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Development of a range-extended electric vehicle powertrain for an integrated energy systems research printed utility vehicle

Author

Listed:
  • Chambon, Paul
  • Curran, Scott
  • Huff, Shean
  • Love, Lonnie
  • Post, Brian
  • Wagner, Robert
  • Jackson, Roderick
  • Green, Johney

Abstract

Rapid vehicle and powertrain development has become essential to for the design and implementation of vehicles that meet and exceed the fuel efficiency, cost, and performance targets expected by today’s consumer while keeping pace with reduced development cycle and more frequent product releases. Recently, advances in large-scale additive manufacturing have provided the means to bridge hardware-in-the-loop (HIL) experimentation and preproduction mule chassis evaluation. This paper details the accelerated development of a printed range-extended electric vehicle (REEV) by Oak Ridge National Laboratory, by paralleling hardware-in-the-loop development of the powertrain with rapid chassis prototyping using big area additive manufacturing (BAAM). BAAM’s ability to accelerate the mule vehicle development from computer-aided design to vehicle build is explored. The use of a hardware-in-the-loop laboratory is described as it is applied to the design of a range-extended electric powertrain to be installed in a printed prototype vehicle. The integration of the powertrain and the opportunities and challenges it presents are described in this work. A comparison of offline simulation, HIL and chassis rolls results is presented to validate the development process. Chassis dynamometer results for battery electric and range extender operation are analyzed to show the benefits of the architecture.

Suggested Citation

  • Chambon, Paul & Curran, Scott & Huff, Shean & Love, Lonnie & Post, Brian & Wagner, Robert & Jackson, Roderick & Green, Johney, 2017. "Development of a range-extended electric vehicle powertrain for an integrated energy systems research printed utility vehicle," Applied Energy, Elsevier, vol. 191(C), pages 99-110.
  • Handle: RePEc:eee:appene:v:191:y:2017:i:c:p:99-110
    DOI: 10.1016/j.apenergy.2017.01.045
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    References listed on IDEAS

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    1. Hu, Xiaosong & Murgovski, Nikolce & Johannesson, Lars & Egardt, Bo, 2013. "Energy efficiency analysis of a series plug-in hybrid electric bus with different energy management strategies and battery sizes," Applied Energy, Elsevier, vol. 111(C), pages 1001-1009.
    2. He, Hongwen & Xiong, Rui & Zhao, Kai & Liu, Zhentong, 2013. "Energy management strategy research on a hybrid power system by hardware-in-loop experiments," Applied Energy, Elsevier, vol. 112(C), pages 1311-1317.
    3. Chen, Bo-Chiuan & Wu, Yuh-Yih & Tsai, Hsien-Chi, 2014. "Design and analysis of power management strategy for range extended electric vehicle using dynamic programming," Applied Energy, Elsevier, vol. 113(C), pages 1764-1774.
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    Cited by:

    1. 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.
    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. Wei, Changyin & Chen, Yong & Li, Xiaoyu & Lin, Xiaozhe, 2022. "Integrating intelligent driving pattern recognition with adaptive energy management strategy for extender range electric logistics vehicle," Energy, Elsevier, vol. 247(C).
    4. Wei, Changyin & Sun, Xiuxiu & Chen, Yong & Zang, Libin & Bai, Shujie, 2021. "Comparison of architecture and adaptive energy management strategy for plug-in hybrid electric logistics vehicle," Energy, Elsevier, vol. 230(C).
    5. Gokan May & Foivos Psarommatis, 2023. "Maximizing Energy Efficiency in Additive Manufacturing: A Review and Framework for Future Research," Energies, MDPI, vol. 16(10), pages 1-28, May.
    6. Trovão, João P. & Silva, Mário A. & Antunes, Carlos Henggeler & Dubois, Maxime R., 2017. "Stability enhancement of the motor drive DC input voltage of an electric vehicle using on-board hybrid energy storage systems," Applied Energy, Elsevier, vol. 205(C), pages 244-259.
    7. 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.
    8. Zhuang, Weichao & Li (Eben), Shengbo & Zhang, Xiaowu & Kum, Dongsuk & Song, Ziyou & Yin, Guodong & Ju, Fei, 2020. "A survey of powertrain configuration studies on hybrid electric vehicles," Applied Energy, Elsevier, vol. 262(C).

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