IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/7767662.html
   My bibliography  Save this article

Optimization of Disk Magnetic Coupler Based on Orthogonal Test and Multiobjective Genetic Algorithm

Author

Listed:
  • Jianlong Gong
  • Meixia Jiang
  • Xiaodong Sun

Abstract

In order to solve the optimization problem of the disk magnetic coupler, the two optimization schemes, the orthogonal test and multiobjective genetic algorithm, were used to optimize the disk magnetic coupler to maximize the magnetic torque while reducing the eddy current loss, and then the correctness of the optimization results was verified by electromagnetic simulation experiments. The eddy current loss and magnetic torque of the optimized disk magnetic coupler were normalized by using the comprehensive evaluation function. After orthogonal test and multiobjective genetic algorithm optimization, the comprehensive evaluation value of the disk magnetic coupler increased by 2.43 times and 3.30 times, respectively, and the optimization effect of multiobjective genetic algorithm is more significant. The relative errors between theoretical and simulated values of the maximum magnetic torque and eddy current loss by multiobjective genetic algorithm are 2.22%–4.72% and 1.13%–6.41%, respectively, suggesting that the optimization method is feasible. The research results show that the multiobjective genetic algorithm optimization can significantly improve the performance of magnetic disk coupler, which can provide theoretical and technical basis for the design of disk magnetic coupler.

Suggested Citation

  • Jianlong Gong & Meixia Jiang & Xiaodong Sun, 2023. "Optimization of Disk Magnetic Coupler Based on Orthogonal Test and Multiobjective Genetic Algorithm," Mathematical Problems in Engineering, Hindawi, vol. 2023, pages 1-16, April.
    • Handle: RePEc:hin:jnlmpe:7767662
    DOI: 10.1155/2023/7767662
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/mpe/2023/7767662.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/mpe/2023/7767662.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2023/7767662?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:jnlmpe:7767662. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.