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A Dual-Voltage-Vector Model-Free Predictive Current Controller for Synchronous Reluctance Motor Drive Systems

Author

Listed:
  • Cheng-Kai Lin

    (Department of Electrical Engineering, National Taiwan Ocean University, Keelung 202, Taiwan)

  • Jen-te Yu

    (Department of Electrical Engineering, Chung Yuan Christian University, Taoyuan 320, Taiwan)

  • Hao-Qun Huang

    (Department of Electrical Engineering, National Taiwan Ocean University, Keelung 202, Taiwan)

  • Jyun-Ting Wang

    (Department of Electrical Engineering, National Taiwan Ocean University, Keelung 202, Taiwan)

  • Hsing-Cheng Yu

    (Department of Systems Engineering and Naval Architecture, National Taiwan Ocean University, Keelung 202, Taiwan)

  • Yen-Shin Lai

    (Department of Electrical Engineering, National Taipei University of Technology, Taipei 106, Taiwan)

Abstract

For current control in power conversion and motor drive systems, there exist three classic methods in the literature and they are the hysteresis current control (HCC), the sine pulse-width modulation (SPWM), and the space vector pulse width modulation (SVPWM). HCC is easy to implement, but has relatively large current harmonic distortion as the disadvantage. On the other hand, the SPWM and SVPWM use modulation technique, commonly together with at least one proportional-integral (PI) regulator to reduce load current ripples, and hence demanding more computation time. This paper aims to improve the performance of a recently proposed new current control method—the single-voltage-vector model predictive current control (SVV-MPCC), for synchronous reluctance motor (SynRMs) drives. To that end, a dual-voltage-vector model-free predictive current control (DVV-MFPCC) for SynRMs is proposed. Unlike the SVV-MPCC that applies only a single voltage vector per sampling period, the proposed DVV-MFPCC is capable of providing two successive segmentary current predictions in the next sampling period through all possible combinations from any two candidate switching states increasing the number of applicable switching modes from seven to nineteen and reducing the prediction error effectively. Moreover, the new control does not utilize any parameters of the SynRM nor its mathematical model. The performance is effectively enhanced compared to that of SVV-MPCC. The working principle of the DVV-MFPCC will be detailed in this paper. Finally, the SVV-MPCC, the single-voltage-vector model-free predictive current control (SVV-MFPCC), the dual-voltage-vector model predictive current control (DVV-MPCC), and the DVV-MFPCC are realized to control the stator currents of SynRM through a 32-bit microcontroller TMS320F28377S. Experimental results are provided to validate the new method and verify that the DVV-MFPCC performs better than do the SVV-MPCC, the SVV-MFPCC, and the DVV-MPCC.

Suggested Citation

  • Cheng-Kai Lin & Jen-te Yu & Hao-Qun Huang & Jyun-Ting Wang & Hsing-Cheng Yu & Yen-Shin Lai, 2018. "A Dual-Voltage-Vector Model-Free Predictive Current Controller for Synchronous Reluctance Motor Drive Systems," Energies, MDPI, vol. 11(7), pages 1-29, July.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:7:p:1743-:d:155979
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    References listed on IDEAS

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    Cited by:

    1. Kang Wang & Ruituo Huai & Zhihao Yu & Xiaoyang Zhang & Fengjuan Li & Luwei Zhang, 2019. "Comparison Study of Induction Motor Models Considering Iron Loss for Electric Drives," Energies, MDPI, vol. 12(3), pages 1-13, February.
    2. Hui Cai & Hui Wang & Mengqiu Li & Shiqi Shen & Yaojing Feng & Jian Zheng, 2018. "Torque Ripple Reduction for Switched Reluctance Motor with Optimized PWM Control Strategy," Energies, MDPI, vol. 11(11), pages 1-27, November.
    3. Crestian Almazan Agustin & Jen-te Yu & Cheng-Kai Lin & Xiang-Yong Fu, 2019. "A Modulated Model Predictive Current Controller for Interior Permanent-Magnet Synchronous Motors," Energies, MDPI, vol. 12(15), pages 1-20, July.

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