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Ageing-aware load following control for composite-cost optimal energy management of fuel cell hybrid electric vehicle

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  • Iqbal, Mehroze
  • Laurent, Julien
  • Benmouna, Amel
  • Becherif, Mohamed
  • Ramadan, Haitham S.
  • Claude, Frederic

Abstract

This paper aims to explore the viability of a novel frequency-driven load following control (LFC) as the dedicated energy management unit (EMU) of a commercial-grade fuel cell hybrid electric vehicle (FCHEV). The proposed EMU is envisioned to facilitate reliable performance under uncertain driving conditions, with mutual awareness towards hydrogen consumption and sources ageing. For that, a concept of composite-cost is introduced to establish an informed trade-off among sources ageing and hydrogen consumption. Thereafter, an adaptive framework is developed to tune the load following rule in an online manner subject to instantaneous minimization of the composite-cost. The conceptual application of proposed EMU is demonstrated in the simulation environment with parameters similar to those of a commercial vehicle. Two driving environments with distinct characteristics are extensively studied: a harsh US06 urban/suburban driving cycle and Artemis-Motorway cycle with an overall higher speed. The practical applicability of the proposed method is also validated via experimental test-bench with scaled-down hybrid power system. Detailed statistical analysis exhibits that the online-tuned variant of LFC with minimization preference given to the composite-cost provides the most appropriate trade-off by decreasing the composite-cost by 1.59%, hydrogen consumption by 0.35 g, and extending battery lifespan by 0.006%.

Suggested Citation

  • Iqbal, Mehroze & Laurent, Julien & Benmouna, Amel & Becherif, Mohamed & Ramadan, Haitham S. & Claude, Frederic, 2022. "Ageing-aware load following control for composite-cost optimal energy management of fuel cell hybrid electric vehicle," Energy, Elsevier, vol. 254(PA).
    • Handle: RePEc:eee:energy:v:254:y:2022:i:pa:s0360544222011367
    DOI: 10.1016/j.energy.2022.124233
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    Cited by:

    1. Mehroze Iqbal & Amel Benmouna & Frederic Claude & Mohamed Becherif, 2023. "Efficient and Reliable Power-Conditioning Stage for Fuel Cell-Based High-Power Applications," Energies, MDPI, vol. 16(13), pages 1-15, June.
    2. Bachir Zine & Haithem Bia & Amel Benmouna & Mohamed Becherif & Mehroze Iqbal, 2022. "Experimentally Validated Coulomb Counting Method for Battery State-of-Charge Estimation under Variable Current Profiles," Energies, MDPI, vol. 15(21), pages 1-15, November.
    3. Seydali Ferahtia & Hegazy Rezk & Rania M. Ghoniem & Ahmed Fathy & Reem Alkanhel & Mohamed M. Ghonem, 2023. "Optimal Energy Management for Hydrogen Economy in a Hybrid Electric Vehicle," Sustainability, MDPI, vol. 15(4), pages 1-19, February.
    4. Guo, Xiaokai & Yan, Xianguo & Chen, Zhi & Meng, Zhiyu, 2022. "Research on energy management strategy of heavy-duty fuel cell hybrid vehicles based on dueling-double-deep Q-network," Energy, Elsevier, vol. 260(C).
    5. Francesco Mocera & Aurelio Somà & Salvatore Martelli & Valerio Martini, 2023. "Trends and Future Perspective of Electrification in Agricultural Tractor-Implement Applications," Energies, MDPI, vol. 16(18), pages 1-36, September.
    6. Daniel de Wolf & Yves Smeers, 2023. "Comparison of Battery Electric Vehicles and Fuel Cell Vehicles [Comparaison des véhicules électriques à batterie et à hydrogène]," Post-Print hal-04367656, HAL.
    7. Wilberforce, Tabbi & Anser, Afaaq & Swamy, Jangam Aishwarya & Opoku, Richard, 2023. "An investigation into hybrid energy storage system control and power distribution for hybrid electric vehicles," Energy, Elsevier, vol. 279(C).

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