2D and 3D fault basis for fuel cell diagnosis by external magnetic field measurements

Ifrek, Lyes; Cauffet, Gilles; Chadebec, Olivier; Bultel, Yann; Rosini, Sébastien; Rouveyre, Luc

doi:10.1051/epjap/2017160468

Cited by 11 publications

(8 citation statements)

References 11 publications

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“…This single array of sensors is moved along the stack length to perform measurements on three different locations along z-axis of the stack (Fig. 2) [37]. The sensors orientation is chosen in order to mainly measure the magnetic field due to the heterogeneity of the current density distribution [35].…”

Section: Magnetic Field Device Descriptionmentioning

confidence: 99%

“…We conclude that the current density distribution basis should contain a set of current loop configurations. [37]. This approach has been already used by Le Ny et al [35,36].…”

Section: Direct Problemmentioning

confidence: 99%

“…To go further, this approach has been improved to be sensitive to more localized faults involving only few adjacent cells in a stack and by proposing an original 3D faults identification method. An inverse model of the Biot and Savart law was then developed, allowing the 3D reconstruction of current density in a fuel cell from external measurements of the magnetic field [37]. The developed tool is validated on a large PEMFC stack that consists of a stack of 100 cells with an active cell area of 220 cm 2 (Fig.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

Ifrek

Rosini

Cauffet

et al. 2019

Electrochimica Acta

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Luc Rouveyre, et al.. Fault detection for polymer electrolyte membrane fuel cell stack by external magnetic field. Electrochimica Acta, Elsevier, 2019, 313, pp. Abstract: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 2 magnetic tomography of a PEMFC stack consisting of 100 cells with a large active area of 220 cm 2 . 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.

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Section: Magnetic Field Device Descriptionmentioning

confidence: 99%

“…We conclude that the current density distribution basis should contain a set of current loop configurations. [37]. This approach has been already used by Le Ny et al [35,36].…”

Section: Direct Problemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

Ifrek

Rosini

Cauffet

et al. 2019

Electrochimica Acta

Self Cite

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“…Defects and the resultant deviation of currents in an FC can cause serious accidents. In the PEFC structure in particular, MEA defects can arise because of external factors such as thermal stress, chemical expansion, and long-term use, all of which pose serious harm to the function of PEFCs [2]. Consequently, nondestructive inspection of MEA defects is necessary for monitoring the conditions of FCs.…”

Section: Introductionmentioning

confidence: 99%

Estimating Defects in a Faulty Polymer Electrolyte Fuel Cell Stack Using a Level-Set Approach with Charge Simulation Methods

et al. 2020

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Polymer electrolyte fuel cells (PEFCs) have tremendous potential as an energy source be- cause of high efficiency and low pollutant emission. Although a membrane electrode assembly (MEA) is core for power generation, it has been reported that the MEA is often damaged due to chemical reactions. Therefore, methods for estimating defects in the MEA are necessary to ensure the safety of the PEFCs. This study proposes a level set-based approach for estimating defects in the MEA of the PEFC stack. The current density in the faulty PEFC is calculated using a charge simulation method. Based on the measured magnetic fields exterior to the PEFC, the shape of the defects in the MEA is identified by updating the level set function. The experimental results show that the proposed method can be used for reconstructing the shape of defects in the MEA.

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“…However, there was a problem in that the estimated regions came to be oversmoothed due to regularization. Ifrek et al examined the current density both in a healthy fuel cell and in a faulty fuel cell by singular value decomposition of a discretized Biot-Savart operator [5]. Although this method is able to model the current density of the fuel cell, it cannot precisely detect the size or shape of defects.…”

Section: Introductionmentioning

confidence: 99%

Level Set Method-Based Identification of Locations and Shapes of Fuel Cell Defects

Miyoshi

Nara

Gotoh

et al. 2018

SICE Journal of Control, Measurement, and System Integration

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Nondestructive inspection of the sizes and positions of defect regions in a fuel cell is an indispensable task in order to ensure their practical use. In the present paper, a level set method for estimating the defects in a membrane electrode assembly (MEA) in fuel cells is proposed. Boundaries of the defects in the MEA are represented by a zero contour of a level set function. By updating the function, the shapes and positions of the defect regions can be identified. A cost function for updating the level set function consists of the mean squared error between the magnetic fields computed by a 2-D model and sensor data and the regularization terms for the estimated shapes. The magnetic fields were measured using magnetic impedance sensors. The effectiveness of the proposed method is demonstrated through numerical simulations and experiments.

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2D and 3D fault basis for fuel cell diagnosis by external magnetic field measurements

Cited by 11 publications

References 11 publications

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

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

Estimating Defects in a Faulty Polymer Electrolyte Fuel Cell Stack Using a Level-Set Approach with Charge Simulation Methods

Level Set Method-Based Identification of Locations and Shapes of Fuel Cell Defects

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