Reliability assessment of a continuous-state fuel cell stack system with multiple degrading components

Abstract

A polymer electrolyte membrane fuel cell (PEMFC) stack is a multi-component system composed of continuously degrading fuel cells. The voltage degradation of the fuel cells causes the degradation of the stack system, which has two system-level degradation measures; the overall stack output voltage and the minimum voltage of individual cells. This paper develops a hierarchical Bayesian modeling and data analysis method to predict the reliability of a PEMFC stack system using the voltage degradation data collected from its fuel cell components. We introduce a two-term exponential model to describe the nonlinear voltage degradation paths of the fuel cell components, then builds a hierarchical Bayesian degradation model to predict the stack system reliability by taking a k-out-of-m:F system into account. Possible alternative modeling approaches are discussed with an in-depth comparison. This paper will contribute to the modeling and data analysis methods for continuous-state systems composed of continuous-state components.