학술논문

Fuel Cell Stochastic Deterioration Modeling for Energy Management in a Multi-stack System
Document Type
Conference
Source
2022 13th International Conference on Reliability, Maintainability, and Safety (ICRMS) Reliability, Maintainability, and Safety (ICRMS), 2022 13th International Conference on. :104-108 Aug, 2022
Subject
Aerospace
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
General Topics for Engineers
Nuclear Engineering
Power, Energy and Industry Applications
Robotics and Control Systems
Transportation
Degradation
Fuel cells
Stochastic processes
Behavioral sciences
Trajectory
Safety
Random variables
Fuel cell
load-dependent deterioration modeling
gamma process
random effects
Language
ISSN
2575-2642
Abstract
Fuel cells are promising clean power sources which use hydrogen and oxygen to generate electricity. However, the limited durability that is decided by various degradation phenomena remains one of the main barriers hindering their commercialization. Fuel cell deterioration modeling contributes to model and reproducing fuel cell deterioration behaviors, thus serving as a key step to decreasing fuel cell system deterioration. Fuel cell deterioration behavior is characterized by two main features, namely, load-dependent and stack-to-stack deterioration heterogeneity. A Gamma process with random effect-based deterioration model is used to account for the above deterioration features of fuel cells. Different types of random effects are introduced to the studied Gamma process on its scale parameter, taken as a random variable following a gamma law. Fuel cell degradation trajectories are studied by the developed deterioration models using the Monte Carlo simulation method. The lifetime distributions of the proposed models are analyzed for investigating their deterioration behavior.