Identification of electrochemical model parameters in PEM fuel cells

The target in this paper is to show how Genetic Algorithms apply for parameter identification of different fuel cells. Therefore, two electrochemical models have been fitted for three different fuel cells. The data originates in the current vs. voltage curves (polarization curves) from the published...

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Main Authors: Ohenoja, M., Leiviska, K.
Format: Conference Proceeding
Language:English
Subjects:
Biological cells
Biomembranes
Equations
Fuel cells
Genetic algorithms
Parameter estimation
Polarization
Power system modeling
Temperature
Voltage
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Leiviska, K.
description The target in this paper is to show how Genetic Algorithms apply for parameter identification of different fuel cells. Therefore, two electrochemical models have been fitted for three different fuel cells. The data originates in the current vs. voltage curves (polarization curves) from the published literature. The results seem promising - a real-coded Genetic Algorithm seems to provide with the model parameters that take the properties of the fuel cells into account. The test material is, however, too small to draw more solid conclusions.
doi_str_mv 10.1109/POWERENG.2009.4915201
format conference_proceeding
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subjects Biological cells
Biomembranes
Equations
Fuel cells
Genetic algorithms
Parameter estimation
Polarization
Power system modeling
Temperature
Voltage
title Identification of electrochemical model parameters in PEM fuel cells
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