DocumentCode :
674785
Title :
A proposed artificial neural network model for PEM fuel cells
Author :
Sari, Ali ; Balikci, Abdul ; Taskin, Sezai ; Aydin, Serap
Author_Institution :
Electr. & Energy Technol, Celal Bayar Univ., Manisa, Turkey
fYear :
2013
fDate :
28-30 Nov. 2013
Firstpage :
205
Lastpage :
209
Abstract :
Fuel cells convert the chemical energy directly to the electrical energy and hence they are a very favorable alternative energy source. In the literature, there are many studies related to the modeling of fuel cells. Artificial neural networks (ANNs) is one of the promising techniques for modelling nonlinear systems such as fuel cells. The proposed model in this study doesn´t require many parameters like other studies. Firstly, training and testing data was obtained the dynamic model of a PEM fuel-cell. Then, proposed ANN model outputs are compared with dynamic model ouputs Simulation results shows that the proposed ANN model can be used very efficiently for PEM fuel-cells without using many parameters.
Keywords :
neural nets; power engineering computing; proton exchange membrane fuel cells; ANN model; PEM fuel cells; alternative energy source; artificial neural network model; chemical energy; dynamic model; electrical energy; fuel cell modeling; nonlinear systems; Artificial neural networks; Data models; Fuel cells; Hydrogen; Load modeling; Mathematical model; Training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical and Electronics Engineering (ELECO), 2013 8th International Conference on
Conference_Location :
Bursa
Print_ISBN :
978-605-01-0504-9
Type :
conf
DOI :
10.1109/ELECO.2013.6713832
Filename :
6713832
Link To Document :
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