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A Comprehensive Electric Vehicle Model for Vehicle-to-Grid Strategy Development

Author

Listed:
  • Fabian Rücker

    (Electrochemical Energy Conversion and Storage Systems, Institute for Power Electronics and Electrical Drives (ISEA), RWTH Aachen, Jägerstr. 17-19, 52066 Aachen, Germany
    Juelich Aachen Research Alliance, JARA-Energy, 52056 Aachen, Germany
    Institute for Power Generation and Storage Systems (PGS), E.ON ERC, RWTH Aachen University, Mathieustr. 10, 52074 Aachen, Germany)

  • Ilka Schoeneberger

    (Electrochemical Energy Conversion and Storage Systems, Institute for Power Electronics and Electrical Drives (ISEA), RWTH Aachen, Jägerstr. 17-19, 52066 Aachen, Germany
    Juelich Aachen Research Alliance, JARA-Energy, 52056 Aachen, Germany
    Institute for Power Generation and Storage Systems (PGS), E.ON ERC, RWTH Aachen University, Mathieustr. 10, 52074 Aachen, Germany)

  • Till Wilmschen

    (Electrochemical Energy Conversion and Storage Systems, Institute for Power Electronics and Electrical Drives (ISEA), RWTH Aachen, Jägerstr. 17-19, 52066 Aachen, Germany
    Wall Box Chargers, S.L., Carrer Josep Ros i Ros, 21, Sant Andreu de la Barca, 08740 Barcelona, Spain)

  • Ahmed Chahbaz

    (Electrochemical Energy Conversion and Storage Systems, Institute for Power Electronics and Electrical Drives (ISEA), RWTH Aachen, Jägerstr. 17-19, 52066 Aachen, Germany
    Juelich Aachen Research Alliance, JARA-Energy, 52056 Aachen, Germany
    Institute for Power Generation and Storage Systems (PGS), E.ON ERC, RWTH Aachen University, Mathieustr. 10, 52074 Aachen, Germany)

  • Philipp Dechent

    (Electrochemical Energy Conversion and Storage Systems, Institute for Power Electronics and Electrical Drives (ISEA), RWTH Aachen, Jägerstr. 17-19, 52066 Aachen, Germany
    Juelich Aachen Research Alliance, JARA-Energy, 52056 Aachen, Germany
    Institute for Power Generation and Storage Systems (PGS), E.ON ERC, RWTH Aachen University, Mathieustr. 10, 52074 Aachen, Germany)

  • Felix Hildenbrand

    (Electrochemical Energy Conversion and Storage Systems, Institute for Power Electronics and Electrical Drives (ISEA), RWTH Aachen, Jägerstr. 17-19, 52066 Aachen, Germany
    Juelich Aachen Research Alliance, JARA-Energy, 52056 Aachen, Germany
    Institute for Power Generation and Storage Systems (PGS), E.ON ERC, RWTH Aachen University, Mathieustr. 10, 52074 Aachen, Germany)

  • Elias Barbers

    (Electrochemical Energy Conversion and Storage Systems, Institute for Power Electronics and Electrical Drives (ISEA), RWTH Aachen, Jägerstr. 17-19, 52066 Aachen, Germany)

  • Matthias Kuipers

    (Electrochemical Energy Conversion and Storage Systems, Institute for Power Electronics and Electrical Drives (ISEA), RWTH Aachen, Jägerstr. 17-19, 52066 Aachen, Germany
    Juelich Aachen Research Alliance, JARA-Energy, 52056 Aachen, Germany
    Institute for Power Generation and Storage Systems (PGS), E.ON ERC, RWTH Aachen University, Mathieustr. 10, 52074 Aachen, Germany)

  • Jan Figgener

    (Electrochemical Energy Conversion and Storage Systems, Institute for Power Electronics and Electrical Drives (ISEA), RWTH Aachen, Jägerstr. 17-19, 52066 Aachen, Germany
    Juelich Aachen Research Alliance, JARA-Energy, 52056 Aachen, Germany
    Institute for Power Generation and Storage Systems (PGS), E.ON ERC, RWTH Aachen University, Mathieustr. 10, 52074 Aachen, Germany)

