Online estimation of internal stack temperatures in solid oxide fuel cell power generating units

B. Dolenc (Corresponding Author), D. Vrečko, Ɖ. Juričić, Antti Pohjoranta, C. Pianese

    Research output: Contribution to journalArticleScientificpeer-review

    11 Citations (Scopus)


    Thermal stress is one of the main factors affecting the degradation rate of solid oxide fuel cell (SOFC) stacks. In order to mitigate the possibility of fatal thermal stress, stack temperatures and the corresponding thermal gradients need to be continuously controlled during operation. Due to the fact that in future commercial applications the use of temperature sensors embedded within the stack is impractical, the use of estimators appears to be a viable option. In this paper we present an efficient and consistent approach to data-driven design of the estimator for maximum and minimum stack temperatures intended (i) to be of high precision, (ii) to be simple to implement on conventional platforms like programmable logic controllers, and (iii) to maintain reliability in spite of degradation processes. By careful application of subspace identification, supported by physical arguments, we derive a simple estimator structure capable of producing estimates with 3% error irrespective of the evolving stack degradation. The degradation drift is handled without any explicit modelling. The approach is experimentally validated on a 10 kW SOFC system.
    Original languageEnglish
    Pages (from-to)251-260
    JournalJournal of Power Sources
    Publication statusPublished - 2016
    MoE publication typeA1 Journal article-refereed


    • Data-driven estimator
    • Degradation compensation
    • Inner stack temperatures
    • Model structure identification
    • Solid oxide fuel cell (SOFC) systems
    • Bacteriology
    • Degradation
    • Estimation
    • Fuel cells
    • Programmable logic controllers
    • Thermal stress
    • Commercial applications
    • Data driven
    • Data-driven design
    • Degradation process
    • On-line estimation
    • Stack temperature
    • Structure identification
    • Subspace identification
    • Solid oxide fuel cells (SOFC)


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