Robust design optimization taking into account manufacturing uncertainties of a permanent magnet assisted synchronous reluctance motor

TL;DR

This paper presents a robust design optimization method for a permanent magnet assisted synchronous reluctance motor that accounts for manufacturing uncertainties, leading to improved mean torque, reduced torque ripple, and enhanced robustness.

Contribution

It introduces a robust optimization approach using surrogate models to improve motor performance and robustness against manufacturing uncertainties.

Findings

Robust designs achieved better mean torque and torque ripple performance.

Robust optimization improved the motor's robustness to manufacturing uncertainties.

Surrogate models effectively facilitated the optimization process.

Abstract

In this paper, deterministic and robust design optimizations of a permanent magnet assisted synchronous reluctance machine were performed to increase its mean torque while reducing torque ripple. These optimizations were carried out using a surrogate model based on 2-D finite element simulations. The results of the robust optimizations, which considered manufacturing uncertainties, were compared to the deterministic optimization. The robust designs have shown not only good mean torque and torque ripple performances, but they have also shown improved robustness against design parameters uncertainties.