In this paper, a novel model for the dynamic reliability analysis of a polymer electrolyte membrane
fuel cell system is developed to account for multi-state dynamics and ageing. The modelling approach
involves the combination of physical and stochastic sub-models with shared variables. The physical
model consists of deterministic calculations of the system state described by variables such as
temperature, pressure, mass flow rates and voltage output. Additionally, estimated component
degradation rates are also taken into account. The non-deterministic model is implemented with
stochastic Petri nets which model the failures of the balance of plant components within the fuel cell
system. Using this approach, the effects of the operating conditions on the reliability of the system
were investigated. Monte Carlo simulations of the process highlighted a clear influence of both purging
and load cycles on the longevity of the fuel cell system.
Funding
Robust Lifecycle Design and Health Monitoring for Fuel-Cell Extended Performance (RESILIENCE)
Engineering and Physical Sciences Research Council
This paper was accepted for publication in the journal Reliability Engineering and System Safety and the definitive published version is available at https://doi.org/10.1016/j.ress.2021.107539.