Fault detection for polymer electrolyte membrane fuel cell stack by external magnetic field

An original non-invasive approach of fuel cell diagnosis is proposed in order to locate different kinds of faults in PEMFC stacks from magnetic field measurements. The method is based on the solving of an inverse linear problem linking the magnetic field signature outside of the fuel cell to the cur...

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Bibliographic Details
Published in:Electrochimica acta 2019-08, Vol.313, p.141-150
Main Authors: Ifrek, Lyes, Rosini, Sébastien, Cauffet, Gilles, Chadebec, Olivier, Rouveyre, Luc, Bultel, Yann
Format: Article
Language:English
Subjects:
Current density
Current density identification
Current distribution
Density distribution
Electric power
Electrokinetics
Electrolytic cells
Engineering Sciences
Fault detection
Fault diagnosis
Flooding
Fuel cells
Ill posed problems
Magnetic fields
Magnetic measurement
Magnetism
Magnetostatic inverse problem
Non-invasive diagnosis
PEM fuel cell
Proton exchange membrane fuel cells
Singular value decomposition
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Summary:An original non-invasive approach of fuel cell diagnosis is proposed in order to locate different kinds of faults in PEMFC stacks from magnetic field measurements. The method is based on the solving of an inverse linear problem linking the magnetic field signature outside of the fuel cell to the current density distribution inside. The searched solution is a linear combination of conservative current distribution obtained by a set of electrokinetic problems solved by a finite face element method. As the problem is ill-posed, the solution is stabilized using a truncated singular value decomposition. In this work, 30 sensors are used to perform the magnetic tomography of a PEMFC stack consisting of 100 cells with a large active area of 220 cm2. External magnetic measurement makes possible to identify 2D or 3D changes of current density distribution induced either by a cell flooding or membrane drying as well as by material degradation in a PEMFC stack. •Noninvasive technique for identifying the current distribution in a fuel cell from the external magnetic field.•Inverse problem modeling linking current density distribution to magnetic field measurements.•Identification of the current distribution in a faulty PEM fuel cell stack.•Validation of the methodology on a stack of 100 cells with an active area of 220 cm2.
ISSN:0013-4686
1873-3859
DOI:10.1016/j.electacta.2019.04.193