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A comprehensive non-isothermal, three-dimensional computational model of a polymer electrolyte membrane (PEM) fuel cell has been developed. The model incorporates a complete cell with both the membrane-electrode-assembly (MEA) and the gas distribution flow channels. With the exception of phase change, the model accounts for all major transport phen...
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... the water ¯ux and the potential distribution is presented in Fig. 10. The ¯ux of liquid water is governed by three mechanisms: electro-osmotic drag from the anode to the cathode, back diffusion driven by a concentration gra- dient from the cathode to the anode and, if a pressure gradient exists, convection which is usually directed from the cathode to the anode in order to counter-balance the electro-osmotic drag. Assuming a fully humidi®ed mem- brane implies no concentration gradient exists, and in any case, the effect of the diffusion on the water ¯ux through the membrane has been found to be small compared to convec- tion and electro-osmotic drag. As illustrated in Fig. 10, the pressure gradient might outweigh the effect of the electro- osmotic drag for low current densities, and the net ¯ux of water is directed from the cathode to the anode. Humidi®ca- tion schemes have to be therefore devised for the cathode side only. At a current density of 0.4 A/cm 2 , the ¯ux of water is reversed. Near the inlet area, where the local current is strongest, the electro-osmotic drag dominates convection, and water ¯ows from the anode to the cathode. Near the outlet, the current is weaker and the net water ¯ux is directed towards the ...
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... the water ¯ux and the potential distribution is presented in Fig. 10. The ¯ux of liquid water is governed by three mechanisms: electro-osmotic drag from the anode to the cathode, back diffusion driven by a concentration gra- dient from the cathode to the anode and, if a pressure gradient exists, convection which is usually directed from the cathode to the anode in order to counter-balance the electro-osmotic drag. Assuming a fully humidi®ed mem- brane implies no concentration gradient exists, and in any case, the effect of the diffusion on the water ¯ux through the membrane has been found to be small compared to convec- tion and electro-osmotic drag. As illustrated in Fig. 10, the pressure gradient might outweigh the effect of the electro- osmotic drag for low current densities, and the net ¯ux of water is directed from the cathode to the anode. Humidi®ca- tion schemes have to be therefore devised for the cathode side only. At a current density of 0.4 A/cm 2 , the ¯ux of water is reversed. Near the inlet area, where the local current is strongest, the electro-osmotic drag dominates convection, and water ¯ows from the anode to the cathode. Near the outlet, the current is weaker and the net water ¯ux is directed towards the ...
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... net ¯ux of water through the membrane is often characterized by the parameter a, the net amount of water molecules dragged through the membrane per hydrogen proton. Fig. 11 shows the net water ¯ux for two different values of the electrokinetic permeability of the membrane. If the value cited by Bernardi and Verbrugge is used [4], a becomes unphysically high. A comparison with the model published by Yi and Nguyen [21] reveals that reducing the permeability to 2:0 Â 10 À20 m 2 as was used in the current base case yields a more realistic values for a. Still, these results differ substantially from the experimentally deter- mined values of a, which range from 0:6 at low current densities to around 0:3 for intermediate current densities in the absence of a pressure gradient. The membrane model has therefore to be improved in order to predict the amount of water that need to be supplied at the electrodes in order to prevent drying out of the ...
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... cells convert the chemical energy of hydrogen and oxygen directly into electricity. Their high ef®ciency and low emissions have made them a prime candidate for powering the next generation of electric vehicles, and their modular design and the prospects of micro-scaling them have gained the attention of cellular phone and laptop manufacturers. Their scalability and relative ¯exibility in terms of fuel makes them prime candidates for a variety of stationary applications including distributed residential power generation. The basic structure and operation prin- ciple of the polymer electrolyte membrane (PEM) fuel cell considered here are illustrated in Fig. ...
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Citations
... To obtain a more sophisticated interface model, reaction kinetics such as the Tafel equation have been incorporated [169,170] with the Butler-Volmer equation [171][172][173], which can be expressed as: ...
... Contemporary simulation researchers heavily depend on the Butler-Volmer (BM) equation [171,172] for electrochemical reactions in CL (Table 8). In most simulation cases, the value of the reference exchange current density was measured from experiments [225], from previous solutions [215,217,226], and assumed [220] to match the polarization curve. ...
For mitigating global warming, polymer electrolyte membrane fuel cells have become promising, clean, and sustainable alternatives to existing energy sources. To increase the energy density and efficiency of polymer electrolyte membrane fuel cells (PEMFC), a comprehensive numerical modeling approach that can adequately predict the multiphysics and performance relative to the actual test such as an acceptable depiction of the electrochemistry, mass/species transfer, thermal management, and water generation/transportation is required. However, existing models suffer from reliability issues due to their dependency on several assumptions made for the sake of modeling simplification, as well as poor choices and approximations in material characterization and electrochemical parameters. In this regard, data-driven machine learning models could provide the missing and more appropriate parameters in conventional computational fluid dynamics models. The purpose of the present overview is to explore the state of the art in computational fluid dynamics of individual components of the modeling of PEMFC, their issues and limitations, and how they can be significantly improved by hybrid modeling techniques integrating with machine learning approaches. Furthermore, a detailed future direction of the proposed solution related to PEMFC and its impact on the transportation sector is discussed.
