IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i19p3773-d273305.html
   My bibliography  Save this article

Sensorless-MTPA Control of Permanent Magnet Synchronous Motor Based on an Adaptive Sliding Mode Observer

Author

Listed:
  • Mengting Ye

    (School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China)

  • Tingna Shi

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

  • Huimin Wang

    (School of Electrical Engineering and Automation, Tianjin Polytechnic University, Tianjin 300387, China)

  • Xinmin Li

    (School of Electrical Engineering and Automation, Tianjin Polytechnic University, Tianjin 300387, China)

  • Changliang Xia

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
    School of Electrical Engineering and Automation, Tianjin Polytechnic University, Tianjin 300387, China)

Abstract

Different from the traditional method of the interior permanent magnet synchronous motor (IPMSM), the sensorless maximum torque per ampere (MTPA) control scheme in this paper does not need two observers for rotor position and d-q axis inductances, respectively. It only needs an adaptive sliding mode observer (ASMO) based on the extended flux (EF) to realize double-loop control and MTPA operation simultaneously. The adaptive mechanism of rotor speed is designed to ensure stability of the ASMO. The rotor position and the difference between d-axis and q-axis inductances are obtained from the estimated EF to acquire the MTPA points when the position sensor of the IPMSM is absent. The proposed scheme is realized on a 20kW IPMSM where the sensorless control performance and the MTPA control performance are tested. The effectiveness of the proposed method is verified by the experiment results.

Suggested Citation

  • Mengting Ye & Tingna Shi & Huimin Wang & Xinmin Li & Changliang Xia, 2019. "Sensorless-MTPA Control of Permanent Magnet Synchronous Motor Based on an Adaptive Sliding Mode Observer," Energies, MDPI, vol. 12(19), pages 1-15, October.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:19:p:3773-:d:273305
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/19/3773/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/12/19/3773/
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Marcel Nicola & Claudiu-Ionel Nicola & Dan Selișteanu, 2022. "Improvement of PMSM Sensorless Control Based on Synergetic and Sliding Mode Controllers Using a Reinforcement Learning Deep Deterministic Policy Gradient Agent," Energies, MDPI, vol. 15(6), pages 1-30, March.
    2. Kan Wang & Zhong Wu & Zhongyi Chu, 2020. "DC-Link Current Control with Inverter Nonlinearity Compensation for Permanent Magnet Synchronous Motor Drives," Energies, MDPI, vol. 13(3), pages 1-16, January.
    3. Massimo Caruso & Antonino Oscar Di Tommaso & Giuseppe Lisciandrello & Rosa Anna Mastromauro & Rosario Miceli & Claudio Nevoloso & Ciro Spataro & Marco Trapanese, 2020. "A General and Accurate Measurement Procedure for the Detection of Power Losses Variations in Permanent Magnet Synchronous Motor Drives," Energies, MDPI, vol. 13(21), pages 1-19, November.
    4. Anton Dianov & Alecksey Anuchin, 2021. "Design of Constraints for Seeking Maximum Torque per Ampere Techniques in an Interior Permanent Magnet Synchronous Motor Control," Mathematics, MDPI, vol. 9(21), pages 1-21, November.
    5. Hyun-Jae Lee & Jin-Geun Shon, 2021. "Improved Voltage Flux-Weakening Strategy of Permanent Magnet Synchronous Motor in High-Speed Operation," Energies, MDPI, vol. 14(22), pages 1-15, November.
    6. Anton Dianov & Alecksey Anuchin, 2020. "Adaptive Maximum Torque per Ampere Control of Sensorless Permanent Magnet Motor Drives," Energies, MDPI, vol. 13(19), pages 1-13, September.
    7. Jiachun Lin & Yuteng Zhao & Pan Zhang & Junjie Wang & Hao Su, 2021. "Research on Compound Sliding Mode Control of a Permanent Magnet Synchronous Motor in Electromechanical Actuators," Energies, MDPI, vol. 14(21), pages 1-17, November.
    8. Yujiao Zhao & Haisheng Yu & Shixian Wang, 2021. "An Improved Super-Twisting High-Order Sliding Mode Observer for Sensorless Control of Permanent Magnet Synchronous Motor," Energies, MDPI, vol. 14(19), pages 1-18, September.
    9. Hyunjae Lee & Gunbok Lee & Gildong Kim & Jingeun Shon, 2022. "Variable Incremental Controller of Permanent-Magnet Synchronous Motor for Voltage-Based Flux-Weakening Control," Energies, MDPI, vol. 15(15), pages 1-15, August.
    10. Zheng Li & Zihao Zhang & Jinsong Wang & Shaohua Wang & Xuetong Chen & Hexu Sun, 2022. "ADRC Control System of PMLSM Based on Novel Non-Singular Terminal Sliding Mode Observer," Energies, MDPI, vol. 15(10), pages 1-18, May.

    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:12:y:2019:i:19:p:3773-:d:273305. 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.