Tuning of PEM fuel cell model parameters for prediction of steady state and dynamic performance under various operating conditions

Hydrogen and fuel cells are widely regarded as the key to energy solutions for the 21st century. These technologies will contribute significantly to a reduction in environmental impact, enhanced energy security and development of new energy industries. Fuel cells operating with hydrogen have the potential to contribute to the transition for a future sustainable energy system with low-CO2 emissions. In this paper a dynamic PEM fuel cell model, implemented in Matlab/Simulink, is presented. In order to estimate the PEM fuel cell model parameters, an optimization based approach is used. The optimization is carried out using the Simulated Annealing (SA) algorithm. This optimization process evolves converging to a minimum of the objective function. The flexibility and robustness of SA as a global search method are extremely important advantages of this method. A good agreement between experimental and simulated results is observed. This optimized PEM fuel cell model can significantly help designers of fuel cell systems by providing a tool to perform accurate design and consequently to improve system efficiency.

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PEM fuel cell model parameters optimization using modified particle swarm optimization algorithm

2013 IEEE Conference on Clean Energy and Technology (CEAT) ◽

10.1109/ceat.2013.6775672 ◽

2013 ◽

Cited By ~ 2

Author(s):

Zainuddin Mat Isa ◽

Nasrudin Abdul Rahim

Keyword(s):

Particle Swarm Optimization ◽

Fuel Cell ◽

Optimization Algorithm ◽

Particle Swarm Optimization Algorithm ◽

Cell Model ◽

Pem Fuel Cell ◽

Parameters Optimization ◽

Model Parameters ◽

Swarm Optimization ◽

Modified Particle Swarm Optimization

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PEM fuel cell model parameters extraction based on moth-flame optimization

Chemical Engineering Science ◽

10.1016/j.ces.2020.116100 ◽

2021 ◽

Vol 229 ◽

pp. 116100

Author(s):

Ramzi Ben Messaoud ◽

Adnene Midouni ◽

Salah Hajji

Keyword(s):

Fuel Cell ◽

Cell Model ◽

Pem Fuel Cell ◽

Model Parameters ◽

Parameters Extraction

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PEM fuel cell model representing steady-state, small-signal and large-signal characteristics

Journal of Power Sources ◽

10.1016/j.jpowsour.2007.06.001 ◽

2007 ◽

Vol 171 (2) ◽

pp. 754-762 ◽

Cited By ~ 10

Author(s):

P.J.H. Wingelaar ◽

J.L. Duarte ◽

M.A.M. Hendrix

Keyword(s):

Steady State ◽

Fuel Cell ◽

Cell Model ◽

Pem Fuel Cell ◽

Small Signal ◽

Large Signal ◽

Signal Characteristics

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Experimental Results of a PEM System Operated on Hydrogen and Reformate

Journal of Fuel Cell Science and Technology ◽

10.1115/1.2784324 ◽

2008 ◽

Vol 5 (1) ◽

Cited By ~ 4

Author(s):

M. Minutillo ◽

E. Jannelli ◽

F. Tunzio

Keyword(s):

Fuel Cell ◽

Natural Gas ◽

Large Scale ◽

Pem Fuel Cell ◽

Proton Exchange ◽

Operating Conditions ◽

Cell Performance ◽

Pure Hydrogen ◽

Test Bed ◽

Fuel Cell Performance

The main objective of this study is to evaluate the performance of a proton exchange membrane (PEM) fuel cell generator operating for residential applications. The fuel cell performance has been evaluated using the test bed of the University of Cassino. The experimental activity has been focused to evaluate the performance in different operating conditions: stack temperature, feeding mode, and fuel composition. In order to use PEM fuel cell technology on a large scale, for an electric power distributed generation, it could be necessary to feed fuel cells with conventional fuel, such as natural gas, to generate hydrogen in situ because currently the infrastructure for the distribution of hydrogen is almost nonexistent. Therefore, the fuel cell performance has been evaluated both using pure hydrogen and reformate gas produced by a natural gas reforming system.

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A simplified PEM fuel cell model for building cogeneration applications

Energy and Buildings ◽

10.1016/j.enbuild.2015.08.023 ◽

2015 ◽

Vol 107 ◽

pp. 213-225 ◽

Cited By ~ 25

Author(s):

Sang-Woo Ham ◽

Su-Young Jo ◽

Hye-Won Dong ◽

Jae-Weon Jeong

Keyword(s):

Fuel Cell ◽

Cell Model ◽

Pem Fuel Cell

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Theoretical Analysis on the Autothermal Reforming Process of Ethanol as Fuel for a Proton Exchange Membrane Fuel Cell System

Journal of Fuel Cell Science and Technology ◽

10.1115/1.2756844 ◽

2006 ◽

Vol 4 (4) ◽

pp. 468-473 ◽

Cited By ~ 11

Author(s):

Alessandra Perna

Keyword(s):

Fuel Cell ◽

Proton Exchange Membrane ◽

Pem Fuel Cell ◽

Cell System ◽

Autothermal Reforming ◽

Proton Exchange ◽

Operating Conditions ◽

Hydrogen Yield ◽

Fuel Cell System ◽

Exchange Membrane

The purpose of this work is to investigate, by a thermodynamic analysis, the effects of the process variables on the performance of an autothermal reforming (ATR)-based fuel processor, operating on ethanol as fuel, integrated into an overall proton exchange membrane (PEM) fuel cell system. This analysis has been carried out finding the better operating conditions to maximize hydrogen yield and to minimize CO carbon monoxide production. In order to evaluate the overall efficiency of the system, PEM fuel cell operations have been analyzed by an available parametric model.

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Pore Structure Modeling of Flow in Gas Diffusion Layers of Proton Exchange Membrane Fuel Cells

ASME 2010 8th International Fuel Cell Science, Engineering and Technology Conference: Volume 1 ◽

10.1115/fuelcell2010-33107 ◽

2010 ◽

Author(s):

Zhongying Shi ◽

Xia Wang

Keyword(s):

Fuel Cell ◽

Pore Structure ◽

Proton Exchange Membrane ◽

Cell Model ◽

Transport Phenomena ◽

Pem Fuel Cell ◽

Gas Diffusion ◽

Proton Exchange ◽

Structure Model ◽

Exchange Membrane

The gas diffusion layer (GDL) in a proton exchange membrane (PEM) fuel cell has a porous structure with anisotropic and non-homogenous properties. The objective of this research is to develop a PEM fuel cell model where transport phenomena in the GDL are simulated based on GDL’s pore structure. The GDL pore structure was obtained by using a scanning electron microscope (SEM). GDL’s cross-section view instead of surface view was scanned under the SEM. The SEM image was then processed using an image processing tool to obtain a two dimensional computational domain. This pore structure model was then coupled with an electrochemical model to predict the overall fuel cell performance. The transport phenomena in the GDL were simulated by solving the Navier-Stokes equation directly in the GDL pore structure. By comparing with the testing data, the fuel cell model predicted a reasonable fuel cell polarization curve. The pore structure model was further used to calculate the GDL permeability. The numerically predicted permeability was close to the value published in the literature. A future application of the current pore structure model is to predict GDL thermal and electric related properties.

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