Development and optimization of a new EIS technique for diagnosis of automotive fuel cells

Abstract

The proton exchange membrane fuel cell (PEMFC) has been identified as a promising automotive power source, given its high efficiency and zero-emission characteristics. Despite these favorable attributes, the practical application of PEMFCs at large scale is constrained by their limited durability and lifespan. Complex automotive operating conditions significantly accelerate fuel cell aging, and result in diverse degradation mechanisms that require thorough inclusion for effective management. This study presents a noble measurement technique that enables impedance measurement in PEMFCs at regular intervals over a prolonged period of time without requiring human intervention. The proposed technique is titled accelerated electrochemical impedance spectroscopy (AEIS), derived from conventional EIS. By utilizing this technique, impedance measurements can be obtained repeatedly, providing a more comprehensive understanding of the degradation mechanisms of PEMFCs under dynamic operating conditions, which is essential for the fault diagnosis of fuel cell vehicles (FCEVs). An equivalent circuit model is developed to mimic the complex electrochemical behavior of the PEMFC. Automation of the measurement technique is accomplished by developing a Python model. The obtained AEIS data is fitted by utilizing the non-linear least square method (NLLS). Results shows the potentiality that, by continuously acquiring impedance measurements over a prolonged period of time, multiple degradation mechanisms occurring in the PEMFC can be recognized.