IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i11p3010-d370168.html
   My bibliography  Save this article

A Novel Voltage Injection Based Offline Parameters Identification for Current Controller Auto Tuning in SPMSM Drives

Author

Listed:
  • Jiang Long

    (Institute of Power Electronics and Electrical Drives, Harbin Institute of Technology, Harbin 150001, China)

  • Ming Yang

    (Institute of Power Electronics and Electrical Drives, Harbin Institute of Technology, Harbin 150001, China)

  • Yangyang Chen

    (Institute of Power Electronics and Electrical Drives, Harbin Institute of Technology, Harbin 150001, China)

  • Dianguo Xu

    (Institute of Power Electronics and Electrical Drives, Harbin Institute of Technology, Harbin 150001, China)

  • Frede Blaabjerg

    (Department of Energy Technology, Aalborg University, 9220 Aalborg, Denmark)

Abstract

This paper presents a comprehensive study on a novel voltage injection based offline parameter identification method for surface mounted permanent magnet synchronous motors (SPMSMs). It gives solutions to obtain stator resistance, d - and q -axes inductances, and permanent magnet (PM) flux linkage that are totally independent of current and speed controllers, and it is able to track variations in q -axis inductance caused by magnetic saturation. With the proposed voltage amplitude selection strategies, a closed-loop-like current and speed control is achieved throughout the identification process. It provides a marked difference compared with the existing methods that are based on open-loop voltage injection and renders a more simplified and industry-friendly solution compared with methods that rely on controllers. Inverter nonlinearity effect compensation is not required because its voltage error is removed by enabling the motor to function at a designed routine. The proposed method is validated through two SPMSMs with different power rates. It shows that the required parameters can be accurately identified and the proportional-integral current controller auto-tuning is achieved only with very limited motor data such as rated current and number of pole pairs.

Suggested Citation

  • Jiang Long & Ming Yang & Yangyang Chen & Dianguo Xu & Frede Blaabjerg, 2020. "A Novel Voltage Injection Based Offline Parameters Identification for Current Controller Auto Tuning in SPMSM Drives," Energies, MDPI, vol. 13(11), pages 1-21, June.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:11:p:3010-:d:370168
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/11/3010/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/11/3010/
    Download Restriction: no
    ---><---

    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:13:y:2020:i:11:p:3010-:d:370168. 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.