A Computationally Efficient Pseudo-2D PEM Fuel Cell Model for Studying Humidity Distribution Without External Humidification: The Role of Anode Recirculation

To reduce greenhouse gas emissions, fuel cell powertrains represent a promising alternative for heavy-duty transport. Such demanding applications require an extended operational lifespan, which calls for models able to accurately map internal states as a function of system architecture and control strategy. This work presents a pseudo-2D macro-homogeneous proton exchange membrane fuel cell model, discretized along the flow channels, in which the various transport phenomena are resolved between layers but not within their thickness. This choice reflects the model’s purpose: integration into complete system models to support system architecture studies, which requires a suitable trade-off between computation time and representativeness of system-imposed operating conditions. Kulikovsky’s analytical approximation is used to compute the voltage losses in the catalyst layer, preserving an accuracy close to a model with a fully discretized catalyst layer thickness. The model is integrated into a system featuring anode recirculation and no cathode humidification to study the sensitivity of humidity distribution to operating parameters. Simulations show that the anode recirculation rate and the temperature difference between inlet and outlet are the two main operating conditions governing spatial humidity distribution, while coolant inlet temperature, pressure, and cathode stoichiometry predominantly affect the absolute humidity within the stack.