主催: 一般社団法人 日本機械学会
会議名: 2024年度 年次大会
開催日: 2024/09/08 - 2024/09/11
Polymer electrolyte fuel cell (PEFC) usually consist of tens to hundreds of layers of membrane electrode assemblies (MEAs) to obtain the required electrical output. A defect in one of the MEAs in the stack can significantly degrade the performance of the entire stack. Therefore, we propose a non-contact detection method for detecting defects caused by electrolyte breakage, poor electrical contact between parts, and the presence of insulators after the stack is assembled. In this study, we attempted to detect defects inside a PEFC stack consisting of two layers of MEAs by using magnetic sensors. The magnetic field around the stack generated during power generation was measured, and the current distribution in the MEA was estimated by inverse problem analysis based on sparse modeling theory. As a result, the current distribution of each of the two stacked MEAs was obtained separately, and the location of a defect with dimensions of 10 mm × 10 mm was successfully identified from the current distribution. The purpose of this study is to apply this method to the inspection process of products at the time of shipment, thereby contributing to quality assurance and yield improvement during production.