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Optimal Operating Point Determination Method Design for Range-Extended Electric Vehicles Based on Real Driving Tests

Author

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  • Gye-Seong Lee

    (Industrial Technology (Robotics), Korea University of Science and Technology, 217 Gajeong-ro, Yuseong-gu, Daejeon 34113, Korea
    EV Components & Materials R&D Group, Korea Institute of Industrial Technology, 6 Cheomdan-gwagiro 208 Beon-gil, Buk-gu, Gwangju 61012, Korea)

  • Dong-Hyun Kim

    (EV Components & Materials R&D Group, Korea Institute of Industrial Technology, 6 Cheomdan-gwagiro 208 Beon-gil, Buk-gu, Gwangju 61012, Korea)

  • Jong-Ho Han

    (EV Components & Materials R&D Group, Korea Institute of Industrial Technology, 6 Cheomdan-gwagiro 208 Beon-gil, Buk-gu, Gwangju 61012, Korea)

  • Myeong-Hwan Hwang

    (EV Components & Materials R&D Group, Korea Institute of Industrial Technology, 6 Cheomdan-gwagiro 208 Beon-gil, Buk-gu, Gwangju 61012, Korea)

  • Hyun-Rok Cha

    (Industrial Technology (Robotics), Korea University of Science and Technology, 217 Gajeong-ro, Yuseong-gu, Daejeon 34113, Korea
    EV Components & Materials R&D Group, Korea Institute of Industrial Technology, 6 Cheomdan-gwagiro 208 Beon-gil, Buk-gu, Gwangju 61012, Korea)

Abstract

In this study, a method to determine the optimal generator operating point is proposed to enhance the utilization of power resources in a range-extended electric vehicle (Re-EV). Currently, the Re-EV is being developed as one of the solutions to the short driving range and charge problem of electric vehicles (EVs). In particular, we present a method for flexibly determining the operating point of the generators mounted on Re-EVs based on the power consumption trends of the users. Our proposed method can address the problem in existing algorithms wherein all the available resources are not utilized, even though there is fuel remaining in the EV because the battery is not completely discharged. The proposed algorithm was developed based on data acquired through actual driving tests using an agricultural utility vehicle; these data can be applied to various power consumption patterns, including nonlinear consumption patterns. In addition, this algorithm can be applied to other types of Re-EV with different battery and generator specifications. We perform simulations and experiments to verify the proposed algorithm and the results demonstrate the effectiveness of the proposed approach compared with other existing methods.

Suggested Citation

  • Gye-Seong Lee & Dong-Hyun Kim & Jong-Ho Han & Myeong-Hwan Hwang & Hyun-Rok Cha, 2019. "Optimal Operating Point Determination Method Design for Range-Extended Electric Vehicles Based on Real Driving Tests," Energies, MDPI, vol. 12(5), pages 1-17, March.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:5:p:845-:d:210873
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    References listed on IDEAS

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    Cited by:

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    2. Xiao, B. & Ruan, J. & Yang, W. & Walker, P.D. & Zhang, N., 2021. "A review of pivotal energy management strategies for extended range electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    3. Jakub Lasocki & Artur Kopczyński & Paweł Krawczyk & Paweł Roszczyk, 2019. "Empirical Study on the Efficiency of an LPG-Supplied Range Extender for Electric Vehicles," Energies, MDPI, vol. 12(18), pages 1-23, September.
    4. Paweł Krawczyk & Artur Kopczyński & Jakub Lasocki, 2022. "Modeling and Simulation of Extended-Range Electric Vehicle with Control Strategy to Assess Fuel Consumption and CO 2 Emission for the Expected Driving Range," Energies, MDPI, vol. 15(12), pages 1-41, June.

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