Acoustic emission as a function of polarisation: Diagnosis of polymer electrolyte fuel cell hydration state
•Acoustic emission technique to probe water formation and removal inside fuel cells.•Acoustic emission polarisation (AEP) in correlation with performance polarisation.•Identify the presence of water in flow channels based on cell polarisation level.•AEP validated by conventional electrochemical and...
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Veröffentlicht in: | Electrochemistry communications 2019-12, Vol.109, p.106582, Article 106582 |
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Sprache: | eng |
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Zusammenfassung: | •Acoustic emission technique to probe water formation and removal inside fuel cells.•Acoustic emission polarisation (AEP) in correlation with performance polarisation.•Identify the presence of water in flow channels based on cell polarisation level.•AEP validated by conventional electrochemical and current hold measurements.
Understanding water management is a crucial aspect in the development of improved polymer electrolyte fuel cells (PEFCs). Separating the performance degradation due to dehydration, water flooding and reactant starvation in PEFCs is a major challenge. In this study, acoustic emission (AE) analysis, a non-invasive and non-destructive diagnostic tool, is utilised to probe water formation and removal inside an operating fuel cell. In the acoustic emission as a function of polarisation (AEfP) method, AE activity from the PEFC is measured in terms of cumulative absolute AE energy (CAEE) hits during operation at discrete points on the polarisation curve. AEfP can identify the presence of liquid water in flow channels and correlate its formation and removal with the level of cell polarisation, and consequent internal temperature. Correlation between acoustic activity and water generation, supply and removal is achieved by varying current (polarisation), cathode air feed relative humidity (RH) and cell temperature, respectively. Features such as initial membrane hydration, liquid water formation, ‘flushing’ and the transition from ‘wet-channel’ to ‘dry-channel’ operation are identified using AE analysis, thereby providing a powerful and easy to implement diagnostic for PEFCs. |
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ISSN: | 1388-2481 1873-1902 |
DOI: | 10.1016/j.elecom.2019.106582 |