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Vehicle Model-Based Driving Strategy Optimization for Lightweight Vehicle

Author

Listed:
  • Zoltán Pusztai

    (Vehicle Industry Research Center, Széchenyi István University, Egyetem tér 1, H-9026 Győr, Hungary)

  • Péter Kőrös

    (Vehicle Industry Research Center, Széchenyi István University, Egyetem tér 1, H-9026 Győr, Hungary)

  • Ferenc Szauter

    (Vehicle Industry Research Center, Széchenyi István University, Egyetem tér 1, H-9026 Győr, Hungary)

  • Ferenc Friedler

    (Vehicle Industry Research Center, Széchenyi István University, Egyetem tér 1, H-9026 Győr, Hungary)

Abstract

In this paper, driving strategy optimization for a track is proposed for an energy efficient battery electric vehicle dedicated to the Shell Eco-marathon. A measurement-based mathematical vehicle model was developed to simulate the behavior of the vehicle. The model contains complicated elements such as the vehicle’s cornering resistance and the efficiency field of the entire powertrain. The validation of the model was presented by using the collected telemetry data from the 2019 Shell Eco-marathon competition in London (UK). The evaluation of applicable powertrains was carried out before the driving strategy optimization. The optimal acceleration curve for each investigated powertrain was defined. Using the proper powertrain is a crucial part of energy efficiency, as the drive has the most significant energy demand among all components. Two tracks with different characteristics were analyzed to show the efficiency of the proposed optimization method. The optimization results are compared to the reference method from the literature. The results of this study provide an applicable vehicle modelling methodology with efficient optimization framework, which demonstrates 5.5% improvement in energy consumption compared to the reference optimization theory.

Suggested Citation

  • Zoltán Pusztai & Péter Kőrös & Ferenc Szauter & Ferenc Friedler, 2022. "Vehicle Model-Based Driving Strategy Optimization for Lightweight Vehicle," Energies, MDPI, vol. 15(10), pages 1-20, May.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:10:p:3631-:d:816531
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    References listed on IDEAS

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    4. Árpád Tóth & Cecília Szigeti & Alex Suta, 2021. "Carbon Accounting Measurement with Digital Non-Financial Corporate Reporting and a Comparison to European Automotive Companies Statements," Energies, MDPI, vol. 14(18), pages 1-18, September.
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    Cited by:

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    2. Boris V. Malozyomov & Nikita V. Martyushev & Viktor Alekseevich Kukartsev & Vladislav Viktorovich Kukartsev & Sergei Vasilievich Tynchenko & Roman V. Klyuev & Nikolay A. Zagorodnii & Yadviga Aleksandr, 2023. "Study of Supercapacitors Built in the Start-Up System of the Main Diesel Locomotive," Energies, MDPI, vol. 16(9), pages 1-24, May.

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