This paper presents a 2D, fully coupled and comprehensive transient model that accounts for micro-structural features of various cell layers. The model benefits from state of the art sub-models for reaction kinetics and incorporates the polymer relaxation dynamics. Furthermore, a mixed wettability model is utilized to simulate the transient two phase conditions in the porous layers. The model is validated with transient experimental data under various conditions. A comprehensive simulation study is presented to investigate the impact of operating temperature and relative humidity on the transient response. The effects of cathode Pt loading and operation mode, i.e., current control versus voltage control, are also studied. The cell response is found to be dominated by water transport through its thickness. Additionally, it is found that reducing the Pt loading can influence the performance by changing the water balance in the cell, which has rarely been highlighted in the literature. In particular, at low temperature more water is transported toward the anode when the cathode Pt loading is reduced, since the resistance to water back diffusion is lowered with reduced thickness of the cathode catalyst layer. This trend is reversed at a higher temperature due to increased volumetric heat generation with reduced thickness. The model can help in understanding various transport phenomena and is expected to be useful for inspecting spatio-temporal temperature, potential, and species distributions across the cell's thickness and optimizing the cell design and choice of materials.

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...

This two-part series develops a framework for effective parameterization of polymer electrolyte membrane (PEM) fuel cell models with limited and non-invasive measurements. In the first part, a systematic procedure for identifiability analysis is presented, where a recently developed model is analyzed for the sensitivity of its output predictions to a variety of structural and fitting parameters. This is achieved by conducting local analyses about several points in the parameter space to obtain sensitivities that are more representative of the entire space than the local values estimated at a single point, which are commonly used in the literature. Three output predictions are studied, namely, cell voltage, resistance, and membrane water crossover. It is found that the cell voltage is sensitive to many of the model parameters, whereas the other model predictions demonstrate a sparser sensitivity pattern. The results are further analyzed from the perspective of collinearity of parameter pairs and it is shown that many of the parameters have similar impact on voltage predictions, which diminishes their identifiability prospects. Lastly, the sensitivity results are utilized to analyze parameter identifiability. The least squares cost Hessian is shown to have an eigenvalue spectrum evenly spanned over many decades and the resulting identifiability challenges are discussed.

Greater neck girth and strength may be associated with a lower risk of sport-related concussion due to mitigation of head accelerations by the neck. However, neck strengthening exercise remains unstudied in youth athletes. Therefore, this pilot study assessed the feasibility and effect of targeted neck strengthening exercises in youth athletes. Seventeen participants were allocated to perform 8-wk manual resistance-based neck strengthening (n = 13) or control resistance exercise (n = 4) programs. Before and after the intervention, participants completed laboratory-based assessments of neck size, strength, and head kinematics during standardized test loading in each plane of motion. Descriptive statistics were calculated to compare pre-post changes between the two groups. All participants safely and successfully completed the intervention. Neck girth and strength increased in both groups, with greater increases in the neck strengthening group. Across all planes of motion, overall changes in head linear and angular velocity decreased in both groups, with greater decreases in ΔV in the neck strengthening group and greater decreases in Δω in controls. These results suggest the potential for resistance exercise training to reduce youth athletes' risk for sport-related concussion by increasing neck girth and strength. Additional research is needed to determine optimal neck strengthening programs.