IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i20p7615-d943037.html
   My bibliography  Save this article

Sensorless Control of High-Speed Motors Subject to Iron Loss

Author

Listed:
  • Yang Cao

    (College of Automation, Nanjing University of Science and Technology, Nanjing 210000, China)

  • Jian Guo

    (College of Automation, Nanjing University of Science and Technology, Nanjing 210000, China)

Abstract

It is widely recognized that the iron loss produced by motors at high speeds will directly affect the angle and size of the back electromotive force, and, therefore, it cannot be ignored. In this paper, a high-performance sensorless control algorithm is proposed for high-speed permanent magnet synchronous motors (HSPMSM), taking the iron loss into account. First, the resistance representing the core loss is precalculated by finite element analysis, and then a sliding mode observer with disturbance observation is designed to estimate the rotor position. The observer possesses the advantages of suppressing the chattering phenomenon and enhancing the robustness against uncertainty. Meanwhile, the idea of the characteristic model is used to design an adaptive robust control law to improve the speed control accuracy. Subsequently, a sensorless control scheme is proposed by using the proposed observer in combination with the designed control scheme. The stability of the observer and controller is verified by the Lyapunov theory method. Finally, a simulation example is given to demonstrate the correctness and the effectiveness of the proposed algorithm.

Suggested Citation

  • Yang Cao & Jian Guo, 2022. "Sensorless Control of High-Speed Motors Subject to Iron Loss," Energies, MDPI, vol. 15(20), pages 1-14, October.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:20:p:7615-:d:943037
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/20/7615/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/20/7615/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yubo Liu & Junlong Fang & Kezhu Tan & Boyan Huang & Wenshuai He, 2020. "Sliding Mode Observer with Adaptive Parameter Estimation for Sensorless Control of IPMSM," Energies, MDPI, vol. 13(22), pages 1-18, November.
    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. Claudiu-Ionel Nicola & Marcel Nicola, 2023. "Improved Performance for PMSM Sensorless Control Based on the LADRC Controller, ESO-Type Observer, DO-Type Observer, and RL-TD3 Agent," Mathematics, MDPI, vol. 11(15), pages 1-25, July.
    2. Weidong Feng & Jing Bai & Zhiqiang Zhang & Jing Zhang, 2022. "A Composite Variable Structure PI Controller for Sensorless Speed Control Systems of IPMSM," Energies, MDPI, vol. 15(21), pages 1-18, November.
    3. Pawel Latosinski & Andrzej Bartoszewicz, 2023. "Sliding Mode Controllers in Energy Systems and Other Applications," Energies, MDPI, vol. 16(3), pages 1-4, January.
    4. Habib Benbouhenni & Nicu Bizon, 2021. "Third-Order Sliding Mode Applied to the Direct Field-Oriented Control of the Asynchronous Generator for Variable-Speed Contra-Rotating Wind Turbine Generation Systems," Energies, MDPI, vol. 14(18), pages 1-20, September.
    5. Yang Liu & Jin Zhao & Quan Yin, 2021. "Model-Based Predictive Rotor Field-Oriented Angle Compensation for Induction Machine Drives," Energies, MDPI, vol. 14(8), pages 1-13, April.
    6. Karol Kyslan & Viktor Petro & Peter Bober & Viktor Šlapák & František Ďurovský & Mateusz Dybkowski & Matúš Hric, 2022. "A Comparative Study and Optimization of Switching Functions for Sliding-Mode Observer in Sensorless Control of PMSM," Energies, MDPI, vol. 15(7), pages 1-17, April.
    7. Artun Sel & Bilgehan Sel & Umit Coskun & Cosku Kasnakoglu, 2022. "SOS-Based Nonlinear Observer Design for Simultaneous State and Disturbance Estimation Designed for a PMSM Model," Sustainability, MDPI, vol. 14(17), pages 1-12, August.
    8. Shuai Li & Ke Zhu & Liang Chen & Yao Yan & Qing Guo, 2022. "Variable Structure Disturbance Observer Based Dynamic Surface Control of Electrohydraulic Systems with Parametric Uncertainty," Energies, MDPI, vol. 15(5), pages 1-15, February.
    9. Thyago Estrabis & Gabriel Gentil & Raymundo Cordero, 2021. "Development of a Resolver-to-Digital Converter Based on Second-Order Difference Generalized Predictive Control," Energies, MDPI, vol. 14(2), pages 1-22, January.
    10. Paweł Latosiński & Andrzej Bartoszewicz, 2021. "Zero-Width Quasi-Sliding Mode Band in the Presence of Non-Matched Uncertainties," Energies, MDPI, vol. 14(11), pages 1-16, May.
    11. Xiaolei Cai & Qixuan Wang & Yucheng Wang & Li Zhang, 2023. "Research on a Variable-Leakage-Flux Permanent Magnet Motor Control System Based on an Adaptive Tracking Estimator," Energies, MDPI, vol. 16(2), pages 1-16, January.
    12. Alessandro Benevieri & Lorenzo Carbone & Simone Cosso & Krishneel Kumar & Mario Marchesoni & Massimiliano Passalacqua & Luis Vaccaro, 2022. "Surface Permanent Magnet Synchronous Motors’ Passive Sensorless Control: A Review," Energies, MDPI, vol. 15(20), pages 1-26, October.

    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:20:p:7615-:d:943037. 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.