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Co-optimization on ecological adaptive cruise control and energy management of automated hybrid electric vehicles

Author

Listed:
  • Zhang, Fengqi
  • Qi, Zhicheng
  • Xiao, Lehua
  • Coskun, Serdar
  • Xie, Shaobo
  • Liu, Yongtao
  • Li, Jiacheng
  • Song, Ziyou

Abstract

Electrified drive systems and eco-driving technologies play a crucial role in promoting energy conservation. Eco-driving for hybrid electric vehicles(HEVs) is an intricate problem involving intertwined speed planning and energy management. In this context, an ecological adaptive cruise control (eco-ACC) and powertrain energy management strategy considering Signal Phase Timing Message (SPaT) can enhance both performance and real-time implementation. Specifically, this study develops a novel co-optimization method based on Pontryagin's minimum principle (PMP) that combines car-following control rules with the SPaT for a parallel HEV. The methodology involves the following steps: firstly, the parallel HEV model is established; secondly, the safe following distance model is constructed and the car-following control rules are devised to ensure safe driving. Subsequently, the co-optimization method based on PMP is then presented to simultaneously optimize the eco-driving problem of an ego-vehicle by converting the inter-vehicle distance constraint of the lead-vehicle into the limitation of the speed of the ego-vehicle. Finally, simulations are conducted under different scenarios for both fused SPaT and non-fused SPaT strategy. The simulation results demonstrate a reduction in fuel consumption by 6.27 % and 5.69 % in two different scenarios, respectively, and a shorter driving time for the fused SPaT strategy compared to the non-fused SPaT strategy.

Suggested Citation

  • Zhang, Fengqi & Qi, Zhicheng & Xiao, Lehua & Coskun, Serdar & Xie, Shaobo & Liu, Yongtao & Li, Jiacheng & Song, Ziyou, 2025. "Co-optimization on ecological adaptive cruise control and energy management of automated hybrid electric vehicles," Energy, Elsevier, vol. 314(C).
    • Handle: RePEc:eee:energy:v:314:y:2025:i:c:s0360544224033188
    DOI: 10.1016/j.energy.2024.133542
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    References listed on IDEAS

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    1. Tang, Tie-Qiao & Yi, Zhi-Yan & Zhang, Jian & Wang, Tao & Leng, Jun-Qiang, 2018. "A speed guidance strategy for multiple signalized intersections based on car-following model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 399-409.
    2. Tang, Wenbin & Wang, Yaqian & Jiao, Xiaohong & Ren, Lina, 2023. "Hierarchical energy management strategy based on adaptive dynamic programming for hybrid electric vehicles in car-following scenarios," Energy, Elsevier, vol. 265(C).
    3. Pan, Chaofeng & Huang, Aibao & Wang, Jian & Chen, Liao & Liang, Jun & Zhou, Weiqi & Wang, Limei & Yang, Jufeng, 2022. "Energy-optimal adaptive cruise control strategy for electric vehicles based on model predictive control," Energy, Elsevier, vol. 241(C).
    4. Zhang, Fengqi & Xiao, Lehua & Coskun, Serdar & Pang, Hui & Xie, Shaobo & Liu, Kailong & Cui, Yahui, 2023. "Comparative study of energy management in parallel hybrid electric vehicles considering battery ageing," Energy, Elsevier, vol. 264(C).
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