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Open AccessArticle

Rapid Fault Diagnosis of PEM Fuel Cells through Optimal Electrochemical Impedance Spectroscopy Tests

Department of Energy, Politecnico di Milano, Via Lambruschini 4, 20156 Milano, Italy
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Energies 2020, 13(14), 3643; https://doi.org/10.3390/en13143643
Received: 3 June 2020 / Revised: 6 July 2020 / Accepted: 9 July 2020 / Published: 15 July 2020
(This article belongs to the Special Issue Polymer Electrolyte Membrane Fuel Cell Systems)
The present paper is focused on proposing and implementing a methodology for robust and rapid diagnosis of PEM fuel cells’ faults using Electrochemical Impedance Spectroscopy (EIS). Accordingly, EIS tests have been first conducted on four identical fresh PEM fuel cells along with an aged PEMFC at different current density levels and operating conditions. A label, which represents the presence of a type of fault (flooding or dehydration) or the regular operation, is then assigned to each test based on the expert knowledge employing the cell’s spectrum on the Nyquist plot. Since the time required to generate the spectrum should be minimized and considering the notable difference in the time needed for carrying out EIS tests at different frequency ranges, the frequencies have been categorized into four clusters (based on the corresponding order of magnitude: >1 kHz, >100 Hz, >10 Hz, >1 Hz). Next, for each frequency cluster and each specific current density, while utilizing a classification algorithm, a feature selection procedure is implemented in order to find the combination of EIS frequencies utilizing which results in the highest fault diagnosis accuracy and requires the lowest EIS testing time. For the case of fresh cells, employing the cluster of frequencies with f > 10 Hz, an accuracy of 98.5 % is obtained, whereas once the EIS tests from degraded cells are added to the dataset, the achieved accuracy is reduced to 89.2 % . It is also demonstrated that, while utilizing the selected pipelines, the required time for conducting the EIS test is less than one second, an advantage that facilitates real-time in-operando diagnosis of water management issues. View Full-Text
Keywords: PEM fuel cells; fault diagnosis; electrochemical impedance spectroscopy; machine learning; feature selection PEM fuel cells; fault diagnosis; electrochemical impedance spectroscopy; machine learning; feature selection
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MDPI and ACS Style

Najafi, B.; Bonomi, P.; Casalegno, A.; Rinaldi, F.; Baricci, A. Rapid Fault Diagnosis of PEM Fuel Cells through Optimal Electrochemical Impedance Spectroscopy Tests. Energies 2020, 13, 3643. https://doi.org/10.3390/en13143643

AMA Style

Najafi B, Bonomi P, Casalegno A, Rinaldi F, Baricci A. Rapid Fault Diagnosis of PEM Fuel Cells through Optimal Electrochemical Impedance Spectroscopy Tests. Energies. 2020; 13(14):3643. https://doi.org/10.3390/en13143643

Chicago/Turabian Style

Najafi, Behzad; Bonomi, Paolo; Casalegno, Andrea; Rinaldi, Fabio; Baricci, Andrea. 2020. "Rapid Fault Diagnosis of PEM Fuel Cells through Optimal Electrochemical Impedance Spectroscopy Tests" Energies 13, no. 14: 3643. https://doi.org/10.3390/en13143643

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