The large-scale adoption of fuel cells system for sustainable power generation will require the combined use of both multidimensional models and of dedicated testing techniques, in order to evolve the current technology beyond its present status. This requires an unprecedented understanding of concurrent and interacting fluid dynamics, material and electrochemical processes. In this review article, Polymer Electrolyte Membrane Fuel Cells (PEMFC) are analysed. In the first part, the most common approaches for multi-phase/multi-physics modelling are presented in their governing equations, inherent limitations and accurate materials characterisation for diffusion layers, membrane and catalyst layers. This provides a thorough overview of key aspects to be included in multidimensional CFD models. In the second part, advanced diagnostic techniques are surveyed, indicating testing practices to accurately characterise the cell operation. These can be used to validate models, complementing the conventional observation of the current–voltage curve with key operating parameters, thus defining a joint modelling/testing environment. The two sections complement each other in portraying a unified framework of interrelated physical/chemical processes, laying the foundation of a robust and complete understanding of PEMFC. This is needed to advance the current technology and to consciously use the ever-growing availability of computational resources in the next future.

Polymer electrolyte membrane fuel cells (PEMFC) are promising devices for securing future sustainable mobility. Their field of application ranges from locally emission-free stationary power generation to propulsion systems for vehicles of all kinds. Computational fluid dynamic (CFD) simulations are successfully used to access the internal states and processes with high temporal and spatial resolution. It is challenging to obtain reliable physical values of material properties for the parameterization of the numerous governing equations. The current work addresses this problem and uses numerically reduced models to parameterize sophisticated transient 3D-CFD models of a commercial PEMFC. Experimental data from a stack test stand were available as a reference for numerical optimization of selected parameters and validation purposes. With an innovative meshing approach, the homogenized channels approach, a reduction of computational cells by 87% could be achieved, thus enabling the unsteady simulation of a 120 s load step with a computational mesh that represents the entire fuel cell geometry with reasonable computational effort. The water formation and the transport processes during the load step were analyzed. The self-humidification strategy of the fuel cell gases was visualized and the uniformity of the simulated quantities was discussed. An outlook on possible future work on efficient parameterization is given.

Polymer electrolyte membrane fuel cells (PEMFCs) supplied with green hydrogen from renewable sources are a promising technology for carbon dioxide-free energy conversion. Many mathematical models to describe and understand the internal processes have been developed to design more powerful and efficient PEMFCs. Parameterizing such models is challenging, but indispensable to predict the species transport and electrochemical conversion accurately. Many material parameters are unknown, or the measurement methods required to determine their values are expensive, time-consuming, and destructive. This work shows the parameterization of a quasi-3D PEMFC model using measurements from a stack test stand and numerical optimization algorithms. Differential evolution and the Nelder–Mead simplex algorithm were used to optimize eight material parameters of the membrane, cathode catalyst layer (CCL), and gas diffusion layer (GDL). Measurements with different operating temperatures and gas inlet pressures were available for optimization and validation. Due to the low operating temperature of the stack, special attention was paid to the temperature dependent terms in the governing equations. Simulations with optimized parameters predicted the steady-state and transient behavior of the stack well. Therefore, valuable data for the characterization of the membrane, the CCL and GDL was created that can be used for more detailed CFD simulations in the future.