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Powertrain Optimization for Electric Buses under Optimal Energy-Efficient Driving

Author

Listed:
  • Alexander Koch

    (Institute of Automotive Technology, Technical University of Munich, 85748 Garching, Germany)

  • Olaf Teichert

    (TUMCREATE Ltd., Singapore 138602, Singapore)

  • Svenja Kalt

    (Institute of Automotive Technology, Technical University of Munich, 85748 Garching, Germany)

  • Aybike Ongel

    (TUMCREATE Ltd., Singapore 138602, Singapore)

  • Markus Lienkamp

    (Institute of Automotive Technology, Technical University of Munich, 85748 Garching, Germany
    TUMCREATE Ltd., Singapore 138602, Singapore)

Abstract

State of the art powertrain optimization compares the energy consumption of different powertrain configurations based on simulations with fixed driving cycles. However, this approach might not be applicable to future vehicles, since speed advisory systems and automated driving functions offer the potential to adapt the speed profile to minimize energy consumption. This study aims to investigate the potential of powertrain optimization with respect to energy consumption under optimal energy-efficient driving for electric buses. The optimal powertrain configurations of the buses under energy-efficient driving and their respective energy consumptions are obtained using powertrain-specific optimized driving cycles and compared with those of human-driven unconnected buses and buses with non-powertrain-specific optimal speed profiles. Based on the results, new trends in the powertrain design of vehicles under energy-efficient driving are derived. The optimized driving cycles are calculated using a dynamic programming approach. The evaluations were based on the fact that the buses under energy-efficient driving operate in dedicated lanes with vehicle-to-infrastructure (V2I) communication while the unconnected buses operate in mixed traffic. The results indicate that deviating from the optimal powertrain configuration does not have a significant effect on energy consumption for optimized speed profiles; however, the energy savings from an optimized powertrain configuration can be significant when ride comfort is considered. The connected buses under energy-efficient driving operating in dedicated lanes may reduce energy consumption by up to 27% compared to human-driven unconnected buses.

Suggested Citation

  • Alexander Koch & Olaf Teichert & Svenja Kalt & Aybike Ongel & Markus Lienkamp, 2020. "Powertrain Optimization for Electric Buses under Optimal Energy-Efficient Driving," Energies, MDPI, vol. 13(23), pages 1-19, December.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:23:p:6451-:d:457635
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    References listed on IDEAS

    as
    1. Egbue, Ona & Long, Suzanna, 2012. "Barriers to widespread adoption of electric vehicles: An analysis of consumer attitudes and perceptions," Energy Policy, Elsevier, vol. 48(C), pages 717-729.
    2. Francesco Bottiglione & Stefano De Pinto & Giacomo Mantriota & Aldo Sorniotti, 2014. "Energy Consumption of a Battery Electric Vehicle with Infinitely Variable Transmission," Energies, MDPI, vol. 7(12), pages 1-21, December.
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    Cited by:

    1. Muhammad Azam & Sitti Asmah Hassan & Othman Che Puan, 2022. "Autonomous Vehicles in Mixed Traffic Conditions—A Bibliometric Analysis," Sustainability, MDPI, vol. 14(17), pages 1-34, August.
    2. Alexander Koch & Lorenzo Nicoletti & Thomas Herrmann & Markus Lienkamp, 2022. "Implementation and Analyses of an Eco-Driving Algorithm for Different Battery Electric Powertrain Topologies Based on a Split Loss Integration Approach," Energies, MDPI, vol. 15(15), pages 1-29, July.
    3. Pier Giuseppe Anselma, 2021. "Optimization-Driven Powertrain-Oriented Adaptive Cruise Control to Improve Energy Saving and Passenger Comfort," Energies, MDPI, vol. 14(10), pages 1-28, May.
    4. Aissam Riad Meddour & Nassim Rizoug & Patrick Leserf & Christopher Vagg & Richard Burke & Cherif Larouci, 2023. "Optimization of the Lifetime and Cost of a PMSM in an Electric Vehicle Drive Train," Energies, MDPI, vol. 16(13), pages 1-27, July.

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