A computationally efficient model toward real-time monitoring of automotive polymer electrolyte membrane (PEM) fuel cell stacks is developed. Computational efficiency is achieved by spatio-temporal decoupling of the problem, developing a new reduced-order model for water balance across the membrane electrode assembly (MEA), and defining a new variable for cathode catalyst utilization that captures the trade-off between proton and mass transport limitations without additional computational cost. Together, these considerations result in the model calculations to be carried out more than an order of magnitude faster than real time. Moreover, a new iterative scheme allows for simulation of counter-flow operation and makes the model flexible for different flow configurations. The proposed model is validated with a wide range of experimental performance measurements from two different fuel cells. Finally, simulation case studies are presented to demonstrate the prediction capabilities of the model.

In this article, a computationally efficient pseudo-2D model for real-time dynamic simulations of polymer electrolyte membrane fuel cells (PEMFCs) is developed with a specific focus on water and thermal management. The model accounts for temperature dynamics, two-phase flow and flooding in the diffusion media, and membrane water crossover as well as absorption and desorption processes. Computational efficiency is achieved by leveraging the disparate time scales within the system dynamics, in addition to exploiting the large aspect ratio of the cell layers to create a spatio-temporal decoupling. Taking advantage of such decoupling, the model yields a computationally efficient solution while providing detailed information about the state of water and temperature throughout the cell. 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. The results are shown to be in qualitative agreement with published experimental data, thereby providing a preliminary validation of the modeling approach. Finally, using the modeling results, an equivalent electrical circuit model is proposed to help elucidate water transport inside various cell layers. 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. However, including such phenomena comes at the cost of higher computational requirements, resulting in a trade-off between model accuracy and computational speed, which must be carefully balanced based on the desired application. As a result of these competing requirements, developing mathematical models that achieve a balance between the needs for high fidelity and low computational demand remains an active area of research.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 1-3 to resolve transport phenomena in all physical directions; ii) transient behavior; iii) detailed multistep hydrogen oxidation reaction (HOR) and oxygen reduction reaction (ORR) kinetics; 4,5 iv) multiphase flow in gas channels and porous media; v) non-isothermal effects; 6 and vi) multicomponent diffusion.7,8 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-themembrane and along-the-channel directions and also account for the channel-land effects in the third dimension. Moreover, these models can easily in...

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With the goal of on-line diagnosis for automotive applications in mind, a real-time model of polymer electrolyte membrane (PEM) fuel cell is developed. The model draws from the authors’ previous modeling effort in this area and extends its domain to incorporate transport under the lands. Transport in the catalyst and micro-porous layers, which were previously omitted, are also included in the model. Membrane water transport model is modified accordingly. Moreover, a recently developed homogeneous catalyst layer model is used to describe local oxygen transport resistance in the cathode catalyst layer. Computational efficiency is achieved through spatio-temporal decoupling of the problem, which simplifies the handling of the nonlinear terms. This computational efficiency is demonstrated by a set of simulations that resemble operation under conditions encountered in automotive applications. Moreover, simulation results of the model are in qualitative agreement with earlier computationally intensive modeling studies as well as experimental observations. The current modeling study demonstrates a significant potential for using relatively high-fidelity physics-based models on-line to improve fuel cell performance and durability, which can have a profound impact on its commercialization.