Potential-dependent electrolyte resistance and steady-state multiplicities of PEM fuel cells

2006 ◽  
Vol 177 (26-32) ◽  
pp. 2397-2401 ◽  
Author(s):  
A KATSAOUNIS ◽  
M TSAMPAS ◽  
S BALOMENOU ◽  
D TSIPLAKIDES ◽  
C VAYENAS
Keyword(s):  
Fuel Cells ◽  
Steady State ◽  
Pem Fuel Cells ◽  
Electrolyte Resistance

scholarly journals STEADY-STATE MODELLING OF PEM FUEL CELLS USING GRADIENT-BASED OPTIMIZER

10.6036/10099 ◽  
2021 ◽  
Vol DYNA-ACELERADO (0) ◽  
pp. [ 8 pp.]-[ 8 pp.]
Author(s):  
SALAH KAMAL ◽  
ATTIA EL-FERGANY ◽  
EHAB EHAB ELSAYED ELATTAR ◽  
AHMED AGWA
Keyword(s):  
Fuel Cells ◽  
Steady State ◽  
Fuel Cell ◽  
Optimization Problem ◽  
Pem Fuel Cells ◽  
Test Cases ◽  
Uncertain Parameters ◽  
Gradient Based ◽  
High Degree ◽  
Exchange Membrane

The accuracy of fuel cell (FC) models is important for the further numerical simulations and analysis at several conditions. The electrical (I-V) characteristic of the polymer exchange membrane fuel cells (PEMFCs) has high degree of nonlinearity comprising uncertain seven parameters as they aren’t given in fabricator's datasheets. These seven parameters need to be obtained to have the PEMFC model in order. This research addresses an up-to-date application of the gradient-based optimizer (GBO) to generate the best estimated values of such uncertain parameters. The estimation of these uncertain parameters is adapted as optimization problem having a cost function (CF) subjects to set of self-constrained limits. Three test cases of widely used PEMFCs units; namely, SR-12, 250-W module and NedStack PS6 to appraise the performance of the GBO are demonstrated and analyzed. The best values of the CF are 0.000142, 0.33598, and 2.10025 V2 for SR-12, 250-W module and NedStack PS6; respectively. Furthermore, the assessment of the GBO-based model is made by comparing its obtained results with the experiential results of these typical PEMFCs plus comparisons to other methods. At a due stage, many scenarios as a result of operating variations in regard to inlet regulation pressures and unit temperatures are performed. The copped reported results of the studied scenarios indicate the effectiveness of the GBO in establishing an accurate PEMFC model.

Steady State Multiplicities in Low Temperature PEM Fuel Cells

2018 ◽  
Vol 5 (14) ◽  
pp. 27397-27405
Author(s):  
E. Martino ◽  
A. Gusev ◽  
A. Katsaounis ◽  
C.G. Vayenas
Keyword(s):  
Fuel Cells ◽  
Steady State ◽  
Low Temperature ◽  
Pem Fuel Cells

scholarly journals Steady-State Modeling of Fuel Cells Based on Atom Search Optimizer

Energies ◽  
2019 ◽  
Vol 12 (10) ◽  
pp. 1884 ◽  
Author(s):  
Ahmed M. Agwa ◽  
Attia A. El-Fergany ◽  
Gamal M. Sarhan
Keyword(s):  
Fuel Cells ◽  
Steady State ◽  
Fuel Cell ◽  
Cell Model ◽  
Optimization Methods ◽  
Pem Fuel Cells ◽  
Vital Role ◽  
Unknown Parameters ◽  
Steady State Condition ◽  
Search Optimization

In simulation studies, the precision of fuel cell models has a vital role in the quality of results. Unfortunately, due to the shortage of manufacturer data given in the datasheets, several unknown parameters should be defined to establish the fuel cell model for further precise analysis. This research addresses a novel application of the atom search optimization (ASO) algorithm to generate these unknown parameters of the fuel cell model and in particular of the polymer exchange membrane (PEM) type. The objective of this study is to establish an accurate model of the PEM fuel cells, which will provide accurate results of modeling and simulation in a steady-state condition. Simulations and further demonstrations were performed under MATLAB/SIMULINK. The viability of the proposed models was appraised by comparing its simulation results with the experimental results of number of commercial PEM fuel cells. In the same context, the obtained numerical results by the proposed ASO-based method were compared to other challenging optimization methods-based results. Finally, parametric tests were made which indicated the robustness of the ASO results as well. It can be stated here that ASO performs well and has a good capability to extract the unknown parameters with lesser errors.

Modeling and Simulations of Polymer Electrolyte Membrane Fuel Cells With Poroelastic Approach for Coupled Liquid Water Transport and Deformation in the Membrane

2010 ◽  
Vol 7 (3) ◽  
Author(s):  
Serhat Yesilyurt
Keyword(s):  
Fuel Cells ◽  
Steady State ◽  
Polymer Electrolyte ◽  
Polymer Electrolyte Membrane ◽  
Pem Fuel Cells ◽  
Gas Diffusion ◽  
Two Dimensional ◽  
Gas Diffusion Layers ◽  
Electrolyte Membrane ◽  
Diffusion Layers

Performance degradation and durability of polymer electrolyte membrane (PEM) fuel cells depend strongly on transport and deformation characteristics of their components especially the polymer membrane. Physical properties of membranes, such as ionic conductivity and Young’s modulus, depend on the water content that varies significantly with operating conditions and during transients. Recent studies indicate that cyclic transients may induce hygrothermal fatigue that leads to the ultimate failure of the membrane shortening its lifetime and, thus, hindering the reliable use of PEM fuel cells for automotive applications. In this work, we present two-dimensional simulations and analysis of coupled deformation and transport in PEM fuel cells to improve the understanding of membrane deformation under steady-state and transient conditions. A two-dimensional cross section of anode and cathode gas diffusion layers, and the membrane sandwiched between them is modeled using Maxwell–Stefan equations for species transport in gas diffusion layers, Biot’s poroelasticity, Darcy’s law for deformation and water transport in the membrane, and Ohm’s law for ionic currents in the membrane and electric currents in the gas diffusion layers. Steady-state deformation and transport of water in the membrane, transient responses to step changes in load, and relative humidity of the anode and cathode are obtained from simulation experiments, which are conducted by means of a commercial finite-element package, COMSOL MULTIPHYSICS.

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