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Coordinated management of connected plug-in hybrid electric buses for energy saving, inter-vehicle safety, and battery health

Author

Listed:
  • Xie, Shaobo
  • Qi, Shanwei
  • Lang, Kun
  • Tang, Xiaolin
  • Lin, Xianke

Abstract

For plug-in hybrid electric vehicles, deeper battery discharge provides more electrical energy at a lower cost than fossil fuel, which reduces the overall energy consumption cost. However, it also accelerates battery degradation and increases the equivalent cost of battery life loss. Therefore, the battery depth of discharge (DOD) needs to be optimized to minimize the overall cost. For connected plug-in hybrid electric vehicles, the longitudinal velocity planning determines the energy demands, which directly affects the charging or discharging current to the battery and therefore affects DOD, aging, and fuel consumption as well. For connected plug-in hybrid electric buses running on fixed routes, in order to coordinate the velocity planning and battery health protection, this paper proposes a real-time energy management strategy aimed at achieving the minimum overall cost by optimizing the DOD and velocity planning. The proposed method is evaluated in an urban traffic scenario, and the goal of achieving optimal DOD is divided into a co-optimization problem over each moving horizon, where the velocity planning and energy management are traded off by minimizing the sum of driving safety cost, energy consumption cost, and equivalent cost of battery life loss. The results show that the proposed far-sighted economy-oriented methodology is superior to a short-sighted velocity planning and energy management method, and has an obvious advantage in the total cost compared with other conventional methods using a preset DOD. Moreover, the impacts of possible communication delays and prediction horizon lengths on the optimization performance and computational cost are investigated. The proposed method provides a promising management strategy for future connected and autonomous mobility design, which can mitigate battery capacity degradation and improve the fuel economy.

Suggested Citation

  • Xie, Shaobo & Qi, Shanwei & Lang, Kun & Tang, Xiaolin & Lin, Xianke, 2020. "Coordinated management of connected plug-in hybrid electric buses for energy saving, inter-vehicle safety, and battery health," Applied Energy, Elsevier, vol. 268(C).
  • Handle: RePEc:eee:appene:v:268:y:2020:i:c:s0306261920305407
    DOI: 10.1016/j.apenergy.2020.115028
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    References listed on IDEAS

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    6. Anselma, Pier Giuseppe & Kollmeyer, Phillip & Lempert, Jeremy & Zhao, Ziyu & Belingardi, Giovanni & Emadi, Ali, 2021. "Battery state-of-health sensitive energy management of hybrid electric vehicles: Lifetime prediction and ageing experimental validation," Applied Energy, Elsevier, vol. 285(C).
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    10. Cui, Wei & Cui, Naxin & Li, Tao & Cui, Zhongrui & Du, Yi & Zhang, Chenghui, 2022. "An efficient multi-objective hierarchical energy management strategy for plug-in hybrid electric vehicle in connected scenario," Energy, Elsevier, vol. 257(C).
    11. Vamsi Krishna Reddy, Aala Kalananda & Venkata Lakshmi Narayana, Komanapalli, 2022. "Meta-heuristics optimization in electric vehicles -an extensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    12. Lin Li & Serdar Coskun & Jiaze Wang & Youming Fan & Fengqi Zhang & Reza Langari, 2021. "Velocity Prediction Based on Vehicle Lateral Risk Assessment and Traffic Flow: A Brief Review and Application Examples," Energies, MDPI, vol. 14(12), pages 1-30, June.
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