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Towards real-time capable optimal control for fuel cell vehicles using hierarchical economic MPC

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  • Haubensak, Lukas
  • Strahl, Stephan
  • Braun, Jochen
  • Faulwasser, Timm

Abstract

Fuel cell vehicles are predicted to play an important role in the electrification of heavy-duty transportation, hence the efficient operation of their powertrains is critical. Since the system dynamics of fuel cell systems are characterized by widespread time-scales (from electrochemistry to thermal processes), the implementation of optimization-based control methods poses several challenges. Control of systems with dynamics covering multiple time-scales leads to a trade-off between control performance and computational effort if solved with a conventional single-layer Model Predictive Control (MPC) scheme. One approach is to partition the problem into different time-scales and to construct a hierarchical architecture combining multiple control layers.

Suggested Citation

  • Haubensak, Lukas & Strahl, Stephan & Braun, Jochen & Faulwasser, Timm, 2024. "Towards real-time capable optimal control for fuel cell vehicles using hierarchical economic MPC," Applied Energy, Elsevier, vol. 366(C).
    • Handle: RePEc:eee:appene:v:366:y:2024:i:c:s0306261924006068
    DOI: 10.1016/j.apenergy.2024.123223
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    References listed on IDEAS

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    1. Wang, Xuechao & Chen, Jinzhou & Quan, Shengwei & Wang, Ya-Xiong & He, Hongwen, 2020. "Hierarchical model predictive control via deep learning vehicle speed predictions for oxygen stoichiometry regulation of fuel cells," Applied Energy, Elsevier, vol. 276(C).
    2. Jonas Breitinger & Mark Hellmann & Helerson Kemmer & Stephan Kabelac, 2023. "Automotive Fuel Cell Systems: Testing Highly Dynamic Scenarios," Energies, MDPI, vol. 16(2), pages 1-15, January.
    3. Xuerui Ma & Yong Zhang & Chengliang Yin & Shifei Yuan, 2017. "Multi-Objective Optimization Considering Battery Degradation for a Multi-Mode Power-Split Electric Vehicle," Energies, MDPI, vol. 10(7), pages 1-16, July.
    4. Carlo Cunanan & Manh-Kien Tran & Youngwoo Lee & Shinghei Kwok & Vincent Leung & Michael Fowler, 2021. "A Review of Heavy-Duty Vehicle Powertrain Technologies: Diesel Engine Vehicles, Battery Electric Vehicles, and Hydrogen Fuel Cell Electric Vehicles," Clean Technol., MDPI, vol. 3(2), pages 1-16, June.
    5. Teresa Donateo, 2023. "Semi-Empirical Models for Stack and Balance of Plant in Closed-Cathode Fuel Cell Systems for Aviation," Energies, MDPI, vol. 16(22), pages 1-40, November.
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