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On the Use of Topology Optimization for Synchronous Reluctance Machines Design

Author

Listed:
  • Oğuz Korman

    (Power Electronics, Machines and Control (PEMC) Research Group, University of Nottingham, Nottingham NG7 2RD, UK)

  • Mauro Di Nardo

    (Power Electronics, Machines and Control (PEMC) Research Group, University of Nottingham, Nottingham NG7 2RD, UK)

  • Michele Degano

    (Power Electronics, Machines and Control (PEMC) Research Group, University of Nottingham, Nottingham NG7 2RD, UK)

  • Chris Gerada

    (Power Electronics, Machines and Control (PEMC) Research Group, University of Nottingham, Nottingham NG7 2RD, UK)

Abstract

Synchronous reluctance (SynRel) machines are considered one of the promising and cost-effective solutions to many industrial and mobility applications. Nonetheless, achieving an optimal design is challenging due to the complex correlation between geometry and magnetic characteristics. In order to expand the limits formed by template-based geometries, this work approaches the problem by using topology optimization (TO) through the density method (DM). Optimization settings and their effects on results, both in terms of performance and computation time, are studied extensively by performing optimizations on the rotor of a benchmark SynRel machine. In addition, DM-based TO is applied to an existing rotor geometry to assess its use and performance as a design refinement tool. The findings are presented, highlighting several insights into how to apply TO to SynRel machine design and its limitations, boundaries for performance improvements and related computational cost.

Suggested Citation

  • Oğuz Korman & Mauro Di Nardo & Michele Degano & Chris Gerada, 2022. "On the Use of Topology Optimization for Synchronous Reluctance Machines Design," Energies, MDPI, vol. 15(10), pages 1-13, May.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:10:p:3719-:d:818902
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    Cited by:

    1. Shahid Hussain & Ants Kallaste & Toomas Vaimann, 2023. "Recent Trends in Additive Manufacturing and Topology Optimization of Reluctance Machines," Energies, MDPI, vol. 16(9), pages 1-19, April.

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