Hydrogen crossover diagnosis for fuel cell stack: An electrochemical impedance spectroscopy based method

Li, Sida; Wei, Xuezhe; Jiang, Shangfeng; Yuan, Hao; Ming, Pingwen; Wang, Xueyuan; Dai, Haifeng

doi:10.1016/j.apenergy.2022.119884

Cited by 14 publications

(3 citation statements)

References 51 publications

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“…Fuel Cell. In the studies currently available, some fuel cell internal leakage diagnostic methods have been already developed, such as the electrochemical impedance spectroscopy (EIS), 182,183 the cross-current diagnostics, 184,185 the voltage difference diagnostics, 186,187 the cathode outlet hydrogen concentration diagnostics, 188,189 and the thermography diagnostics. 190,191 However, with advances in technology and increased complexity, diagnostic strategies have begun to move in a more advanced and intelligent phase.…”

Section: Model-based Leakage Diagnosismentioning

confidence: 99%

“…In the studies currently available, some fuel cell internal leakage diagnostic methods have been already developed, such as the electrochemical impedance spectroscopy (EIS), , the cross-current diagnostics, , the voltage difference diagnostics, , the cathode outlet hydrogen concentration diagnostics, , and the thermography diagnostics. , However, with advances in technology and increased complexity, diagnostic strategies have begun to move in a more advanced and intelligent phase. Figure shows a flowchart of three diagnostic methods for fuel cell internal leakage in FCVs: (1) the machine learning-based leakage diagnosis, (2) the signal processing-based leakage diagnosis, and (3) the leakage diagnosis based on sensor fusion and multimodal methods.…”

Section: Leakage Diagnosismentioning

confidence: 99%

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Comprehensive Review of Hydrogen Leakage in Relation to Fuel Cell Vehicles and Hydrogen Refueling Stations: Status, Challenges, and Future Prospects

Hu,

Gao,

Cheng

et al. 2024

Energy Fuels

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As fuel cell vehicles (FCVs) are increasingly put on the market and hydrogen refueling stations (HRSs) are built accordingly, fatal accidents caused by explosion due to hydrogen leakage are reported and have become a critical issue. The explosion results from complicated processes associated with the so-called hydrogen jet and diffusion when the hydrogen leaks from FCVs or HRSs, demonstrating its sophisticated characteristics and presenting significant technical challenges. Recently, particularly in the past a few years, researchers have established a variety of theoretical models to reveal the relevant mechanisms and introduced a series of monitoring/diagnostic approaches to detect and control the relevant hazards. This comprehensive review summarizes the major research outcomes and particularly the state-of-the-art progresses in relation to hydrogen leakage in FCVs and HRSs, including (1) subsonic jets, (2) underexpanded jets, (3) hydrogen diffusion behavior, (4) hazard reduction methods for confined and free spaces, (5) four types of widely used hydrogen detection technologies, and (6) the application of hydrogen leakage diagnostic methods in different systems. An insight of the review is that research on hydrogen leakage related to FCVs and HRSs should be combined with the relevant realistic characteristics. The characteristics of hydrogen jets generated in real gaps are discussed, and hazard reduction methods are proposed based on the characteristics of hydrogen diffusion in different confined and free spaces. It is suggested that, in order to integrate and evaluate multiple sensor data points and more accurately determine the leakage location and the leakage level, artificial intelligence technologies could be introduced to resolve the issues encountered currently.

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Section: Model-based Leakage Diagnosismentioning

confidence: 99%

Section: Leakage Diagnosismentioning

confidence: 99%

Comprehensive Review of Hydrogen Leakage in Relation to Fuel Cell Vehicles and Hydrogen Refueling Stations: Status, Challenges, and Future Prospects

Hu,

Gao,

Cheng

et al. 2024

Energy Fuels

View full text Add to dashboard Cite

show abstract

“…Existen dos medidas principales para evaluar la convergencia de un algoritmo, la velocidad de convergencia y la tasa de convergencia. La primera, la velocidad de convergencia mide el número de iteraciones necesarias para alcanzar una solución óptima [90], [91], [92], [93], [94], [95], [96], [97], [98], [99], [100]. La segunda, la tasa de convergencia, se calcula como la desviación estándar de los valores de la solución que el algoritmo encontró en un número determinado de búsquedas bajo en las mismas condiciones; si la desviación estándar es cercana a cero, la convergencia del algoritmo es mejor [101].…”

Section: Figura 6 Diagrama De Bloques General De Un Algoritmo De Opti...unclassified

Contribuciones al modelado y diagnóstico de fallos en PEMFC para mejorar la fiabilidad en sistemas híbridos renovables

Ariza Chacón

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Com a resultat de la validació d'aquest model, en una primera simulació usant dades reals de funcionament corresponents a 1500 segons, l'error de simulació va ser del 2,21% en el senyal de tensió, del 1,97% en el senyal de temperatura i un error mitjà del 2,09%. En un segon conjunt de dades d'una mica més de 2.500 segons de funcionament, l'error de simulació va ser del 2,40% i del 1,96% per als senyals de tensió i temperatura, respectivament. S'estima que l'error mitjà de simulació per a tots dos senyals i condicions de funcionament similars és inferior al 2,5%.

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Online EIS Evaluation of PEM Electrolyzer Powered by LLC Resonant Converter

Jing,

Li,

Sun

2024

Springer Proceedings in Physics

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Hydrogen crossover diagnosis for fuel cell stack: An electrochemical impedance spectroscopy based method

Cited by 14 publications

References 51 publications

Comprehensive Review of Hydrogen Leakage in Relation to Fuel Cell Vehicles and Hydrogen Refueling Stations: Status, Challenges, and Future Prospects

Comprehensive Review of Hydrogen Leakage in Relation to Fuel Cell Vehicles and Hydrogen Refueling Stations: Status, Challenges, and Future Prospects

Contribuciones al modelado y diagnóstico de fallos en PEMFC para mejorar la fiabilidad en sistemas híbridos renovables

Online EIS Evaluation of PEM Electrolyzer Powered by LLC Resonant Converter

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