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Real-Time Digital Twin of a Wound Rotor Induction Machine Based on Finite Element Method

Author

Listed:
  • Sami Bouzid

    (Department of Electrical and Computer Engineering, Laval University, Quebec, QC G1V 0A6, Canada)

  • Philippe Viarouge

    (Department of Electrical and Computer Engineering, Laval University, Quebec, QC G1V 0A6, Canada)

  • Jérôme Cros

    (Department of Electrical and Computer Engineering, Laval University, Quebec, QC G1V 0A6, Canada)

Abstract

Monitoring and early fault prediction of large electrical machines is important to maintain a sustainable and safe power system. With the ever-increasing computational power of modern processors, real-time simulation based monitoring of electrical machines is becoming a topic of interest. This work describes the development of a real-time digital twin (RTDT) of a wound rotor induction machine (WRIM) using a precomputed finite element model fed with online measurements. It computes accurate outputs in real-time of electromagnetic quantities otherwise difficult to measure such as local magnetic flux, current in bars and torque. In addition, it considers space harmonics, magnetic imbalance and fault conditions. The development process of the RTDT is described thoroughly and outputs are compared in real-time to measurements taken from the actual machine in rotation. Results show that they are accurate with harmonic content respected.

Suggested Citation

  • Sami Bouzid & Philippe Viarouge & Jérôme Cros, 2020. "Real-Time Digital Twin of a Wound Rotor Induction Machine Based on Finite Element Method," Energies, MDPI, vol. 13(20), pages 1-18, October.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:20:p:5413-:d:429217
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    References listed on IDEAS

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    1. Jinjiang Wang & Lunkuan Ye & Robert X. Gao & Chen Li & Laibin Zhang, 2019. "Digital Twin for rotating machinery fault diagnosis in smart manufacturing," International Journal of Production Research, Taylor & Francis Journals, vol. 57(12), pages 3920-3934, June.
    2. Kati Sidwall & Paul Forsyth, 2020. "Advancements in Real-Time Simulation for the Validation of Grid Modernization Technologies," Energies, MDPI, vol. 13(16), pages 1-17, August.
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    Cited by:

    1. Georgios Falekas & Athanasios Karlis, 2021. "Digital Twin in Electrical Machine Control and Predictive Maintenance: State-of-the-Art and Future Prospects," Energies, MDPI, vol. 14(18), pages 1-26, September.

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