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Journal Article

Three-Dimensional Simulation of Water Management for High-Performance Proton Exchange Membrane Fuel Cell

2018-04-03
2018-01-1309
Proton exchange membrane fuel cell (PEMFC) is widely regarded as the most promising candidate for the next generation power source of automobile, after the pure battery electric vehicle. In this study, the gas and liquid two-phase flow in channels and porous electrodes inside PEMFC coupled with electrochemical reaction is simulated in detail, in which the anisotropic gas diffusion layer (GDL) is also considered. In the simulation, the inlet reactant gas molar concentration is calculated based on the real inlet pressure, which is more practical than specifying a constant value in previous simulation. Meanwhile, the effect of electro-osmotic drag on membrane water content distribution is treated to be a convection term in the conservation equation, instead of a source term as usually used.
Technical Paper

Large-Scale Simulation of PEM Fuel Cell Using a “3D+1D” Model

2020-04-14
2020-01-0860
Nowadays, proton exchange membrane (PEM) fuel cell is widely seen as a promising energy conversion device especially for transportation application scenario because of its high efficiency, low operation temperature and nearly-zero road emission. Extensive modeling work have been done based on different dimensions during the past decades, including one-dimensional (1D), two-dimensional (2D), three-dimensional (3D) and intermediate combinations in between (e.g. “1+1D”). 1D model benefits from a rationally-chosen set of assumptions to obtain excellent calculation efficiency, yet at the cost of accuracy to some extent. In contrast, 3D model has great advantage over 1D model on acquiring more comprehensive information inside the fuel cell. For macro-scale modeling work, one compromise aiming to realize both acceptable computation speed and reasonable reflection of cell operation state is to simplify the membrane electrode assembly (MEA).
Technical Paper

Three-Dimensional Multi-Scale Simulation for Large-Scale Proton Exchange Membrane Fuel Cell

2019-04-02
2019-01-0381
PEMFC (proton exchange membrane or polymer electrolyte membrane fuel cell) is a potential candidate as a future power source for automobile applications. Water and thermal management is important to PEMFC operation. Numerical models, which describe the transport and electrochemical phenomena occurring in PEMFCs, are important to the water and thermal management of fuel cells. 3D (three-dimensional) multi-scale CFD (computational fluid dynamics) models take into account the real geometry structure and thus are capable of predicting real operation/performance. In this study, a 3D multi-phase CFD model is employed to simulate a large-scale PEMFC (109.93 cm2) under various operating conditions. More specifically, the effects of operating pressure (1.0-4.0 atm) on fuel cell performance and internal water and thermal characteristics are studied in detail under two inlet humidities, 100% and 40%.
Journal Article

A Quasi-2D Transient Multiphase Modeling of Cold Start Processes in Proton Exchange Membrane Fuel Cell

2019-04-02
2019-01-0390
It’s well known that startup process of proton exchange membrane fuel cells (PEMFCs) under subzero temperature is extremely significant because of its influence on fuel cell performance and durability. In the study, a quasi-2D numerical model is developed and dynamic equations of mass conservation, energy conservation, membrane water conservation, ice conservation, species conservation are all considered. Three different hydrogen supply modes are studied in detail: flow-through anode (FTA) mode, dead-ended anode (DEA) mode and off-gas recirculation (OR) mode. It is found that the local current density (LCD) and temperature distribution vary remarkably along flow channel in OR mode as t > 500s due to nitrogen crossover and accumulation. During the cold start operation, the DEA mode and OR mode hold more water in anode catalyst layer (ACL) which reduces the effects of hydraulic permeation, resulting in more ice formation in cathode catalyst layer (CCL) and slower temperature rising.
Journal Article

Experimental Investigation of Proton Exchange Membrane Fuel Cell with Metal Foam Flow Field

2019-04-02
2019-01-0388
Compared with conventional flow field, metal foam has been increasingly used for gas distributor in the PEM (proton exchange membrane) fuel cell due to its high porosity and conductivity, which significantly enhances the species transport under high current density condition. In this study, the cell performances with metal foam and graphite parallel flow field are compared under normal and subzero temperature conditions. Besides, electrochemical impedance spectroscopy (EIS) is recorded to characterize the Ohmic, polarization and polarization resistance. Under normal condition, the cell with metal foam exhibits three times better performance than the one with parallel flow field. Meanwhile, the effects of inlet gas humidity and flow rates on cell performance are also studied, indicating that the cathode flooding easily occurs due to its difficult water removal. However, the high flow rate can greatly ease the cathode water flooding.
Technical Paper

Deep Optimization of Catalyst Layer Composition via Data-Driven Machine Learning Approach

2020-04-14
2020-01-0859
Proton exchange membrane fuel cell (PEMFC) provides a promising future low carbon automotive powertrain solution. The catalyst layer (CL) is its core component which directly influences the output performance. PEMFC performance can be greatly improved by the effective optimization of CL composition. This work demonstrates a deep optimization of CL composition for improving the PEMFC performance, including the platinum (Pt) loading, Pt percentage of carbon-supported Pt and ionomer to carbon ratio of the anode and the cathode,. The simulation results by a PEMFC three-dimensional (3D) computation fluid dynamics (CFD) model coupled with the CL agglomerate model is used to train the artificial neural network (ANN) which can efficiently predict the current density under different CL composition. Squared correlation coefficient (R-square) and mean percentage error in the training set and validation set are 0.9867, 0.2635% and 0.9543, 1.1275%, respectively.
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