IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i23p16326-d1288332.html
   My bibliography  Save this article

Automated Monitoring of the Uniform Demagnetization Faults in Permanent-Magnet Synchronous Motors: Practical Methods and Challenges

Author

Listed:
  • Junxiang Li

    (College of Artificial Intelligence and Automation, Beijing University of Technology, Beijing 100124, China)

  • Ziang Li

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310058, China)

  • Jian Zhang

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310058, China)

  • Shuyuan Zhao

    (National Key Laboratory of Science and Technology on Advanced Composites in Special Environments, Harbin Institute of Technology, Harbin 150080, China)

  • Feitian Cheng

    (Jiangsu Marine Resources Development Research Institute, School of Mechanical Engineering, Jiangsu Ocean University, Lianyungang 222005, China)

  • Chuan Qian

    (Jiangsu Marine Resources Development Research Institute, School of Mechanical Engineering, Jiangsu Ocean University, Lianyungang 222005, China)

  • Xingyu Hu

    (Jiangsu Marine Resources Development Research Institute, School of Mechanical Engineering, Jiangsu Ocean University, Lianyungang 222005, China)

  • Guoxiang Zhou

    (Chongqing Research Institute of Harbin Institute of Technology, Chongqing 401135, China)

Abstract

Due to its high power, high efficiency, low pollution, and compact size, permanent-magnet synchronous motors (PMSMs) have been widely used in a variety of fields, including electric vehicles, aerospace, wind turbines, and marine devices, which are used in renewable, sustainable, and environmentally friendly energy resources. However, in these practical scenarios, the motor operating conditions are complex and variable. Under high-temperature and high-current conditions, PMSMs may experience demagnetization failures, not only leading to performance degradation but also inducing unexpected failures of the motors. To reduce the risk of unexpected losses caused by demagnetization faults and improve the safety and reliability of motor systems, it is necessary to apply automated monitoring of the magnet flux of the motor’s permanent magnets and achieve real-time diagnosis of early demagnetization faults, ensuring the safe operation of the motor. This review article tries to summarize the current detection methods of the automated monitoring of demagnetization faults in PMSMs. The main online monitoring technologies from both practical and academic perspectives are summarized and their benefits and challenges are reviewed. Finally, the research trends and suggestions for future improvements are provided. This review article not only sheds light on the origins of the automated monitoring of demagnetization faults but also helps to design highly effective and sustainable permanent-magnet synchronous motors.

Suggested Citation

  • Junxiang Li & Ziang Li & Jian Zhang & Shuyuan Zhao & Feitian Cheng & Chuan Qian & Xingyu Hu & Guoxiang Zhou, 2023. "Automated Monitoring of the Uniform Demagnetization Faults in Permanent-Magnet Synchronous Motors: Practical Methods and Challenges," Sustainability, MDPI, vol. 15(23), pages 1-22, November.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:23:p:16326-:d:1288332
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/23/16326/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/23/16326/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fuzhang Wang & Ayesha Sohail & Wing-Keung Wong & Qurat Ul Ain Azim & Shabieh Farwa & Maria Sajad, 2023. "Artificial Intelligence And Stochastic Optimization Algorithms For The Chaotic Datasets," FRACTALS (fractals), World Scientific Publishing Co. Pte. Ltd., vol. 31(06), pages 1-14.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Khondaker Sazzadul Karim & Mohammad Ekramol Islam & Abdullah Mohammed Ibrahim & Shin-Hung Pan & Md. Mominur Rahman, 2023. "Online Marketing Trends and Purchasing Intent Advances in Customer Satisfaction through PLS-SEM and ANN Approach," Advances in Decision Sciences, Asia University, Taiwan, vol. 27(4), pages 24-54, December.

    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:jsusta:v:15:y:2023:i:23:p:16326-:d:1288332. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.