Multi-objective optimization design of inset-surface permanent magnet machine considering deterministic and robust performances

Abstract

The inset-surface permanent magnet (ISPM) machine can achieve the desired electromagnetic performance according to the traditional deterministic design. However, the reliability and quality of the machine may be affected by the essential manufacturing tolerances and unavoidable noise factors in mass production. To address this weakness, a comprehensive multi-objective optimization design method is proposed, in which robust optimization is performed after the deterministic design. The response surface method is first adopted to establish the optimization objective equation. Afterward, the sample points are obtained via Monte Carlo simulation considering the design-variable uncertainty. The Design for Six Sigma approach is adopted to ensure the robustness of the design model. Furthermore, the barebones multi-objective particle swarm optimization algorithm is used to obtain a compromise solution. A prototype is manufactured to evaluate the effectiveness of the proposed method. According to the finite-element analysis and experimental tests, the electromagnetic performance and reliability of the machine are significantly enhanced with the proposed method.