University of Oulu

M. Ohenoja, A. Sorsa and K. Leiviskä, "Genetic Algorithms in Model Structure Identification for Fuel Cell Polarization Curve," 2018 5th International Conference on Control, Decision and Information Technologies (CoDIT), Thessaloniki, 2018, pp. 539-544. doi: 10.1109/CoDIT.2018.8394829

Genetic algorithms in model structure identification for fuel cell polarization curve

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Author: Ohenoja, Markku1; Sorsa, Aki1; Leiviskä, Kauko1
Organizations: 1Control Engineering Research Group, University of Oulu, P.O.Box 4300, 90014 Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.4 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2018082133861
Language: English
Published: Institute of Electrical and Electronics Engineers, 2018
Publish Date: 2018-08-21
Description:

Abstract

Evolutionary optimizers, such as genetic algorithms, have earlier been successfully applied to find the parameter values for the fuel cell polarization curve models. The structure of these, typically semi-empirical, models have evolved during the decades. In this study, the model structures were reviewed and a new model structure was generated. Genetic algorithms were used to determine the optimized model structure with linear model parameters. Four different fuel cells, one with varying operating conditions, were studied. The results show that the model can outperform the semi-empirical model utilized in number of studies without increasing the model complexity.

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Series: International Conference on Control, Decision and Information Technologies
ISSN: 2576-3547
ISSN-E: 2576-3555
ISSN-L: 2576-3547
ISBN: 978-1-5386-5065-3
ISBN Print: 978-1-5386-5066-0
Pages: 1 - 6
DOI: 10.1109/CoDIT.2018.8394829
OADOI: https://oadoi.org/10.1109/CoDIT.2018.8394829
Host publication: 2018 5th International Conference on Control, Decision and Information Technologies (CoDIT), 10-3 April 2018, Thessaloniki, Greece
Conference: International Conference on Control, Decision and Information Technologies (CoDIT)
Type of Publication: A4 Article in conference proceedings
Field of Science: 215 Chemical engineering
222 Other engineering and technologies
Subjects:
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