VSSystem-Level Optimization of Electric Vehicle Powertrains: Comparative Analysis of PMSM, PMaSynRM, and Induction Machine Technologies

Abstract

The rapid growth of electric vehicles (EVs) has increased the demand for highly efficient, cost-effective, and sustainable powertrain solutions. Traditional powertrain design approaches often optimize individual components independently, resulting in suboptimal system-level performance. This study presents a comprehensive system-level optimization methodology for EV powertrains incorporating electrical machines, power electronic converters, and mechanical transmissions. Three traction machine technologies—Permanent Magnet Synchronous Machines (PMSM), Permanent Magnet-assisted Synchronous Reluctance Machines (PMaSynRM), and Induction Machines (IM)—were modeled and evaluated using electromagnetic, thermal, efficiency, and cost models. Finite Element Method (FEM)-based simulations were employed to generate machine databases, while analytical models were used for thermal analysis, power electronics, transmission losses, and manufacturing cost estimation. The proposed optimization framework minimizes both investment and operational costs while satisfying vehicle performance requirements. Results demonstrate that PMSM-based powertrains provide superior efficiency and energy consumption performance, whereas IM systems offer lower material costs and PMaSynRM configurations present a balanced compromise between cost and rare-earth material dependency. The proposed methodology enables informed decision-making during EV powertrain design and provides a robust platform for future multi-objective optimization studies.

Keywords: Electric Vehicle, Powertrain Optimization, PMSM, PMaSynRM, Induction Machine, System-Level Design