Weighting Optimization for Fuel Cell Hybrid Vehicles: Lifetime-Conscious Component Sizing and Energy Management

Fuel economy and system durability are critical yet interdependent performance metrics for fuel cell hybrid vehicles (FCHVs). This paper devises an integrated framework for optimizing component sizing and energy management in a fuel cell/battery hybrid passenger vehicle. A unified cost function is proposed, combining fuel economy and system durability through a weighting coefficient, based on a comprehensive model of the hydrogen consumption and degradation characteristics of fuel cells and batteries. Utilizing the dynamic programming (DP) algorithm, the total cost is optimized to derive the optimal weighting factors and component sizing, effectively addressing the multi-objective optimization problem and balancing efficiency and durability. Furthermore, the impact of power prices on the optimal parameters is carefully examined. The simulation results indicate that a battery capacity of 44 Ah and a fuel cell maximum power of 80 kW represent the optimal sizing configuration. A weighting factor of 0.5 achieves the minimum equivalent total cost by effectively balancing fuel economy and system durability for the light-duty fuel cell passenger vehicle. Additionally, the battery price affects the weighting factor, indicating that future reductions in power source costs will shift focus away from system durability to fuel economy in FCHV optimization. These findings provide recommendations for FCHV manufacturers to advance the application of fuel cells in passenger vehicles.

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Publication Details

Journal
Applied Sciences
Published
2025-03-25
DOI
https://doi.org/10.3390/app15073586
Citations
2
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
1.37

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article

Weighting Optimization for Fuel Cell Hybrid Vehicles: Lifetime-Conscious Component Sizing and Energy Management

Hao Yuan, Jinfeng Feng, Hang Dong, Shuzhan Bai et al.
2 citations
Applied Sciences
Advanced Battery Technologies Research
1.37
article

Weighting Optimization for Fuel Cell Hybrid Vehicles: Lifetime-Conscious Component Sizing and Energy Management

Hao Yuan, Jinfeng Feng, Hang Dong, Shuzhan Bai, Sipeng Zhu, Shu Chen, Guoxiang Li, X. Xiao, Yujun Tang
article en
2 citations

Abstract

Fuel economy and system durability are critical yet interdependent performance metrics for fuel cell hybrid vehicles (FCHVs). This paper devises an integrated framework for optimizing component sizing and energy management in a fuel cell/battery hybrid passenger vehicle. A unified cost function is proposed, combining fuel economy and system durability through a weighting coefficient, based on a comprehensive model of the hydrogen consumption and degradation characteristics of fuel cells and batteries. Utilizing the dynamic programming (DP) algorithm, the total cost is optimized to derive the optimal weighting factors and component sizing, effectively addressing the multi-objective optimization problem and balancing efficiency and durability. Furthermore, the impact of power prices on the optimal parameters is carefully examined. The simulation results indicate that a battery capacity of 44 Ah and a fuel cell maximum power of 80 kW represent the optimal sizing configuration. A weighting factor of 0.5 achieves the minimum equivalent total cost by effectively balancing fuel economy and system durability for the light-duty fuel cell passenger vehicle. Additionally, the battery price affects the weighting factor, indicating that future reductions in power source costs will shift focus away from system durability to fuel economy in FCHV optimization. These findings provide recommendations for FCHV manufacturers to advance the application of fuel cells in passenger vehicles.

Applied SciencesVol. 15(7)
Shandong University (CN), City University of Hong Kong, Shenzhen Research Institute (CN), University of Bath (GB)
Natural Science Foundation of Shandong Province, Basic and Applied Basic Research Foundation of Guangdong Province
Openalex Percentile: Top 21%
Advanced Battery Technologies Research
1.37
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