A computationally efficient multi-physics optimization technique for permanent magnet machines in electric vehicle traction applications

Abstract

This paper describes a computationally efficient optimization technique for permanent magnet machines in electric vehicle (EV) traction applications. It addresses multi-physics machine designs against driving cycles, including inverter-machine system energy efficiency, thermal behaviors and mechanical stress in rotor lamination. To drastically reduce computation time of repeated finite element analysis (FE) of the non-linear electromagnetic field and mechanical stress in permanent magnet machines especially interior permanent magnet machines (IPM), a set of analytical machine models characterized from FE calculations are developed which lead to significant reduction in computation time without compromising accuracy during an optimization. The proposed technique is applied to a multi-physics design optimization of an IPM machine for EV traction against 6-8 leading design parameters, and is validated by a series of tests on a prototype machine.