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Research on a Plug-In Hybrid Electric Bus Energy Management Strategy Considering Drivability

Author

Listed:
  • Ye Yang

    (Laboratory of Low Emission Vehicle, Beijing Institute of Technology, Beijing 100081, China
    Qing Gong College, North China University of Science and Technology, Tangshan 063000, China)

  • Youtong Zhang

    (Laboratory of Low Emission Vehicle, Beijing Institute of Technology, Beijing 100081, China)

  • Jingyi Tian

    (School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China)

  • Si Zhang

    (Qing Gong College, North China University of Science and Technology, Tangshan 063000, China)

Abstract

Plug-in hybrid electric buses (PHEBs) is some of the most promising products to address air pollution and the energy crisis. Considering the switching between different working modes often bring about sudden changes of the torque and the speed of different power sources, which may lead to the instability of the power output and affect the driving performance and ride comfort, it is of great significance to develop a real-time optimal energy management strategy for PHEBs to achieve the optimization of fuel economy and drivability. In this study, the proposed strategy includes an offline part and an online part. In the offline part, firstly, the energy conversion coefficient s ( t ) is optimized by linear weight particle swarm optimization algorithm (LinWPSO), then, the optimization results of s ( t ) are converted into a 2-dimensional look-up table. Secondly, combined with three typical driving cycle conditions, the gear-shifting correction and mode switching boundary parameters that affect the drivability of the vehicle are extracted by dynamic programming (DP) algorithm. In the online part, combined with the s ( t ), the gear-shifting correction and mode switching boundary parameters which are obtained through offline optimization, the real-time energy management strategy is proposed to solve the trade-off problem between minimizing the fuel consumption and improving the drivability and riding comfort. Finally, the proposed strategy is verified with simulation, the results show that the proposed strategy can guarantee the engine and the electric motor (EM) work in the high-efficiency area with optimal energy distribution while keeping drivability in the variation of driving circle. The overall performance is improved by 18.54% compared with the rule-based control strategy. The proposed strategy may provide theoretical support for the optimal control of PHEB.

Suggested Citation

  • Ye Yang & Youtong Zhang & Jingyi Tian & Si Zhang, 2018. "Research on a Plug-In Hybrid Electric Bus Energy Management Strategy Considering Drivability," Energies, MDPI, vol. 11(8), pages 1-22, August.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:8:p:2177-:d:164752
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    References listed on IDEAS

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    Cited by:

    1. Ye Yang & Youtong Zhang & Si Zhang & Jingyi Tian & Shaoyi Hu, 2019. "Control Strategy of Mode Transition with Engine Start in a Plug-in Hybrid Electric Bus," Energies, MDPI, vol. 12(15), pages 1-20, August.
    2. Yongjian Zhou & Rong Yang & Song Zhang & Kejun Lan & Wei Huang, 2023. "Optimization of Power-System Parameters and Energy-Management Strategy Research on Hybrid Heavy-Duty Trucks," Energies, MDPI, vol. 16(17), pages 1-21, August.
    3. Yang, Ye & Zhang, Youtong & Tian, Jingyi & Li, Tao, 2020. "Adaptive real-time optimal energy management strategy for extender range electric vehicle," Energy, Elsevier, vol. 197(C).
    4. Jean-Michel Clairand & Javier Rodríguez-García & Carlos Álvarez-Bel, 2018. "Electric Vehicle Charging Strategy for Isolated Systems with High Penetration of Renewable Generation," Energies, MDPI, vol. 11(11), pages 1-21, November.
    5. Fan, Likang & Wang, Yufei & Wei, Hongqian & Zhang, Youtong & Zheng, Pengyu & Huang, Tianyi & Li, Wei, 2022. "A GA-based online real-time optimized energy management strategy for plug-in hybrid electric vehicles," Energy, Elsevier, vol. 241(C).

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