University of Oulu

Ohenoja, M., Sorsa, A., & Leiviskä, K. (2018). Model Structure Optimization for Fuel Cell Polarization Curves. Computers, 7(4), 60. doi:10.3390/computers7040060

Model structure optimization for fuel cell polarization curves

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Author: Ohenoja, Markku1; Sorsa, Aki1; Leiviskä, Kauko1
Organizations: 1Control Engineering, University of Oulu
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 1.6 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2018121150373
Language: English
Published: Multidisciplinary Digital Publishing Institute, 2018
Publish Date: 2018-12-11
Description:

Abstract

The applications of evolutionary optimizers such as genetic algorithms, differential evolution, and various swarm optimizers to the parameter estimation of the fuel cell polarization curve models have increased. This study takes a novel approach on utilizing evolutionary optimization in fuel cell modeling. Model structure identification is performed with genetic algorithms in order to determine an optimized representation of a polarization curve model with linear model parameters. The optimization is repeated with a different set of input variables and varying model complexity. The resulted model can successfully be generalized for different fuel cells and varying operating conditions, and therefore be readily applicable to fuel cell system simulations.

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Series: Computers
ISSN: 2073-431X
ISSN-E: 2073-431X
ISSN-L: 2073-431X
Volume: 7
Issue: 4
Article number: 60
DOI: 10.3390/computers7040060
OADOI: https://oadoi.org/10.3390/computers7040060
Type of Publication: A1 Journal article – refereed
Field of Science: 215 Chemical engineering
Subjects:
Copyright information: © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
  https://creativecommons.org/licenses/by/4.0/