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Optimization of Magnetic Gear Patterns Based on Taguchi Method Combined with Genetic Algorithm

Author

Listed:
  • Yuan Mao

    (College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China)

  • Yun Yang

    (Department of Electrical Engineering, The Hong Kong Polytechnic University, Hong Kong, China)

Abstract

Magnetic gears (MGs) have gained increasing attention due to their sound performance in high torque density and low friction loss. Aiming to maximize the torque density, topology design has been a popular issue in recent years. However, studies on the optimization comparisons of a general MG topology pattern are very limited. This paper proposes a Taguchi-method-based optimization method for a general MG topology pattern, which can cover most of the common types of radially magnetized concentric-surface-mounted MGs (RMCSM-MGs). The Taguchi method is introduced to evaluate the influence of each parameter in MGs. Moreover, the parameter value range is re-examined based on the sensitivity analysis results. The genetic algorithm (GA) method is adopted to optimize the topology pattern in the study.

Suggested Citation

  • Yuan Mao & Yun Yang, 2022. "Optimization of Magnetic Gear Patterns Based on Taguchi Method Combined with Genetic Algorithm," Energies, MDPI, vol. 15(14), pages 1-12, July.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:14:p:4963-:d:857310
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    References listed on IDEAS

    as
    1. Shuangxia Niu & Yuan Mao, 2016. "A Comparative Study of Novel Topologies of Magnetic Gears," Energies, MDPI, vol. 9(10), pages 1-10, September.
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    Cited by:

    1. Carlos D. Zuluaga-Ríos & Alejandro Villa-Jaramillo & Sergio D. Saldarriaga-Zuluaga, 2022. "Evaluation of Distributed Generation and Electric Vehicles Hosting Capacity in Islanded DC Grids Considering EV Uncertainty," Energies, MDPI, vol. 15(20), pages 1-17, October.

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