... In fact, considerable efforts have been devoted to developing models for physiochemical processes in CLs with increasing accuracy of describing distributions of different constituents and multiple reactive transport processes. Existing CL models can be generally divided into three kinds, the thin-film model [3], the homogeneous model [4] and the agglomerate model [5]. Among them, the agglomerate model recognizes the hierarchical structures of CL including large pores between agglomerates consisted of carbon particles where the oxygen bulk diffusion occurs and the relatively small pores inside the agglomerate in which the local oxygen reactive transport takes place. ...
... Similarly, it should be noted again that in Ref. [60] four different RH (25 %, 50 %, 75 %, and 100 %) were measured but only the detailed current density distributions under 25 % and 50% RH were provided. It can be observed in Fig. 10(a) and (c) that as the RH decreases from 50 % to 25 %, the regions of high local current density shift downward from the up region (approximately rows [1][2][3][4][5] to the lower region (approximately rows [3][4][5][6]. This is attributed to the decreased hydration capability of the incoming hydrogen and air on the ionomer at low RH conditions. ...
... Similarly, it should be noted again that in Ref. [60] four different RH (25 %, 50 %, 75 %, and 100 %) were measured but only the detailed current density distributions under 25 % and 50% RH were provided. It can be observed in Fig. 10(a) and (c) that as the RH decreases from 50 % to 25 %, the regions of high local current density shift downward from the up region (approximately rows [1][2][3][4][5] to the lower region (approximately rows [3][4][5][6]. This is attributed to the decreased hydration capability of the incoming hydrogen and air on the ionomer at low RH conditions. ...
Improving the performance of proton exchange membrane fuel cells (PEMFCs) requires deep understanding of the reactive transport processes inside the catalyst layers (CLs). In this study, a particle-overlapping model is developed for accurately describing the hierarchical structures and oxygen reactive transport processes in CLs. The analytical solutions derived from this model indicate that carbon particle overlap increases ionomer thickness, reduces specific surface areas of ionomer and carbon, and further intensifies the local oxygen transport resistance ( R other ). The relationship between R other and roughness factor predicted by the model in the range of 800-1600 s m ⁻¹ agrees well with the experiments. Then, a multiscale model is developed by coupling the particle-overlapping model with cell-scale models, which is validated by comparing with the polarization curves and local current density distribution obtained in experiments. The relative error of local current density distribution is below 15% in the ohmic polarization region. Finally, the multiscale model is employed to explore effects of CL structural parameters including Pt loading, I/C , ionomer coverage and carbon particle radius on the cell performance as well as the phase-change-induced (PCI) flow and capillary-driven (CD) flow in CL. The result demonstrates that the CL structural parameters have significant effects on the cell performance as well as the PCI and CD flows. Optimizing the CL structure can increase the current density and further enhance the heat-pipe effect within the CL, leading to overall higher PCI and CD rates. The maximum increase of PCI and CD rates can exceed 145%. Besides, the enhanced heat-pipe effect causes the reverse flow regions of PCI and CD near the CL/PEM interface, which can occupy about 30% of the CL. The multiscale model significantly contributes to a deep understanding of reactive transport and multiphase heat transfer processes inside PEMFCs.
... In situ data such as temperature, pressure, species flow and saturation are not easy to obtain during operation due to the highly reactive and confined environment of the cells. This causes a paucity of experimental data, which does not allow adequate understanding of these processes [4,5]. ...
Computational Fluid Dynamics (CFD) software is well known for its application feasibility as well as reliable results in modeling electrochemical, thermal, and fluid transport processes. CFD has been used to investigate the phenomena involved in the operation of fuel cells, providing a large amount of data that must be analyzed to improve cell efficiency. This paper aims to demonstrate that programming can be used in the post-processing phase, using scripts in Python language to automate data analysis, based on the results of the simulation of oxygen transport in Polymer Electrolyte Membrane Fuel Cell (PEMFC). The OpenFOAM open-source CFD tool solved the fluid governing equations through the SIMPLE algorithm of three proposed Gas Diffusion Layer (GDL) case studies. In this work, an algorithm is presented to extract, compute and visualize the post-process results, supporting the GDL selection.
