Multi-Physics Design and Optimization of Electric Motors for a Traction Application

Abstract

This thesis presents a comprehensive study on the multiphysics design and optimization of electric motors specifically tailored for traction applications in electric vehicles (EVs). The research aims to investigate various motor types, including Permanent Magnet Synchronous Motor (PMSM), Permanent Magnet-assisted Synchronous Reluctance Motor (PMa-SynRM), Induction Motor (IM) with copper rotor bars, and Electrically Excited Synchronous Motor (EESM).

The purpose of this research is to identify and propose optimal electric motor configurations through a multiphysics optimization workflow. This approach incorporates finite element analysis (FEA), sensitivity analysis, and genetic algorithm-based optimization. By applying this methodology, the performance, efficiency, and suitability of the motors are systematically evaluated for an EV traction application.

The proposed optimization methods aim to achieve significant improvements in critical performance parameters, including electromagnetic efficiency, torque density, mechanical robustness, thermal management, and Sound Power Level (SPL). The impact of pulse-width-modulation switching has also been considered in the analysis.