Defect detection inside Polymer Electrolyte Fuel Cell Stack by magnetic field measurement

Abstract

The aim of this study is to detect defects in polymer electrolyte fuel cells (PEFCs) stack containing two layers of MEA (Membrane Electrode Assembly) by a non-invasive method in a simple and instant manner. In this study, the magnetic flux density calculated by electromagnetic field analysis by the 3D-finite element method was analyzed by inverse problem analysis based on sparse modeling, and the current distribution inside the fuel cell was estimated. Assuming a two-layer stack consisting of a defective MEA with a defect of 10 mm × 10 mm in the electrode of a 50 mm × 50 mm MEA and a normal MEA, the current distribution of each MEA is estimated by inverse problem analysis based on sparse modeling theory. As a result, the estimated current value of the defect position in the defective MEA was 0.00A, and the estimated current value of the other positions was 0.12A, and the defect position could be clearly identified.