A new artificial bee swarm algorithm for optimization of proton exchange membrane fuel cell model parameters

2011 ◽  
Vol 12 (8) ◽  
pp. 638-646 ◽  
Author(s):  
Alireza Askarzadeh ◽  
Alireza Rezazadeh
Keyword(s):  
Fuel Cell ◽  
Proton Exchange Membrane ◽  
Cell Model ◽  
Proton Exchange ◽  
Model Parameters ◽  
Swarm Algorithm ◽  
Exchange Membrane

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

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.

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

2012 ◽  
Vol 9 (2) ◽  
Author(s):  
Z. Shi ◽  
X. 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.

scholarly journals Open-Source Dynamic Matlab/Simulink 1D Proton Exchange Membrane Fuel Cell Model

Energies ◽  
2019 ◽  
Vol 12 (18) ◽  
pp. 3478 ◽  
Author(s):  
Arne L. Lazar ◽  
Swantje C. Konradt ◽  
Hermann Rottengruber
Keyword(s):  
Fuel Cell ◽  
Open Source ◽  
Real Time ◽  
Proton Exchange Membrane ◽  
Cell Model ◽  
Cell Voltage ◽  
Proton Exchange ◽  
Cell Parameters ◽  
Real Time Analysis ◽  
Exchange Membrane

This work presents an open-source, dynamic, 1D, proton exchange membrane fuel cell model suitable for real-time applications. It estimates the cell voltage based on activation, ohmic and concentration overpotentials and considers water transport through the membrane by means of osmosis, diffusion and hydraulic permeation. Simplified equations reduce the computational load to make it viable for real-time analysis, quick parameter studies and usage in complex systems like complete vehicle models. Two modes of operation for use with or without reference polarization curves allow for a flexible application even without information about cell parameters. The program code is written in MATLAB and provided under the terms and conditions of the Creative Commons Attribution License (CC BY). It is designed to be used inside of a Simulink model, which allows this fuel cell model to be used in a wide variety of 1D simulation platforms by exporting the code as C/C++.

Proton Exchange Membrane Fuel Cell Model

1995 ◽  
pp. 187-196 ◽  
Author(s):  
J. Divisek ◽  
J. Mosig ◽  
B. Steffen ◽  
U. Stimming
Keyword(s):  
Fuel Cell ◽  
Proton Exchange Membrane ◽  
Cell Model ◽  
Proton Exchange ◽  
Exchange Membrane

scholarly journals Thermal and Electrical Parameter Identification of a Proton Exchange Membrane Fuel Cell Using Genetic Algorithm

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2099 ◽  
Author(s):  
H. Ariza ◽  
Antonio Correcher ◽  
Carlos Sánchez ◽  
Ángel Pérez-Navarro ◽  
Emilio García
Keyword(s):  
Fuel Cell ◽  
Proton Exchange Membrane ◽  
Cell Model ◽  
Electrical Parameter ◽  
Real Data ◽  
Pem Fuel Cell ◽  
Proton Exchange ◽  
Physical Models ◽  
Real Behavior ◽  
Exchange Membrane

Proton Exchange Membrane Fuel Cell (PEMFC) fuel cells is a technology successfully used in the production of energy from hydrogen, allowing the use of hydrogen as an energy vector. It is scalable for stationary and mobile applications. However, the technology demands more research. An important research topic is fault diagnosis and condition monitoring to improve the life and the efficiency and to reduce the operation costs of PEMFC devices. Consequently, there is a need of physical models that allow deep analysis. These models must be accurate enough to represent the PEMFC behavior and to allow the identification of different internal signals of a PEM fuel cell. This work presents a PEM fuel cell model that uses the output temperature in a closed loop, so it can represent the thermal and the electrical behavior. The model is used to represent a Nexa Ballard 1.2 kW fuel cell; therefore, it is necessary to fit the coefficients to represent the real behavior. Five optimization algorithms were tested to fit the model, three of them taken from literature and two proposed in this work. Finally, the model with the identified parameters was validated with real data.

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