... In the literature, there exists a variety of mathematical models: those based on algebraic expressions to describe physical relations that occur in the fuel cell, they are called empirical or semi-empirical models, and we obtain the behavior of the polarization curves by setting a set of empirical or semi-empirical parameters through non-linear regression methods (Zhang and Sanderson, 2009;Ohenoja and Leiviskä, 2010;Outeiro et al., 2008). Interface models, this kind of models describe the diffusion processes through the anode, membrane, and cathode using diffusion equations (assuming that the catalytic layer is negligible) (Lu et al., 2002;Berning and Djilali, 2003a,b). Macro-homogeneous models consist of a set of non-linear ordinary differential equations; they assume that the main reactions occur in the catalytic layers, and describe the physical compositions of the materials (Tiedemann and Newman, 1975;Marr and Li, 1999;You and Liu, 2001;Khajeh-Hosseini-Dalasm et al., 2010b;Heidary et al., 2016); Agglomerated models, these formulations are conformed by a set of partial differential equations, model diffusion in the cell, provide a description of the physical composition, porosity, and conglomerates of the catalytic layers of the fuel cell. ...
... Computational fluid dynamics (CFD) have been successfully used for decades to gain deeper insight into the underlying multiphase flow processes in proton exchange membrane fuel cells (2)(3)(4)(5)(6)(7)(8). However, concerning the mature alkaline electrolyzer technology that has been developed since 1920, there is surprisingly few efforts to develop high-fidelity computational models (9-10) ...
As the most mature technology within the electrolysis field, alkaline electrolyzers are expected to play an important role in the energetic transition. Advantages as their simplicity, modularity and low-cost components make it an interesting technology for the near future. However, the fundamental physics are complex as it includes multicomponent, multiphase flow, porous media, electrochemistry and heat transfer. To have a better understanding of these phenomena, the presented work is devoted to the development of a computational fluid dynamic model to better understand the behavior of all the species that are part of this technology.
... In conjunction with advanced transmission electron microscopy (TEM) [11], scanning electron microscopy (SEM) [12], nano Xray computed tomography (CT) [13], and focused-ion beam (FIB) [14], researches have gained fundamental insights into the transport processes occurring within the CL. Recently, a promising three-dimensional nanoimaging called deep-learningaided cryogenic transmission electron tomography (cryo-ET) has shown great potential in evaluating catalyst layer architectures and establishing connections between morphology, transport properties, and overall fuel cell performance [15]. ...
... It is widely recognized that the optimal design is the CL with a higher catalyst concentration towards the membrane side. Similarly, the CL with a higher ionomer concentration towards the membrane side can enhance the performance, especially under high current density conditions, which has been validated by numerous previous studies [15,45,46]. Additionally, increasing the in-plane distribution of ionomer from inlet to outlet direction has been shown to outperform homogeneous electrodes [10]. ...
The effective management of oxygen transport resistance (OTR) within the cathode catalyst layer (CCL) is crucial for achieving a high catalyst performance at low platinum (Pt) loading. Over the past two decades, significant advancements have been made in the development of various high active platinum-based catalysts, aiming at enhancing oxygen mass transport and the oxygen reduction reaction (ORR). However, experimental investigations of transport processes in porous media are often computational costs and restrained by limitations in in-situ measurement capabilities, as well as spatial and temporal resolution. Fortunately, numerical simulation provides a valuable alternative for unveiling the intricate relationship between local transport properties and overall cell performance that remain unresolved or uncoupled through experimental approach. In this review, we elucidate the primary experimental and numerical efforts undertaken to improve OTR. We consolidate the available literature on OTR values and perform a quantitative comparison of the effectiveness of different strategies in mitigating OTR. Furthermore, we analyze the intrinsic limitations and challenges associated with current experimental and numerical methods. Finally, we outline future prospect for advancements in both experimental techniques and modelling methods.
... where T is the temperature (in K), ϕ is mass fractions, M is the gas molecular weight (in kg/mole), σ is the diffusion coefficient (in m 2 /s), and the subscript letters i and j refer to hydrogen in anode or oxygen in cathode and the water vapor in both sides, respectively. Based on both pressure and temperature, it is possible to determine Maxwell-Stefan diffusion coefficients from the kinetic theory equation [23]: ...
... In this equation, the units of binary diffusion coefficient and pressure are cm 2 /s and atm, respectively. The values for ∑W ri are provided in [23]. ...
Citation: AL-bonsrulah, H.A.Z.; Alshukri, M.J.; Mikhaeel, L.M.; AL-sawaf, N.N.; Nesrine, K.; Reddy, M.V.; Zaghib, K. Design and Simulation Studies of Hybrid Power Systems Based on Photovoltaic, Wind, Electrolyzer, and PEM Fuel Cells.
