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Multi-Objective Optimization Considering Battery Degradation for a Multi-Mode Power-Split Electric Vehicle

Author

Listed:
  • Xuerui Ma

    (National Engineering Laboratory for Automotive Electronic Control Technology, Shanghai Jiao Tong University, 800 Dongchuan Rd, Shanghai 200240, China)

  • Yong Zhang

    (National Engineering Laboratory for Automotive Electronic Control Technology, Shanghai Jiao Tong University, 800 Dongchuan Rd, Shanghai 200240, China)

  • Chengliang Yin

    (National Engineering Laboratory for Automotive Electronic Control Technology, Shanghai Jiao Tong University, 800 Dongchuan Rd, Shanghai 200240, China)

  • Shifei Yuan

    (National Engineering Laboratory for Automotive Electronic Control Technology, Shanghai Jiao Tong University, 800 Dongchuan Rd, Shanghai 200240, China)

Abstract

A multi-mode power-split (MMPS) hybrid electric vehicle (HEV) has two planetary gearsets and clutches/grounds which results in several operation modes with enhanced electric drive capability and better fuel economy. Basically, the battery storage system is involved in different operation modes to satisfy the power demand and minimize the fuel consumption, whereas the complicated operation modes with frequent charging/discharging will absolutely influence the battery life because of degradation. In this paper, firstly, we introduce the solid electrolyte interface (SEI) film growth model based on the previous study of the battery degradation principles and was verified according to the test data. We consider both the fuel economy and battery degradation as a multi-objective problem for MMPS HEV by normalization with a weighting factor. An instantaneous optimization is implemented based on the equivalent fuel consumption concept. Then the control strategy is implemented on a simulation framework integrating the MMPS powertrain model and the SEI film growth map model over some typical driving cycles, such as New European Driving Cycle (NEDC) and Urban Dynamometer Driving Schedule (UDDS). Finally, the result demonstrates that these two objectives are conflicting and the trade-off reduces the battery degradation with fuel sacrifice. Additionally, the analysis reveals how the mode selection will reflect the battery degradation.

Suggested Citation

  • Xuerui Ma & Yong Zhang & Chengliang Yin & Shifei Yuan, 2017. "Multi-Objective Optimization Considering Battery Degradation for a Multi-Mode Power-Split Electric Vehicle," Energies, MDPI, vol. 10(7), pages 1-16, July.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:7:p:975-:d:104355
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    References listed on IDEAS

    as
    1. Yong Zhang & Xuerui Ma & Chengliang Yin & Shifei Yuan, 2016. "Development and Simulation of a Type of Four-Shaft ECVT for a Hybrid Electric Vehicle," Energies, MDPI, vol. 9(3), pages 1-20, February.
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    Citations

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    Cited by:

    1. Wiesław Grzesikiewicz & Lech Knap & Michał Makowski & Janusz Pokorski, 2018. "Study of the Energy Conversion Process in the Electro-Hydrostatic Drive of a Vehicle," Energies, MDPI, vol. 11(2), pages 1-22, February.
    2. Zhang, Shuo & Hu, Xiaosong & Xie, Shaobo & Song, Ziyou & Hu, Lin & Hou, Cong, 2019. "Adaptively coordinated optimization of battery aging and energy management in plug-in hybrid electric buses," Applied Energy, Elsevier, vol. 256(C).
    3. Jarosław Wątróbski & Krzysztof Małecki & Kinga Kijewska & Stanisław Iwan & Artur Karczmarczyk & Russell G. Thompson, 2017. "Multi-Criteria Analysis of Electric Vans for City Logistics," Sustainability, MDPI, vol. 9(8), pages 1-34, August.
    4. López-Ibarra, Jon Ander & Gaztañaga, Haizea & Saez-de-Ibarra, Andoni & Camblong, Haritza, 2020. "Plug-in hybrid electric buses total cost of ownership optimization at fleet level based on battery aging," Applied Energy, Elsevier, vol. 280(C).
    5. Haubensak, Lukas & Strahl, Stephan & Braun, Jochen & Faulwasser, Timm, 2024. "Towards real-time capable optimal control for fuel cell vehicles using hierarchical economic MPC," Applied Energy, Elsevier, vol. 366(C).

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