A Review on solid oxide fuel cell models

Kun Wang (Corresponding Author), Daniel Hissel, Marie-Cecile Péra, Nadia Steiner, Dario Marra, Marco Sorrentino, Cesare Pianese, Michela Monteverde, Pietro Cardone, Jaakko Saarinen

Research output: Contribution to journalArticleScientificpeer-review

129 Citations (Scopus)

Abstract

Since the model plays an important role in diagnosing solid oxide fuel cell (SOFC) system, this paper proposes a review of existing SOFC models for model-based diagnosis of SOFC stack and system. Three categories of modelling based on the white-, the black- and the grey-box approaches are introduced. The white-box model includes two types, i.e. physical model and equivalent circuit model based on EIS technique. The black-box model is based on artificial intelligence and its realisation relies mainly on experimental data. The grey-box model is more flexible: it is a physical representation but with some parts being modelled empirically. Validation of models is discussed and a hierarchical modelling approach involving all of three modelling methods is briefly mentioned, which gives an overview of the design for implementing a generic diagnostic tool on SOFC system.
Original languageEnglish
Pages (from-to)7212-7228
JournalInternational Journal of Hydrogen Energy
Volume36
Issue number12
DOIs
Publication statusPublished - 2011
MoE publication typeA1 Journal article-refereed

Keywords

  • SOFC
  • modelling
  • artificial intelligent
  • neural network
  • electrochemical impedance spectroscopy
  • model-based diagnosis

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