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Health-aware energy management strategy for fuel cell hybrid bus considering air-conditioning control based on TD3 algorithm

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  • Jia, Chunchun
  • Li, Kunang
  • He, Hongwen
  • Zhou, Jiaming
  • Li, Jianwei
  • Wei, Zhongbao

Abstract

The air-conditioning system (ACS), as a high-power component on the fuel cell hybrid electric bus (FCHEB), has a significant impact on the whole vehicle economy while maintaining comfortable temperature. Achieving cabin comfort in a way that reduces the whole vehicle operating cost is a great challenge. This task requires excellent coordination between the ACS and the on-board energy sources. Given that, this paper proposes an energy management strategy (EMS) with on-board energy sources health awareness considering air-conditioning control. Specifically, firstly, cabin comfort is combined with fuel cell/battery durability control to minimize total vehicle operating cost while satisfying cabin comfort. Secondly, the state-of-the-art twin delayed deep deterministic policy gradient algorithm is adopted to improve the training efficiency and optimization capability of the EMS to achieve the best power allocation. Finally, comparative analysis is performed to verify the effectiveness of the proposed EMS, and the results show that the proposed strategy can enhance training efficiency by 56.7% and decrease total operating cost by 8.58% compared to the benchmark strategy based on deep deterministic policy gradient.

Suggested Citation

  • Jia, Chunchun & Li, Kunang & He, Hongwen & Zhou, Jiaming & Li, Jianwei & Wei, Zhongbao, 2023. "Health-aware energy management strategy for fuel cell hybrid bus considering air-conditioning control based on TD3 algorithm," Energy, Elsevier, vol. 283(C).
    • Handle: RePEc:eee:energy:v:283:y:2023:i:c:s036054422301856x
    DOI: 10.1016/j.energy.2023.128462
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    References listed on IDEAS

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    Cited by:

    1. Cui, Can & Xue, Jing, 2024. "Energy and comfort aware operation of multi-zone HVAC system through preference-inspired deep reinforcement learning," Energy, Elsevier, vol. 292(C).
    2. Jia, Chunchun & He, Hongwen & Zhou, Jiaming & Li, Jianwei & Wei, Zhongbao & Li, Kunang, 2023. "A novel health-aware deep reinforcement learning energy management for fuel cell bus incorporating offline high-quality experience," Energy, Elsevier, vol. 282(C).

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