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An Improved Continuous-Time Model Predictive Control of Permanent Magnetic Synchronous Motors for a Wide-Speed Range

Author

Listed:
  • Dandan Su

    (National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China
    Collaborative Innovation Center of Electric Vehicle in Beijing, 5 South Zhongguancun Street, Haidian District, Beijing 100081, China)

  • Chengning Zhang

    (National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China
    Collaborative Innovation Center of Electric Vehicle in Beijing, 5 South Zhongguancun Street, Haidian District, Beijing 100081, China)

  • Yugang Dong

    (National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China
    Collaborative Innovation Center of Electric Vehicle in Beijing, 5 South Zhongguancun Street, Haidian District, Beijing 100081, China)

Abstract

This paper proposes an improved continuous-time model predictive control (CTMPC) of permanent magnetic synchronous motors (PMSMs) for a wide-speed range, including the constant torque region and the flux-weakening (FW) region. In the constant torque region, the mathematic models of PMSMs in dq-axes are decoupled without the limitation of DC-link voltage. However, in the FW region, the mathematic models of PMSMs in dq-axes are cross-coupled together with the limitation of DC-link voltage. A nonlinear PMSMs mathematic model in the FW region is presented based on the voltage angle. The solving of the nonlinear mathematic model of PMSMs in FW region will lead to heavy computation load for digital signal processing (DSP). To overcome such a problem, a linearization method of the voltage angle is also proposed to reduce the computation load. The selection of transiting points between the constant torque region and FW regions is researched to improve the performance of the driven system. Compared with the proportional integral (PI) controller, the proposed CTMPC has obvious advantages in dealing with systems’ nonlinear constraints and improving system performance by restraining overshoot current under step torque changing. Both simulation and experimental results confirm the effectiveness of the proposed method in achieving good steady-state performance and smooth switching between the constant torque and FW regions.

Suggested Citation

  • Dandan Su & Chengning Zhang & Yugang Dong, 2017. "An Improved Continuous-Time Model Predictive Control of Permanent Magnetic Synchronous Motors for a Wide-Speed Range," Energies, MDPI, vol. 10(12), pages 1-18, December.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:12:p:2051-:d:121551
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    References listed on IDEAS

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    1. Xiong, Rui & Cao, Jiayi & Yu, Quanqing, 2018. "Reinforcement learning-based real-time power management for hybrid energy storage system in the plug-in hybrid electric vehicle," Applied Energy, Elsevier, vol. 211(C), pages 538-548.
    2. Xiong, Rui & Yu, Quanqing & Wang, Le Yi & Lin, Cheng, 2017. "A novel method to obtain the open circuit voltage for the state of charge of lithium ion batteries in electric vehicles by using H infinity filter," Applied Energy, Elsevier, vol. 207(C), pages 346-353.
    3. Xiong, Rui & Tian, Jinpeng & Mu, Hao & Wang, Chun, 2017. "A systematic model-based degradation behavior recognition and health monitoring method for lithium-ion batteries," Applied Energy, Elsevier, vol. 207(C), pages 372-383.
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    Cited by:

    1. Rui Xiong & Suleiman M. Sharkh & Xi Zhang, 2018. "Research Progress on Electric and Intelligent Vehicles," Energies, MDPI, vol. 11(7), pages 1-5, July.
    2. Kai Zhou & Min Ai & Yancheng Sun & Xiaogang Wu & Ran Li, 2019. "PMSM Vector Control Strategy Based on Active Disturbance Rejection Controller," Energies, MDPI, vol. 12(20), pages 1-19, October.
    3. Qi Wang & Haitao Yu & Min Wang & Xinbo Qi, 2018. "A Novel Adaptive Neuro-Control Approach for Permanent Magnet Synchronous Motor Speed Control," Energies, MDPI, vol. 11(9), pages 1-21, September.
    4. 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.
    5. Chunyan Li & Fei Guo & Baoquan Kou & Tao Meng, 2021. "Research on the Non-Magnetic Conductor of a PMSM Based on the Principle of Variable Exciting Magnetic Reluctance," Energies, MDPI, vol. 14(2), pages 1-29, January.

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