Proton exchange membrane fuel cells (PEMFCs) have been recognized as a promising power generation source for a wide range of automotive, stationary, and portable electronic applications. However, the durability of PEMFCs remains as one of the key barriers to their wide commercialization. The membrane electrode assembly (MEA) as a central part of a PEMFC, which consists of a proton exchange membrane with a catalyst layer (CL) and gas diffusion layer (GDL) on each side, is subject to failure and degradation in long-running and cycling load conditions. The real-time monitoring of the degradation evolution process through experimental techniques is challenging. Therefore, different numerical modeling approaches were proposed in the literature to assist the understanding of the degradation mechanisms in PEMFCs. To provide modeling progress in the addressed field, this paper briefly discusses the different degradation mechanisms occurring in the MEA. In particular, we present a detailed review of MEA degradation modeling research work, with special attention paid to the physical-based models (mechanistic models). Following the most recent relevant literature, the results showed that the combination of microstructure component models with macro-scale comprehensive PEMFC models provides a better understanding of degradation mechanisms when compared to single-scale degradation models. In this sense, it is concluded that in order to develop an accurate and efficient predictive degradation model, the different relevant scales ranging from nano- to macro-sized scales should be considered, and coupling techniques for multiscale modeling have to be advanced. Finally, the paper summarizes the degradation models for different MEA components. It is highlighted that the GDL chemical degradation models that describe damage accumulation are relatively limited. The paper provides a useful reference for the recent developments in the MEA degradation modeling of PEMFCs.

The current limitations of air-cooled proton exchange membrane fuel cells (AC-PEMFCs) in water and heat management remain a major obstacle to their commercialization. A 90 cm² full-size AC-PEMFC multi-physical field-coupled numerical model was constructed; isothermal and non-isothermal calculations were performed to explore the effects of univariate and multivariate variables on cell performance, respectively. The isothermal results indicate that lower temperature is beneficial to increase the humidity of MEA, and distribution uniformity at lower stoichiometric ratios and lower temperatures is better. The correlation between current density distribution and temperature, water content, and concentration distribution shows that the performance of AC-PEMFCs is influenced by multiple factors. Notably, under high current operation, the large heat generation may lead to high local temperature and performance decline, especially in the under-channel region with drier MEA. The higher stoichiometric ratio can enhance heat dissipation, improve the uniformity of current density, and increase power density. Optimal fuel cell performance is achieved with a stoichiometric ratio of 300, balancing the mixed influence of multiple factors.

Lithium-ion batteries (LIBs) are widely used as power sources for electric vehicles due to their various advantages, including high energy density and low self-discharge rate. However, the safety challenges associated with LIB thermal runaway (TR) still need to be addressed. In the present study, the effects of the battery SOC value and coolant flow rate on the TR behavior in a LIB pack are comprehensively investigated. The battery pack consists of 10 18650-type LIBs applied with the serpentine channel liquid-cooling thermal management system (TMS). The TR tests for various SOC values (50%, 75% and 100%) and coolant flow rates (0 L/h, 32 L/h, 64 L/h and 96 L/h) are analyzed. The retarding effect of the TMS on TR propagation is found to be correlated with both the coolant flow rate and the battery SOC value, and a larger coolant flow rate and lower SOC generally result in fewer TR batteries. Furthermore, the TR propagation rate, evaluated by the time interval of TR occurrence between the adjacent batteries, increases with the battery SOC. The battery pack with 100% SOC shows more rapid TR propagation, which can be completed in just a few seconds, in contrast to several minutes for 50% and 75% SOC cases. In addition, the impact of the battery SOC and coolant flow rate on the maximum temperature of the TR battery is also examined, and no determined association is observed between them. However, it is found that the upstream batteries (closer to the external heater) show a slightly higher maximum temperature than the downstream ones, indicating a weak association between the TR battery maximum temperature and the external heating duration or the battery temperature at which the TR starts to take place.