Variance-based Robust Optimization of a Permanent Magnet Synchronous Machine

TL;DR

This paper introduces a variance-based robust optimization method for designing permanent magnet synchronous machines, effectively reducing torque ripple and losses by accounting for material uncertainties through stochastic analysis.

Contribution

It combines variance-based sensitivity analysis with topology optimization and polynomial chaos expansion to improve the robustness of PMSM design under material uncertainties.

Findings

Reduced torque ripple and electromagnetic losses in the optimized design

Validated approach through 2D simulations confirming effectiveness

Proposed a novel topology for PMSM with enhanced robustness

Abstract

This paper focuses on the application of the variance-based global sensitivity analysis for a topology derivative method in order to solve a stochastic nonlinear time-dependent magnetoquasistatic interface problem. To illustrate the approach a permanent magnet synchronous machine has been considered. Our key objective is to provide a robust design of the rotor poles and of the tooth base in a stator for the reduction of the torque ripple and electromagnetic losses, while taking material uncertainties into account. Input variations of material parameters are modeled using the polynomial chaos expansion technique, which is incorporated into the stochastic collocation method in order to provide a response surface model. Additionally, we can benefit from the variance-based sensitivity analysis. This allows us to reduce the dimensionality of the stochastic optimization problems, described by the random-dependent cost functional. Finally, to validate our approach, we provide the two-dimensional simulations and analysis, which confirm the usefulness of the proposed method and yield a novel topology of a permanent magnet synchronous machine.