Acoustic emission: Towards a real-time diagnosis technique for Proton Exchange Membrane Fuel Cell operation

Legros, B.; Thivel, Pierre-Xavier; Bultel, Yann; Boinet, Mickaël; Nogueira, R.P.

doi:10.1016/j.jpowsour.2010.07.045

Cited by 37 publications

(35 citation statements)

References 30 publications

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“…The crossover rates were determined for each individual cell inside the complete assembly and for the entire stack as well. Legros et al (2010) employed an acoustic emission (AE) technique to survey a PEM single cell under various operating conditions. The method is based on microsensing electrodes that are placed at appropriate locations in a single cell.…”

Section: Electrochemical Methodsmentioning

confidence: 99%

Experimental Methods for Investigating Fuel Cell Stacks

Bagotsky

2012

Fuel Cells

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Section: Electrochemical Methodsmentioning

confidence: 99%

Experimental Methods for Investigating Fuel Cell Stacks

Bagotsky

2012

Fuel Cells

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“…We can divide them in at least four categories. [65,70,71] Acoustic emission [72] Feature extraction. This category gathers a great variety of methods.…”

Section: Data Processingmentioning

confidence: 99%

“…Statistical treatment. When a correlation seems to exist between the measured variables it could be interesting to use statistical treatments such as Principle Component Analysis (PCA) [72,78,79]. In [79], PCA aims at visualizing the different parameters, their variations and correlations, and then allows the authors to identify which ones mostly contribute to the stack behavior.…”

Section: Data Processingmentioning

confidence: 99%

“…In [79], PCA aims at visualizing the different parameters, their variations and correlations, and then allows the authors to identify which ones mostly contribute to the stack behavior. This kind of post processing is also used in [72] for data discrimination between data coming from distinct origins for then categorizing them into different clusters. Here we can also quote data reduction [41] and data normalization [80] that are very helpful when a huge amount of data exist or when one wants to work with a small range of values.…”

Section: Data Processingmentioning

confidence: 99%

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Prognostics and Health Management of PEMFC – State of the art and remaining challenges

Jouin

Gouriveau

Hissel

et al. 2013

International Journal of Hydrogen Energy

187

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Fuel Cell systems (FC) represent a promising alternative energy source. However, even if this technology is close to being competitive, it is not ready for large scale industrial deployment: FC still must be optimized, particularly by increasing their limited lifespan. This involves a better understanding of wearing processes and requires emulating the behavior of the whole system. Furthermore, a new area of science and technology emerges: Prognostics and Health Management (PHM) appears to be of great interest to face the problems of health assessment and life prediction of FCs. According to this, the aim of this paper is to present the current state of the art on PHM of FCs, more precisely of Proton-Exchange Membrane Fuel Cells (PEMFC) stack. PHM discipline is described in order to depict the processing layers that allow early deviations detection, avoiding faults, deciding mitigation actions, and thereby increasing the useful life of FCs. On this basis, a taxonomy of existing works on PHM of PEMFC is given, highlighting open problems to be addressed. The whole enables getting a better understanding of remaining challenging issues in this area.

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“…Research activities have also addressed approaches that obtain additional data to detect the state of health of a fuel cell. These approaches include model based predictive control [8], analysis of total harmonic distortion [9] and acoustic emissions [10]. Additionally, there are many methods that convert measured or calculated data into a control strategy e.g.…”

Section: Introductionmentioning

confidence: 99%

Analysis Process for Different Polymere Electrolyte Fuel Cell Stacks to Derive a Control Strategy Based on Impedance Data

et al. 2014

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To further the development of polymer electrolyte membrane (PEM) fuel cells control strategies must be developed and optimized. In this study, an analysis process to derive a control strategy based on impedance data is developed and investigated. For this purpose an air cooled stack consisting of 12 cells and developed at Fraunhofer ISE was investigated. Impedance spectra were measured at different operating conditions to identify relevant frequencies at which an online control algorithm should be developed. A comparison of the impedance data between the analyzed stack and commercially available stacks of both air cooled and liquid cooled architectures suggest that the usable frequency ranges are independent of the stack. Hence, the presented analysis process is not limited to a specific stack design and yields a measure for the fuel cell's state of health that does not need information of a complete spectrum, but rather uses impedance data at a few discrete frequencies as control input.

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Acoustic emission: Towards a real-time diagnosis technique for Proton Exchange Membrane Fuel Cell operation

Cited by 37 publications

References 30 publications

Experimental Methods for Investigating Fuel Cell Stacks

Experimental Methods for Investigating Fuel Cell Stacks

Prognostics and Health Management of PEMFC – State of the art and remaining challenges

Analysis Process for Different Polymere Electrolyte Fuel Cell Stacks to Derive a Control Strategy Based on Impedance Data

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