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Overview on Digital Twin for Autonomous Electrical Vehicles Propulsion Drive System

Author

Listed:
  • Mahmoud Ibrahim

    (Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, 19086 Tallinn, Estonia)

  • Anton Rassõlkin

    (Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, 19086 Tallinn, Estonia)

  • Toomas Vaimann

    (Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, 19086 Tallinn, Estonia)

  • Ants Kallaste

    (Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, 19086 Tallinn, Estonia)

Abstract

The significant progress in the electric automotive industry brought a higher need for new technological innovations. Digital Twin (DT) is one of the hottest trends of the fourth industrial revolution. It allows representing physical assets under various operating conditions in a low-cost and zero-risk environment. DTs are used in many different fields from aerospace to healthcare. However, one of the perspective applications of such technology is the automotive industry. This paper presents an overview of the implementation of DT technology in electric vehicles (EV) propulsion drive systems. A general review of DT technology is supplemented with main applications analysis and comparison between different simulation technologies. Primary attention is given to the adaptation of DT technology for EV propulsion drive systems.

Suggested Citation

  • Mahmoud Ibrahim & Anton Rassõlkin & Toomas Vaimann & Ants Kallaste, 2022. "Overview on Digital Twin for Autonomous Electrical Vehicles Propulsion Drive System," Sustainability, MDPI, vol. 14(2), pages 1-16, January.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:2:p:601-:d:718886
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    Citations

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    Cited by:

    1. Anton Rassõlkin & Kari Tammi & Galina Demidova & Hassan HosseinNia, 2022. "Mechatronics Technology and Transportation Sustainability," Sustainability, MDPI, vol. 14(3), pages 1-3, January.
    2. Pietro Stabile & Federico Ballo & Giorgio Previati & Giampiero Mastinu & Massimiliano Gobbi, 2023. "Eco-Driving Strategy Implementation for Ultra-Efficient Lightweight Electric Vehicles in Realistic Driving Scenarios," Energies, MDPI, vol. 16(3), pages 1-19, January.
    3. Anton Dianov, 2022. "Instant Closing of Permanent Magnet Synchronous Motor Control Systems at Open-Loop Start," Sustainability, MDPI, vol. 14(19), pages 1-17, October.
    4. Mahmoud Ibrahim & Anton Rassõlkin & Toomas Vaimann & Ants Kallaste & Janis Zakis & Van Khang Hyunh & Raimondas Pomarnacki, 2023. "Digital Twin as a Virtual Sensor for Wind Turbine Applications," Energies, MDPI, vol. 16(17), pages 1-12, August.
    5. Dimitrios Rimpas & Stavrοs D. Kaminaris & Dimitrios D. Piromalis & George Vokas & Konstantinos G. Arvanitis & Christos-Spyridon Karavas, 2023. "Comparative Review of Motor Technologies for Electric Vehicles Powered by a Hybrid Energy Storage System Based on Multi-Criteria Analysis," Energies, MDPI, vol. 16(6), pages 1-24, March.
    6. Maurizio Cutini & Carlo Bisaglia & Massimo Brambilla & Andrea Bragaglio & Federico Pallottino & Alberto Assirelli & Elio Romano & Alessandro Montaghi & Elisabetta Leo & Marco Pezzola & Claudio Maroni , 2023. "A Co-Simulation Virtual Reality Machinery Simulator for Advanced Precision Agriculture Applications," Agriculture, MDPI, vol. 13(8), pages 1-21, August.
    7. Bhaskar P. Rimal & Cuiyu Kong & Bikrant Poudel & Yong Wang & Pratima Shahi, 2022. "Smart Electric Vehicle Charging in the Era of Internet of Vehicles, Emerging Trends, and Open Issues," Energies, MDPI, vol. 15(5), pages 1-24, March.

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