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Design for Reliability: The Case of Fractional-Slot Surface Permanent-Magnet Machines

Author

Listed:
  • Ambra Torreggiani

    (DISMI, University of Modena and Reggio Emilia, 42122 Reggio Emilia, Italy)

  • Claudio Bianchini

    (DIEF, University of Modena and Reggio Emilia, 41125 Modena, Italy)

  • Matteo Davoli

    (Raw Power S.r.l., 42122 Reggio Emilia, Italy)

  • Alberto Bellini

    (DEI, University of Bologna, 47521 Cesena, Italy)

Abstract

Surface permanent-magnet machines are widely used in different applications, from industrial automation to home appliance and electrical traction. Among any possible machine topology, the fractional-slot surface permanent-magnet one has gained increasing importance, because of its high torque density, low cogging torque, extended flux weakening capability and high efficiency. In addition, fractional-slot machines are attractive for tooth concentrated windings, which allow some optimized manufacturing solutions such as modular stator tooth and high slot filling factor, which result in copper volume reduction; cost reduction, and lower stator parasitic resistances. The slot–pole combination is one of the most important design parameter and, as shown in this paper, it affects performances and the robustness of the machine with respect to the manufacturing imperfections. In the literature, slot–pole combinations are optimized at design phase by finite-element analysis relying on a healthy machine model. The original contribution of this paper is a design for reliability method that models manufacturing defects and includes them at design phase in the optimization process of slot–pole combinations. A method is presented that allows defining the optimal design parameters for maximum performances and robustness towards unavoidable imperfections caused by tolerances of the manufacturing process.

Suggested Citation

  • Ambra Torreggiani & Claudio Bianchini & Matteo Davoli & Alberto Bellini, 2019. "Design for Reliability: The Case of Fractional-Slot Surface Permanent-Magnet Machines," Energies, MDPI, vol. 12(9), pages 1-18, May.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:9:p:1691-:d:228306
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    Citations

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    Cited by:

    1. Armin Dietz & Antonino Oscar Di Tommaso & Fabrizio Marignetti & Rosario Miceli & Claudio Nevoloso, 2020. "Enhanced Flexible Algorithm for the Optimization of Slot Filling Factors in Electrical Machines," Energies, MDPI, vol. 13(5), pages 1-21, February.
    2. Elia Brescia & Donatello Costantino & Paolo Roberto Massenio & Vito Giuseppe Monopoli & Francesco Cupertino & Giuseppe Leonardo Cascella, 2021. "A Design Method for the Cogging Torque Minimization of Permanent Magnet Machines with a Segmented Stator Core Based on ANN Surrogate Models," Energies, MDPI, vol. 14(7), pages 1-26, March.

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