A comprehensive review of the modeling of transport phenomenon in the flow channels of polymer electrolyte membrane fuel cells

doi:10.1007/s11705-024-2445-x

2024, Vol. 18

Issue (8) : 94 https://doi.org/10.1007/s11705-024-2445-x

A comprehensive review of the modeling of transport phenomenon in the flow channels of polymer electrolyte membrane fuel cells

Niyi Olukayode¹, Shenrong Ye¹, Mingruo Hu¹, Yanjun Dai², Rui Chen³, Sheng Sui¹(

)

¹. Institute of Fuel Cell, Shanghai Jiao Tong University, Shanghai 200240, China
². Institute of Refrigeration and Cryogenics, Shanghai Jiao Tong University, Shanghai 200240, China
³. Low Carbon Engineering, Loughborough University, Loughborough Leicestershire LE11 3TU, UK

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Abstract

Reactant gas and liquid water transport phenomena in the flow channels are complex and critical to the performance and durability of polymer electrolyte membrane fuel cells. The polymer membrane needs water at an optimum level for proton conductivity. Water management involves the prevention of dehydration, waterlogging, and the cell’s subsequent performance decline and degradation. This process requires the study and understanding of internal two-phase flows. Different experimental visualization techniques are used to study two-phase flows in polymer electrolyte membrane fuel cells. However, the experiments have limitations in in situ measurements; they are also expensive and time exhaustive. In contrast, numerical modeling is cheaper and faster, providing insights into the complex multiscale processes occurring across the components of the polymer electrolyte membrane fuel cells.

This paper introduces the recent design of flow channels. It reviews the numerical modeling techniques adopted for the transport phenomena therein: the two-fluid, multiphase mixture, volume of fluid, lattice Boltzmann, and pressure drop models. Furthermore, this work describes, compares, and analyses the models’ approaches and reviews the representative results of some selected aspects. Finally, the paper summarizes the modeling perspectives, emphasizing future directions with some recommendations.

Keywords two-phase flows numerical model flow channel polymer electrolyte membrane fuel cells water management

Corresponding Author(s): Sheng Sui

Just Accepted Date: 29 April 2024 Issue Date: 12 July 2024

Cite this article:

Niyi Olukayode,Shenrong Ye,Mingruo Hu, et al. A comprehensive review of the modeling of transport phenomenon in the flow channels of polymer electrolyte membrane fuel cells[J]. Front. Chem. Sci. Eng., 2024, 18(8): 94.

URL:

https://academic.hep.com.cn/fcse/EN/10.1007/s11705-024-2445-x
https://academic.hep.com.cn/fcse/EN/Y2024/V18/I8/94

Fig.2 Uniformity comparison between metal foam and channel-rib fields. (a) Oxygen molar concentration at the CL mid-plane, and (b) current density distribution at the membrane mid-plane. Reprinted with permission from ref [72], copyright 2021, Elsevier Ltd.

Fig.3 Scanning electron microscope images of a hybrid of graphene and metal foam before compression: (a) top-view and (b) cross-section; after compression (c) top-view and (d) after compression; (e) porosity (%) before and after compression. Reprinted with permission from ref [78], copyright 2018, Elsevier Ltd.

Fig.4 Some recent flow channel patterns. (a) Metal foam. Reprinted with permission from ref [73], copyright 2019, Elsevier BV. (b) Spiderweb based. Reprinted with permission from ref [68], copyright 2021, MDPI. (c) Honeycomb. Reprinted with permission from ref [65], copyright 2022, Elsevier Ltd. (d) Multi-inlet. Reprinted with permission from ref [28], copyright 2022, Elsevier Ltd. (e) Intersectant. Reprinted with permission from ref [63], copyright 2018, Elsevier Ltd. (f) Nautilus. Reprinted with permission from ref [70], copyright 2023, Elsevier Ltd. (g) M-shaped. Reprinted with permission from ref [45], copyright 2020, Elsevier Ltd. (h) Auxiliary fishbone-shaped. Reprinted with permission from ref [67], copyright 2021, Elsevier Ltd. (i) Snowflake. Reprinted with permission from ref [61], copyright 2022, MDPI. (j) Bio-inspired wave-like (cuttlefish like). Reprinted with permission from ref [66], copyright 2020, Elsevier Ltd. (k) Multi-hole structured. Reprinted with permission from ref [37], copyright 2018, Elsevier BV. (l) Imitating-river. Reprinted with permission from ref [55], copyright 2023, Elsevier Ltd. (m) V-ribbed serpentine. Reprinted with permission from ref [36], copyright 2022, Elsevier Ltd. (n) Convergent and divergent. Reprinted with permission from ref [39], copyright 2018, Elsevier Ltd. (o) Rim-type radial. Reprinted with permission from ref [50], copyright 2022, Taylor & Francis INC. (p) OSWFF and ICFF. Reprinted with permission from ref [59], copyright 2023, Elsevier Ltd. (q) Spider-based bionic. Reprinted with permission from ref [69], copyright 2023, The Korean Electrochemical Society. (r) Traveling-wave. Reprinted with permission from ref [58], copyright 2023, Elsevier Ltd. (s) Tapered. Reprinted with permission from ref [42], copyright 2022, Elsevier Ltd. (t) Key-shaped. Reprinted with permission from ref [47], copyright 2022, Elsevier Ltd. (u) 3D ((i) Toyota 3D fine mesh. Reprinted with permission from ref [94], copyright 2015, MDPI. (ii) Reprinted with permission from ref [99], copyright 2020, Elsevier Ltd. (iii) Reprinted with permission from ref [100], copyright 2023, Elsevier) flow fields.

