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

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 sc...

Full description

Saved in:
Bibliographic Details
Published in:Energy (Oxford) Vol. 308; p. 132857
Main Authors: Zhang, Zhendong, He, Hongwen, Quan, Shengwei, Chen, Jinzhou, Han, Ruoyan
Format: Journal Article
Language:English
Published: Elsevier Ltd 01.11.2024
Subjects:
batteries
energy
Fuel cell
Heavy-duty vehicle
Hybrid system sizing
hydrogen
Multi-objective jellyfish swarm algorithm
transportation
Hybrid system sizing
Heavy-duty vehicle
Fuel cell
Multi-objective jellyfish swarm algorithm
ISSN:0360-5442
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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. •Multi-objective jellyfish swarm algorithm is introduced into the sizing procedure.•The equivalent hydrogen consumption combining degradation models.•The sizing procedure is conducted for the serial development under different vehicle weights.•Pareto optimization is introduced to solve the multi-objective problem of the dual-FCS architecture.•The upper-performance limit is obtained by dynamic programming algorithm.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0360-5442
DOI:10.1016/j.energy.2024.132857