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Model-Based Predictive Rotor Field-Oriented Angle Compensation for Induction Machine Drives

Author

Listed:
  • Yang Liu

    (School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Jin Zhao

    (School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Quan Yin

    (School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China)

Abstract

In this paper, a model-based predictive rotor field-oriented angle compensation approach is proposed for induction machine drives. Indirect rotor field-oriented control is widely used in induction machine drives for its simple implementation and low cost. However, the accuracy of the rotor field-oriented angle is affected by variable parameters such as the rotor resistance and inductance. An inaccurate rotor field-oriented angle leads to a degradation of the torque and dynamic performance, especially in the high-speed flux-weakening region. Therefore, the d-axis and q-axis currents in the rotation reference frame are predicted based on the model and compared with the feedback current to correct the rotor field-oriented angle. To improve the stability and robustness, the proposed predictive algorithm is based on the storage current, voltage, and velocity data. The algorithm can be easily realized in real-time. Finally, the simulated and experimental results verify the algorithm’s effectiveness on a 7.5 kW induction machine setup.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:8:p:2049-:d:531871
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    References listed on IDEAS

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    Cited by:

    1. Ryszard Palka, 2022. "The Performance of Induction Machines," Energies, MDPI, vol. 15(9), pages 1-4, April.

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