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Model-Based Control System Design of Brushless Doubly Fed Reluctance Machines Using an Unscented Kalman Filter

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  • Yassine Benômar

    (Mobility, Logistics and Automotive Technology Research Centre (MOBI), Department of Electrical Engineering and Energy Technology (ETEC), Faculty of Engineering, Vrije Universiteit Brussel (VUB), 1050 Brussel, Belgium
    Flanders Make, 3001 Heverlee, Belgium)

  • Julien Croonen

    (Mobility, Logistics and Automotive Technology Research Centre (MOBI), Department of Electrical Engineering and Energy Technology (ETEC), Faculty of Engineering, Vrije Universiteit Brussel (VUB), 1050 Brussel, Belgium
    Flanders Make, 3001 Heverlee, Belgium)

  • Björn Verrelst

    (MECH Department, Vrije Universiteit Brussel (VUB), Pleinlaan 2, 1050 Brussel, Belgium)

  • Joeri Van Mierlo

    (Mobility, Logistics and Automotive Technology Research Centre (MOBI), Department of Electrical Engineering and Energy Technology (ETEC), Faculty of Engineering, Vrije Universiteit Brussel (VUB), 1050 Brussel, Belgium
    Flanders Make, 3001 Heverlee, Belgium)

  • Omar Hegazy

    (Mobility, Logistics and Automotive Technology Research Centre (MOBI), Department of Electrical Engineering and Energy Technology (ETEC), Faculty of Engineering, Vrije Universiteit Brussel (VUB), 1050 Brussel, Belgium
    Flanders Make, 3001 Heverlee, Belgium)

Abstract

The Brushless Doubly Fed Reluctance Machine (BDFRM) is an emerging alternative for variable speed drive systems, providing a significant downsizing of the power electronics converter. This paper proposes a new view on the machine equations, allowing the reuse of the standard control system design for conventional synchronous and asynchronous machines: a cascade control system with an inner current control- and outer speed control loop. The assumptions and simplifications made on the machine model allow for a simple, model-based approach to set the controller gains in a brushless doubly fed machine drive system. The cascade control scheme is combined with an Unscented Kalman Filter as a state observer, capable of estimating the load torque and losses. The performance of the proposed control system design is checked in simulation and tested in real-time on a low power BDFRM prototype.

Suggested Citation

  • Yassine Benômar & Julien Croonen & Björn Verrelst & Joeri Van Mierlo & Omar Hegazy, 2021. "Model-Based Control System Design of Brushless Doubly Fed Reluctance Machines Using an Unscented Kalman Filter," Energies, MDPI, vol. 14(24), pages 1-23, December.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:24:p:8222-:d:696876
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    References listed on IDEAS

    as
    1. Yassine Benômar & Julien Croonen & Björn Verrelst & Joeri Van Mierlo & Omar Hegazy, 2021. "On Analytical Modeling of the Air Gap Field Modulation in the Brushless Doubly Fed Reluctance Machine," Energies, MDPI, vol. 14(9), pages 1-27, April.
    2. Hongwen He & Hongzhou Qin & Xiaokun Sun & Yuanpeng Shui, 2013. "Comparison Study on the Battery SoC Estimation with EKF and UKF Algorithms," Energies, MDPI, vol. 6(10), pages 1-13, September.
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