Fig.5 (a) Cost breakdown for FC stack components (at a production volume of 500,000 units·yr^–1). Reprinted with permission from ref [103], copyright 2018, Elsevier. (b) Mekko diagram showing cost types and distribution for fuel cell components. Reprinted with permission from ref [104], copyright 2023, Elsevier Ltd.

Criteria	Two-Fluid [22, 134,138,140]	M² [21,138,202]	VOF [9,10,23]	LBM [177,181,210,211]	Pressure-Drop [133,199,216]
Approach	?Considers the phases separately.?Computes two mass, momentum, and energy conservation equations for each phase.	?Considers a two-phase flow as a single-fluid flow with a varying phase composition.?Solves a single continuity, momentum, and energy equation for the mixture and algebraic expressions for the relative velocities and volume fractions.	?An interface-tracking technique for two or immiscible fluids. ?Solves a single set of momentum equations for the whole fluid domain.	?A mesoscopic approach that describes the statistical distribution of particles in a fluid and simulates the fluid flow through the evolution of the particle distribution functions on fixed lattices.	?Evaluates the pressure drop using correlations based on the homogeneous or separated formulations ?Uses the pressure drop to characterise flow patterns and interactions.
Applications	?For two or more interpenetrating phases (fluid-fluid).?Primarily used to simulate dispersed flow.	?Designed for two or more phases (fluid or particulate).	?Designed for two or more immiscible fluids where the position of the interface between the fluids is of interest ?For steady or transient tracking of any liquid-gas interface.	?Efficient for single- and multiphase fluid with interfacial dynamics and complex boundaries. ?For the study of the wettability of solid surfaces and behaviour of droplets on different surfaces.	?Effective for analysing flow patterns (slug flows, mist flows, annular flow, bubble flow, stratified flow) in channels of different length scales.
Strengths	?High accuracy, relatively good performance. ?Uses interphase transfer models.?Can model species diffusion and resolve complex liquid motions.?Can be used to quantify liquid water saturation (amount of liquid water) in the flow channels and its effect on PEMFC performances.	?Significant reduction in the number of variables and computational time and cost.?Has reduced complexity.?Requires less modelling effort compared to two-fluid and VOF models.?Inherently assumes local equilibrium between the gas and liquid phases, simplifying the calculation.?Can evaluate the quantity of liquid water in the flow channels and predict its influence on fuel cell performances.	?Powerful, efficient, and flexible.?Can solve problems with complex free surface configuration. ?Conservation is ensured.?Can be used to observe the formation and evolution of liquid water droplets in flow channels.?Well-suited for surface-tension dominant flows, especially in microchannels.?Can track the shape of a droplet.	?Computationally more efficient than conventional models.?Requires less time to produce results for the same or finer computational mesh.?Easy implementation of boundary conditions and parallel computations.?Can be adopted for macroscale, mesoscale, or microscale flow situations. ?Accounts for interactions between different phases.	?Suitable for many flow patterns. ?Availability of several correlations to describe complex flow situations.
Shortcomings	?Has the highest number of variables?High computational time and cost.?Increased complexity. ?Instabilities are experienced due to the coupling of phases.?Requires specification of phase change kinetics, making its calculation more complicated.?Cannot track the gas-liquid interface; hence, it cannot be used to observe liquid water droplets’ formation, transition, and motion.	?Convergence and mass conservation problems. ?Cannot use interphase transfer model. ?Requires evaluation of many mixture quantities.?Cannot observe the formation of liquid water or study droplet dynamics.	?High computational cost?Accurate reconstruction of the curvature of the interface is difficult in unstructured grids and complex geometries.?Difficult to couple the model with electrochemical reactions and heat transfer.	?Difficult to couple the model with electrochemical reactions and heat transfer ?Spurious currents at high values.?Challenging to adopt the model for large-scale flow channels.	?Prediction of pressure drop in PEMFC channel bend is challenging.?Limited applicability of correlations.

Tab.1 Comparison of multiphase models

Fig.6 Agreement between the experiments and model simulations. (i) Water droplet deformations as reported by (a) experimental observations and (b) VOF simulation. Reprinted with permission from ref [220], copyright 2006, Academic Press Inc. (ii) (a) Water thickness and (b) pressure drop predictions of VOF model, pressure drop models (homogeneous and separated model), theoretical results, experimental data and two-fluid model. Reprinted with permission from ref [158], copyright 2020, Elsevier Ltd. (iii) Polarization curve results of a mixture model, a CFD model, and an experiment. Reprinted with permission from ref [124], copyright 2009, Elsevier.

Fig.7 (a) Liquid water distribution and (b) oxygen concentration distribution in the cathode channel of serpentine and parallel flow field. Reprinted with permission from ref [122], copyright 2018, Elsevier Ltd.

Fig.8 (a) Behavior of liquid water and (b) liquid water volume fraction in conventional straight channels and opposite sinusoidal wave flow channel. Reprinted with permission from ref [222], copyright 2022, Elsevier Ltd.

Fig.9 Effect of metal foam (a) porosity, (b) pore density, and (c) compression ratio on current density at different inlet velocities. Reprinted with permission from ref [74], copyright 2022, Elsevier.

Fig.13 Droplet dynamic behavior (i) with different GDL wettability, and (ii) with the proposed hydrophilic wettability method: (a) small droplet and (b) large droplet. Reprinted with permission from ref [230], copyright 2022, Elsevier.

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