Moreover, pseudo 2-D models may be calibrated to account for the channel-land effects through the use of effective resistances at the channel interface with the diffusion media.
In terms of temporal behavior of the fuel cell system, transient models are required to capture various dynamic phenomena in the cell that occur on multiple time scales and have a profound effect on its performance.
Through this approach, the current implementation of the model is found to be about twice faster than real time.
Moreover, a case study is carried out where different mechanisms contributing to overall water balance in the cell are investigated.
Furthermore, it requires extensive parameter identification to fit the modeling results to experimental data.
Nevertheless, it remains one of the main models that is used in the control community. proposed a reduced model for nonlinear model predictive control applications, where they used representative elementary volumes (REVs) to reduce partial differential equations (PDEs) into ordinary differential equations (ODEs).
Within the context of this paper, a fuel cell model is considered to have high fidelity if it incorporates the following phenomena: i) 3-D effects including anisotropic material properties A more detailed explanation of these considerations follows.
In terms of dimensionality, 3-D models are of highest fidelity, because they are capable of capturing transport in both through-the-membrane and along-the-channel directions and also account for the channel-land effects in the third dimension.
Real-time estimation, prediction, and control of cell hydration and temperature distribution is essential for optimizing the performance of polymer electrolyte membrane fuel cells (PEMFCs), as well as avoiding critical conditions and mitigating cell degradation.
These applications necessitate mathematical models that not only run in real time, but also incorporate the important physical phenomena related to water transport and thermal management.