Multi-parameter and multi-objective optimization of dual-fuel cell system heavy-duty vehicles: Sizing for serial development

Zhendong Zhang, Hongwen He, Shengwei Quan, Jinzhou Chen and Ruoyan Han

Energy, 2024, vol. 308, issue C

Abstract: Dual-fuel cell hybrid system provides an attractive propulsion option in transportation, especially for heavy-duty vehicles. However, the larger vehicle weight improves the sensitivity of power demand to road conditions and vehicle handling, making it a challenge to realize reasonable sizing. The scope of this work is to demonstrate a multi-objective and multi-parameter optimization for the serial development of the heavy-duty vehicle, powered by a dual-fuel cell hybrid system. Toward this end, a comprehensive modeling is presented combining the degradation model of the FC system and the battery system. The Pareto theory is introduced to evaluate the three-dimensional objectives involving the equivalent hydrogen consumption, the mass goal, and the vehicle dynamic, which is derived from different six-dimensional parameters under a dual-layer optimization approach. The brute force approach is not applicable in the presence of the curse of dimensionality arising from multi-parameter optimization. The proposed methodology offers a viable approach to acquiring rational sets of sizing solutions in the optimization space with high-dimensional parameters. Considering the serialization of products, the improved solution and the corresponding performance upper limit have be determined according to the proposed methodology under different weight levels as well.

Keywords: Fuel cell; Heavy-duty vehicle; Hybrid system sizing; Multi-objective jellyfish swarm algorithm (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:308:y:2024:i:c:s0360544224026318

DOI: 10.1016/j.energy.2024.132857

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