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Optimal sizing and adaptive energy management of a novel four-wheel-drive hybrid powertrain

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  • Ju, Fei
  • Zhuang, Weichao
  • Wang, Liangmo
  • Zhang, Zhe

Abstract

Hybrid powertrain technology must be applied to sport utility vehicles (SUVs) to meet stringent fuel economy and emissions standards. As an essential attribute of SUV, four-wheel-drive (4WD) offers flexible torque arrangement and results in safe and powerful driving under off-road conditions. In this paper, we propose a novel compound 4WD hybrid powertrain by adding an extra output shaft to a conventional power-split hybrid electric vehicle. By connecting two output shafts to the front and rear axles, this hybrid powertrain could deliver the engine power to four wheels simultaneously, while maintaining the electrical continuously variable transmission (ECVT) function. The dynamics, modeling and system characteristics of the compound 4WD hybrid powertrain are presented firstly. Using an integrated optimization framework to optimize components’ sizes, the proposed 4WD hybrid powertrain indicates 36.22% and 13.82% fuel economy improvements than conventional 4WD SUV in city and highway cycles, respectively. Since it is difficult to implement the DP in real-time controller, we present an adaptive equivalent consumption minimization strategy (A-ECMS), whose equivalent factor (EF) is constrained by its theoretical extremum. Finally, simulation results show A-ECMS achieves better fuel economy than regular ECMS.

Suggested Citation

  • Ju, Fei & Zhuang, Weichao & Wang, Liangmo & Zhang, Zhe, 2019. "Optimal sizing and adaptive energy management of a novel four-wheel-drive hybrid powertrain," Energy, Elsevier, vol. 187(C).
    • Handle: RePEc:eee:energy:v:187:y:2019:i:c:s0360544219317025
    DOI: 10.1016/j.energy.2019.116008
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    Cited by:

    1. Deng, Huifan & Zhao, Youqun & Feng, Shilin & Wang, Qiuwei & Zhang, Chenxi & Lin, Fen, 2021. "Torque vectoring algorithm based on mechanical elastic electric wheels with consideration of the stability and economy," Energy, Elsevier, vol. 219(C).
    2. Zhuang, Weichao & Li, Jinhui & Ju, Fei & Li, Bingbing & Liu, Haoji & Yin, Guodong, 2024. "Dual-objective eco-routing strategy for vehicles with different powertrain types," Energy, Elsevier, vol. 293(C).
    3. Yang, Yalian & Li, Pengshuai & Pei, Huanxin & Zou, Yunge, 2022. "Design of all-wheel-drive power-split hybrid configuration schemes based on hierarchical topology graph theory," Energy, Elsevier, vol. 242(C).
    4. Ju, Fei & Zhuang, Weichao & Wang, Liangmo & Zhang, Zhe, 2020. "Comparison of four-wheel-drive hybrid powertrain configurations," Energy, Elsevier, vol. 209(C).
    5. Ali M. Jasim & Basil H. Jasim & Florin-Constantin Baiceanu & Bogdan-Constantin Neagu, 2023. "Optimized Sizing of Energy Management System for Off-Grid Hybrid Solar/Wind/Battery/Biogasifier/Diesel Microgrid System," Mathematics, MDPI, vol. 11(5), pages 1-34, March.
    6. Pei Zhang & Xianpan Wu & Changqing Du & Hongming Xu & Huawu Wang, 2020. "Adaptive Equivalent Consumption Minimization Strategy for Hybrid Heavy-Duty Truck Based on Driving Condition Recognition and Parameter Optimization," Energies, MDPI, vol. 13(20), pages 1-20, October.

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