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Parameter Sensitivity Analysis and Robust Design Approach for Flux-Switching Permanent Magnet Machines

Author

Listed:
  • Gan Zhang

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China)

  • Qing Tong

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China)

  • Anjian Qiu

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China)

  • Xiaohan Xu

    (Maintenance Branch Company, State Grid Jiangsu Electric Power Co., Ltd., Nanjing 211102, China)

  • Wei Hua

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China)

  • Zhihong Chen

    (Beijing Institute of Precision Mechatronics and Controls, Beijing 100076, China)

Abstract

Parameter sensitivity analysis is usually required to select the key parameters with high sensitivity to the optimal goal before the optimization is carried out, especially for flux-switching permanent magnet (FSPM) machines where lot of design parameters should be considered. Unlike the traditional studies on parameter sensitivity, which are generally experience- or statistics-based, and are time-consuming, this paper proposes a parameter sensitivity analysis method of a FSPM machine based on a magnetic equivalent circuit (MEC), which enables the parameters’ sensitivities to be evaluated by their exponential in the nondimensionalized equations, thus providing a fast and accurate way to obtain the parameter sensitivities. Thereafter, the influences of modular manufacturing methods on magnetic performances are discussed, and the robust design approach for the FSPM machine is introduced, which aims to achieve the best machine stability and robustness by setting boundaries on design dimensions when taking into account the manufacturing tolerances. Experimental validations are also presented.

Suggested Citation

  • Gan Zhang & Qing Tong & Anjian Qiu & Xiaohan Xu & Wei Hua & Zhihong Chen, 2022. "Parameter Sensitivity Analysis and Robust Design Approach for Flux-Switching Permanent Magnet Machines," Energies, MDPI, vol. 15(6), pages 1-15, March.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:6:p:2194-:d:773228
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