... The gas diffusion layer is generally made of carbon paper, and its structure is characterized by significant anisotropy. However, most computational simulation models in the literature use a homogeneous simulation model for gas diffusion layers [12][13][14][15][16][17][18][19], using the same transfer coefficients in all directions. Only a few papers [20][21][22][23][24] have investigated the effect of non-isotropic characteristics in the gas diffusion layer on the capabilities of proton exchange membrane fuel cells. ...
In this paper, the effect of changes in the thermal conductivity of porous electrodes in three coordinate directions on the capability of proton exchange membrane fuel cells is investigated on the basis of current density versus voltammetry curves, and the temperature distribution and water-carrying capacity distribution of the membrane. The results show that when the cell discharge voltage of the PEMFC is 0.3 V, the thermal conductivity in the Z-direction of the porous electrode has a greater effect on the performance of the PEMFC than in the other directions, with the thermal conductivity in the X- and Y-directions of the porous electrode having less than a 5% effect on the performance of the PEMFC, which can therefore be neglected. When the thermal conductivity of the porous electrode in the Z-direction of the PEMFC is 500 W/(m·K) and 1000 W/(m·K), the performance of the PEMFC is improved by 5.78% and 5.87%, respectively, and when the thermal conductivity of the porous electrode in the X-direction of the PEMFC is 500 W/(m·K) and 1000 W/(m·K), the performance of the PEMFC is improved by 2.09% and 2.89%, and the PEMFC performance is improved by 1.51% and 2.00% when the Y-direction thermal conductivity of the porous electrode of the PEMFC is 500 W/(m·K) and 1000 W/(m·K), respectively. The improvement in performance decreases with increasing thermal conductivity, because the thickness of the porous electrode is too thin. Since the side of the model is set to adiabatic heat exchange conditions, while the top and bottom surfaces are set to natural convection heat exchange conditions, the Z-direction thermal conductivity of the porous electrode plays the most important role in the temperature distribution of the PEMFC. The Z-direction thermal conductivity of the porous electrode causes the temperature distribution of the PEMFC assembly to be more uniform, and the Z-direction thermal conductivity of the porous electrode also causes the area of the high-water-content region on the proton exchange membrane to significantly increase.
... In the 2000s, multi-dimensional models have been developed by many researchers to solve a complete set of conservation equations (such as continuity and Navier-Stokes) coupled with electrochemical reactions (for example the ORR kinetics at the cathode). Computational fluid dynamics (CFD) code and commercial software (such as ANSYS Fluent, and COMSOL Multiphysics) based on finite volume methods (FEM) were adopted to develop the fuel cell models, and more complicated geometry and transport phenomena were investigated [34][35][36][37][38][39][40][41][42][43][44]. ...
... In the area of three-dimensional (3D) geometry, the models developed by Dutta et al. [34,35], Zhou and Liu [36], Berning et al. [37], Mazumder and Cole [38], Lee et al. [40], Um and Wang [41], and Wang and Wang [42] were mainly considered a single flow channel with the major components of reactant gases. Large-scale simulations considering multi-channel or small stacks give a more accurate and more specific analysis of the distribution of reactant gases (H2 and O2), water vapor, and pressures. ...
... In the simplest approach, the CLs are treated as reactive boundaries between the GDL and membrane [37,72]. For example, Jeng et al. [72] developed a simple 2D across-the-channel model to study the mass transport of the reactant gases through the GDLs. ...
... A quasi-2D model based on the concentration theorem was developed and presented by Fuller and Newman in [71]. The first 3D computational design of PEMFC was established by Berning et al. [72]. In this design, electrolyte membrane and mass transfer rates, electric current, humidity, and temperature effects were investigated. ...
As renewables are being integrated into the power grids, new challenges are introduced, such as the impacts on the grid due to sudden variations in weather conditions and load demands. Green hydrogen energy (GHE) storage, using electrolyzers (EL) and fuel cells (FC), has been identified as one of the potential solutions. As the world transitions to a zero-carbon economy, the production and storage of hydrogen using EL from surplus renewable is receiving global interest. Whenever electricity is required, the stored hydrogen gas can be used to produce electrical energy using an FC to supply to the loads/grid. To make the renewable energy sources (RESs) and FC/EL integrated power systems optimal, efficient, reliable, and cost-effective, an adaptive energy conversion system and power management control strategy (PMCS) that includes advanced control algorithms need to be formulated to utilize the surplus of renewable energy. Despite many review studies on FCs/ELs integrated power systems, a detailed review of FCs/ELs technologies for utilizing the renewable energy surplus is still limited in terms of different types of grids (AC or DC) integrated topologies, multiple types of FCs/ELs models, and a variety of power electronic interfaces with appropriate PMCS. This paper presents a comprehensive review with a more specific assessment of FC/EL comprised GHE storage technologies for the widespread interconnection of RESs. It is expected that this in-depth review will help in advancing the relevant technologies and eventually support the transition to a zero-carbon economy and meet Goal 7 of the United Nation Sustainable Development.
