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Optimal Energy Management Strategy for Repeat Path Operating Fuel Cell Hybrid Tram

Author

Listed:
  • Jaekwang Jung

    (Department of Mechanical Engineering, BK21 FOUR ERICA-ACE Center, Hanyang University, Ansan 15588, Republic of Korea)

  • Dongeon Kim

    (Department of Mechanical Engineering, BK21 FOUR ERICA-ACE Center, Hanyang University, Ansan 15588, Republic of Korea)

  • Liyue Yang

    (Department of Mechanical Engineering, BK21 FOUR ERICA-ACE Center, Hanyang University, Ansan 15588, Republic of Korea)

  • Namwook Kim

    (Department of Mechanical Engineering, BK21 FOUR ERICA-ACE Center, Hanyang University, Ansan 15588, Republic of Korea)

Abstract

This study focuses on minimizing fuel consumption of a fuel cell hybrid tram, operated with electric power from both the fuel cell stack and the energy storage system, by optimizing energy distribution between distinct energy sources. In the field of fuel cell hybrid system application, dealing with real-world optimal control implementation becomes more important. Some ‘online control’ strategies optimize energy management by measuring the current battery’s state and planning for future cycles. However, its dependence on stochastic processes remains a limitation for adapting ‘online control’ even when driving in the same way. In order to optimize energy distribution robustly during the tram’s repetitive cycle operation, we develop a practical control map with a fuel cell hybrid tram simulation model and conduct energy distribution. The control map is based on a mathematical equivalent consumption minimization strategy (ECMS) equation reflecting the characteristics of the fuel cell stack and electric cells. The comparison of fuel consumption with another practical control strategy optimized for a specific railway cycle shows that the suggested map-based optimal control achieves a reduction in fuel consumption while satisfying a boundary condition.

Suggested Citation

  • Jaekwang Jung & Dongeon Kim & Liyue Yang & Namwook Kim, 2024. "Optimal Energy Management Strategy for Repeat Path Operating Fuel Cell Hybrid Tram," Energies, MDPI, vol. 17(7), pages 1-12, March.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:7:p:1560-:d:1363121
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    References listed on IDEAS

    as
    1. Li, Qi & Wang, Tianhong & Li, Shihan & Chen, Weirong & Liu, Hong & Breaz, Elena & Gao, Fei, 2021. "Online extremum seeking-based optimized energy management strategy for hybrid electric tram considering fuel cell degradation," Applied Energy, Elsevier, vol. 285(C).
    2. Hou, Shengyan & Yin, Hai & Xu, Fuguo & Benjamín, Pla & Gao, Jinwu & Chen, Hong, 2023. "Multihorizon predictive energy optimization and lifetime management for connected fuel cell electric vehicles," Energy, Elsevier, vol. 266(C).
    3. Peng, Hujun & Li, Jianxiang & Löwenstein, Lars & Hameyer, Kay, 2020. "A scalable, causal, adaptive energy management strategy based on optimal control theory for a fuel cell hybrid railway vehicle," Applied Energy, Elsevier, vol. 267(C).
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