  • Dirk Uwe Sauer

    (Electrochemical Energy Conversion and Storage Systems, Institute for Power Electronics and Electrical Drives (ISEA), RWTH Aachen, Jägerstr. 17-19, 52066 Aachen, Germany
    Juelich Aachen Research Alliance, JARA-Energy, 52056 Aachen, Germany
    Institute for Power Generation and Storage Systems (PGS), E.ON ERC, RWTH Aachen University, Mathieustr. 10, 52074 Aachen, Germany
    Helmholtz-Institute Münster (HIMS), Ionics in Energy Storage, 52428 Jülich, Germany)

Abstract

A comprehensive electric vehicle model is developed to characterize the behavior of the Smart e.d. (2013) while driving, charging and providing vehicle-to-grid services. To facilitate vehicle-to-grid strategy development, the EV model is completed with the measurement of the on-board charger efficiency and the charging control behavior upon external set-point request via IEC 61851-1. The battery model is an electro-thermal model with a dual polarization equivalent circuit electrical model coupled with a lumped thermal model with active liquid cooling. The aging trend of the EV’s 50 Ah large format pouch cell with NMC chemistry is evaluated via accelerated aging tests in the laboratory. Performance of the model is validated using laboratory pack tests, charging and driving field data. The RMSE of the cell voltage was between 18.49 m V and 67.17 m V per cell for the validation profiles. Cells stored at 100% SOC and 40 °C reached end-of-life (80% of initial capacity) after 431–589 days. The end-of-life for a cell cycled with 80% DOD around an SOC of 50% is reached after 3634 equivalent full cycles which equates to a driving distance of over 420,000 k m . The full parameter set of the model is provided to serve as a resource for vehicle-to-grid strategy development.

Suggested Citation

  • Fabian Rücker & Ilka Schoeneberger & Till Wilmschen & Ahmed Chahbaz & Philipp Dechent & Felix Hildenbrand & Elias Barbers & Matthias Kuipers & Jan Figgener & Dirk Uwe Sauer, 2022. "A Comprehensive Electric Vehicle Model for Vehicle-to-Grid Strategy Development," Energies, MDPI, vol. 15(12), pages 1-31, June.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:12:p:4186-:d:833313
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    References listed on IDEAS

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    1. de Hoog, Joris & Timmermans, Jean-Marc & Ioan-Stroe, Daniel & Swierczynski, Maciej & Jaguemont, Joris & Goutam, Shovon & Omar, Noshin & Van Mierlo, Joeri & Van Den Bossche, Peter, 2017. "Combined cycling and calendar capacity fade modeling of a Nickel-Manganese-Cobalt Oxide Cell with real-life profile validation," Applied Energy, Elsevier, vol. 200(C), pages 47-61.
    2. Wang, Yujie & Tian, Jiaqiang & Sun, Zhendong & Wang, Li & Xu, Ruilong & Li, Mince & Chen, Zonghai, 2020. "A comprehensive review of battery modeling and state estimation approaches for advanced battery management systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    3. Tang, Xiaopeng & Zou, Changfu & Yao, Ke & Lu, Jingyi & Xia, Yongxiao & Gao, Furong, 2019. "Aging trajectory prediction for lithium-ion batteries via model migration and Bayesian Monte Carlo method," Applied Energy, Elsevier, vol. 254(C).
    4. Zhu, Rui & Duan, Bin & Zhang, Chenghui & Gong, Sizhao, 2019. "Accurate lithium-ion battery modeling with inverse repeat binary sequence for electric vehicle applications," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    5. Englberger, Stefan & Abo Gamra, Kareem & Tepe, Benedikt & Schreiber, Michael & Jossen, Andreas & Hesse, Holger, 2021. "Electric vehicle multi-use: Optimizing multiple value streams using mobile storage systems in a vehicle-to-grid context," Applied Energy, Elsevier, vol. 304(C).
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    Cited by:

    1. Namala Narasimhulu & Mohan Awasthy & Rocío Pérez de Prado & Parameshachari Bidare Divakarachari & Nadimapalli Himabindu, 2023. "Analysis and Impacts of Grid Integrated Photo-Voltaic and Electric Vehicle on Power Quality Issues," Energies, MDPI, vol. 16(2), pages 1-18, January.
    2. Rajeshkumar Ramraj & Ehsan Pashajavid & Sanath Alahakoon & Shantha Jayasinghe, 2023. "Quality of Service and Associated Communication Infrastructure for Electric Vehicles," Energies, MDPI, vol. 16(20), pages 1-28, October.

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