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Dynamic programming improved online fuzzy power distribution in a demonstration fuel cell hybrid bus

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  • Zhou, Hongxu
  • Yu, Zhongwei
  • Wu, Xiaohua
  • Fan, Zhanfeng
  • Yin, Xiaofeng
  • Zhou, Lingxue

Abstract

The optimal energy management strategy of power sources plays a vital role in enhancing the efficiency and extending the driving range of fuel cell electric vehicles. However, current studies predominantly focus on optimizing energy management for standard driving cycles, which may differ significantly from actual driving cycles. This paper addresses this gap by developing a dynamic programming-based fuzzy logic strategy for optimizing energy management in a demonstration fuel cell hybrid bus. It begins by introducing the propulsion system of the fuel cell hybrid bus and the specific driving cycles used in the demonstration. Subsequently, a dynamic programming-based fuzzy logic strategy is derived by considering the relationship between fuel cell power, battery state of charge, and demand power from the optimal allocation strategy of dynamic programming, which is tailored to the unique characteristics of the demonstration driving cycles instead of a generic standard driving cycle. The effectiveness and real-time performance of the dynamic programming-based fuzzy logic strategy are then validated through offline simulation and hardware-in-the-loop simulation. The results highlight that the proposed method outperforms the original rule-based strategy regarding energy efficiency, particularly when the initial state of charge is low and the energy consumption per unit mileage of the driving cycle is high.

Suggested Citation

  • Zhou, Hongxu & Yu, Zhongwei & Wu, Xiaohua & Fan, Zhanfeng & Yin, Xiaofeng & Zhou, Lingxue, 2023. "Dynamic programming improved online fuzzy power distribution in a demonstration fuel cell hybrid bus," Energy, Elsevier, vol. 284(C).
    • Handle: RePEc:eee:energy:v:284:y:2023:i:c:s0360544223019436
    DOI: 10.1016/j.energy.2023.128549
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    References listed on IDEAS

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    1. Xie, Shaobo & Hu, Xiaosong & Xin, Zongke & Brighton, James, 2019. "Pontryagin’s Minimum Principle based model predictive control of energy management for a plug-in hybrid electric bus," Applied Energy, Elsevier, vol. 236(C), pages 893-905.
    2. Sulaiman, N. & Hannan, M.A. & Mohamed, A. & Majlan, E.H. & Wan Daud, W.R., 2015. "A review on energy management system for fuel cell hybrid electric vehicle: Issues and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 802-814.
    3. Song, Ke & Wang, Xiaodi & Li, Feiqiang & Sorrentino, Marco & Zheng, Bailin, 2020. "Pontryagin’s minimum principle-based real-time energy management strategy for fuel cell hybrid electric vehicle considering both fuel economy and power source durability," Energy, Elsevier, vol. 205(C).
    4. Perez-Dávila, Oriana & Álvarez Fernández, Roberto, 2023. "Optimization algorithm applied to extended range fuel cell hybrid vehicles. Contribution to road transport decarbonization," Energy, Elsevier, vol. 267(C).
    5. Wang, Yichun & Zhang, Yuanzhi & Zhang, Caizhi & Zhou, Jiaming & Hu, Donghai & Yi, Fengyan & Fan, Zhixian & Zeng, Tao, 2023. "Genetic algorithm-based fuzzy optimization of energy management strategy for fuel cell vehicles considering driving cycles recognition," Energy, Elsevier, vol. 263(PF).
    6. Li, Tianyu & Liu, Huiying & Wang, Hui & Yao, Yongming, 2020. "Hierarchical predictive control-based economic energy management for fuel cell hybrid construction vehicles," Energy, Elsevier, vol. 198(C).
    7. Wu, Yunna & Liu, Fangtong & He, Jiaming & Wu, Man & Ke, Yiming, 2021. "Obstacle identification, analysis and solutions of hydrogen fuel cell vehicles for application in China under the carbon neutrality target," Energy Policy, Elsevier, vol. 159(C).
    8. Bizon, Nicu, 2019. "Real-time optimization strategies of Fuel Cell Hybrid Power Systems based on Load-following control: A new strategy, and a comparative study of topologies and fuel economy obtained," Applied Energy, Elsevier, vol. 241(C), pages 444-460.
    9. Quan, Shengwei & Wang, Ya-Xiong & Xiao, Xuelian & He, Hongwen & Sun, Fengchun, 2021. "Real-time energy management for fuel cell electric vehicle using speed prediction-based model predictive control considering performance degradation," Applied Energy, Elsevier, vol. 304(C).
    10. Anselma, Pier Giuseppe & Belingardi, Giovanni, 2022. "Fuel cell electrified propulsion systems for long-haul heavy-duty trucks: present and future cost-oriented sizing," Applied Energy, Elsevier, vol. 321(C).
    11. İnci, Mustafa & Büyük, Mehmet & Demir, Mehmet Hakan & İlbey, Göktürk, 2021. "A review and research on fuel cell electric vehicles: Topologies, power electronic converters, energy management methods, technical challenges, marketing and future aspects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
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