A probabilistic analysis method based on Noisy-OR gate Bayesian network for hydrogen leakage of proton exchange membrane fuel cell

Abstract

The proton exchange membrane fuel cell (PEMFC) is one of the crucial power units of the hydrogen vehicle. This work proposes a method based on the Noisy-OR gate Bayesian network to evaluate the hydrogen leakage probability of PEMFC. The generation mechanism of hydrogen leakage in fuel cells was analyzed using the fault tree theory. The conditional probability was determined using the Noisy-OR gate model in the Bayesian network, and the probability of hydrogen leakage in the fuel cell was 0.04. Through sensitivity analysis, the key factors that can cause hydrogen leaks in fuel cell were identified. The method proposed in this study can aid in PEMFC accident prevention and control strategies.