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Quantitative assessment approach of fuel cell operating state of safety based on potential field method

The fuel cell holds significant promise for vehicle applications due to its low carbon footprint and high efficiency. Accurate assessment of the state of safety (SOS) of fuel cells is crucial for ensuring vehicle safety, given the electrochemical characteristics, structure, and material properties i...

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Bibliographic Details
Published in:Renewable energy 2025-01, Vol.238, p.121782, Article 121782
Main Authors: Zou, Weitao, Li, Jianwei
Format: Article
Language:English
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Summary:The fuel cell holds significant promise for vehicle applications due to its low carbon footprint and high efficiency. Accurate assessment of the state of safety (SOS) of fuel cells is crucial for ensuring vehicle safety, given the electrochemical characteristics, structure, and material properties involved. However, evaluating the safety performance of fuel cells is challenging, as it encompasses various factors such as mechanical, electrical, thermal, and chemical aspects, making quantitative SOS assessment difficult. Existing literature provides qualitative descriptions but lacks numerical quantification of the operational safety performance of fuel cell systems. To address this gap, this paper introduces, for the first time, a potential field method to quantitatively evaluate the operational safety of fuel cells. The model establishes a fuel cell behavior potential field by defining feasible regions for control or state variables, representing the mapping relationship between fuel cell behavior and the state of safety. Additionally, the proposed potential field model’s real-time performance is validated in a test case, demonstrating its feasibility and applicability for quantitatively assessing the fuel cell state of safety. •A potential field method is developed to quantitatively evaluate the fuel cell SOS.•The relationship between fuel cell behavior and the state of safety is established.•The fuel cell behavior potential field by defining feasible regions for variables.•The feasibility of the proposed method is demonstrated by real-time verification.
ISSN:0960-1481
DOI:10.1016/j.renene.2024.121782