Shape optimization of an electric motor subject to nonlinear magnetostatics

TL;DR

This paper presents a shape optimization approach for an electric motor's rotor iron core to improve its rotation smoothness, employing nonlinear magnetostatics modeling and a novel shape sensitivity analysis.

Contribution

It introduces a new shape-Lagrangian formulation for nonlinear magnetostatics and applies it to optimize electric motor performance.

Findings

Successful formulation of a shape optimization problem for rotor geometry

Development of a rigorous shape sensitivity analysis for nonlinear magnetostatics

Potential for improved motor performance through geometry modification

Abstract

The goal of this paper is to improve the performance of an electric motor by modifying the geometry of a specific part of the iron core of its rotor. To be more precise, the objective is to smooth the rotation pattern of the rotor. A shape optimization problem is formulated by introducing a tracking-type cost functional to match a desired rotation pattern. The magnetic field generated by permanent magnets is modeled by a nonlinear partial differential equation of magnetostatics. The shape sensitivity analysis is rigorously performed for the nonlinear problem by means of a new shape-Lagrangian formulation adapted to nonlinear problems.