronous reluctance motor were calculated, including the air gap flux density and back electromotive force (EMF) in no-load analysis, as well as the average torque, torque ripple, and efficiency in load analysis. In addition, multi-objective optimization was also conducted on the rotor topology structure of proposed model two, using the uniform Latin hypercube sampling method to uniformly sample the data samples and the Pearson correlation coefficients to perform a sensitivity analysis on the data. The pilOPT multi-objective autonomous optimization algorithm was used to perform multi-objective autonomous optimization on parameters with high correlation, and the best-found solution based on the Pareto front was selected. Compared with proposed model two, the average torque of the optimized model increased by 18.14%, the efficiency increased by 1.05% and the torque ripple decreased by 5.22%. Finally, the anti-demagnetization performance of the optimized model’s permanent magnet was analyzed.