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Adaptive brake energy recovery strategy considering traffic information

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  • Zhao, Haiyan
  • Xie, Hongbin
  • Zhao, Yan
  • Lu, Xinghao
  • Gao, Bingzhao
  • Chen, Hong

Abstract

In order to improve the adaptability of the braking energy recovery process of intelligent vehicle, a traffic information-based adaptive braking strategy is proposed in this paper. In the multi-objective optimization framework, driving safety constraints, traffic law limitations, comfort requirements, and energy recovery efficiency are integrated into consideration. The terminal demands of the braking objectives are transformed into a constraint problem for a model predictive controller with a decreasing sampling distance. Traffic information, along with the demands of comfort and safety, are transformed into real-time torque thresholds through the model and state information of vehicle. The real-time braking torque range is updated through the set of thresholds, which is dynamically adjusted by a combination of real-time road condition information and braking objectives to ensure the adaptability of various driving conditions. The optimal motor and hydraulic torque are obtained by optimizing within the real-time and dynamic range of torque constraints. Several scenarios are given under co-simulation of CarSim and Matlab/Simulink. The results show that the proposed adaptive method is able to ensure safety and meet traffic regulations in different driving conditions compared to the energy-efficient speed optimization strategy, and the SOC increased by 6% compared to the rule-based strategy, verifying the effectiveness of the proposed method.

Suggested Citation

  • Zhao, Haiyan & Xie, Hongbin & Zhao, Yan & Lu, Xinghao & Gao, Bingzhao & Chen, Hong, 2025. "Adaptive brake energy recovery strategy considering traffic information," Energy, Elsevier, vol. 321(C).
    • Handle: RePEc:eee:energy:v:321:y:2025:i:c:s0360544225009880
    DOI: 10.1016/j.energy.2025.135346
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    References listed on IDEAS

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