IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i15p5470-d874148.html
   My bibliography  Save this article

Sensorless Control Strategy of Novel Axially Magnetized Vernier Permanent-Magnet Machine

Author

Listed:
  • Bowen Xu

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

  • Jien Ma

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

  • Qiyi Wu

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

  • Lin Qiu

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

  • Xing Liu

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

  • Chao Luo

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

  • Youtong Fang

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

Abstract

Vernier permanent-magnet machines have been attracted more and more attention because of their high torque density. In this paper, the sensorless control strategy of the novel axially magnetized Vernier permanent-magnet (AMVPM) machine is presented. First, the inductance non-linearity is investigated under different load conditions. Second, the mathematical model is established in cooperation with the finite element method. After that, the back electromotive force based sensorless control strategy is developed according to the state equation of the motor. In the sensorless drive, the model reference adaptive system (MRAS) technique incorporated with the inductance non-linearity is used for the speed estimation. The modified control strategy not only increases the stability but also improves the dynamic response of the system. Finally, the simulation results show that the modified MRAS is of high estimation precision, and the AMVPM machine can be well controlled, and the experimental results validated the theoretical design process.

Suggested Citation

  • Bowen Xu & Jien Ma & Qiyi Wu & Lin Qiu & Xing Liu & Chao Luo & Youtong Fang, 2022. "Sensorless Control Strategy of Novel Axially Magnetized Vernier Permanent-Magnet Machine," Energies, MDPI, vol. 15(15), pages 1-19, July.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:15:p:5470-:d:874148
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/15/5470/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/15/5470/
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yongjie Yang & Xudong Liu, 2022. "A Novel Nonsingular Terminal Sliding Mode Observer-Based Sensorless Control for Electrical Drive System," Mathematics, MDPI, vol. 10(17), pages 1-16, August.

    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:gam:jeners:v:15:y:2022:i:15:p:5470-:d:874148. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.