Robust Optimization of High-Speed PM Motor Design

This paper proposes a robust optimization algorithm, enabling global optimum tracking and manufacturing uncertainty factors handling, for high-speed permanent magnet motor design. A new robustness criterion is introduced, considering effectively the impact of the construction tooling uncertainties on the design variables in all objectives. An adaptive-network-based fuzzy inference system is adopted acting as a surrogate for the time-consuming finite-element (FE) analyses and results in computationally fast robust electric machine design procedure. The procedure has been validated through FE high-speed motor design.