Hybrid Approach to Remaining Useful Life Prediction of Solid Oxide Fuel Cell Stack

Bostjan Dolenc, Pavle Boskoski, Antti Pohjoranta, Matti Noponen, Dani Juricic

    Research output: Contribution to journalArticleScientificpeer-review

    9 Citations (Scopus)


    Improvement in efficiency and reliability are essential for more intensive deployment and commercial exploitation of solid oxide fuel cell (SOFC) systems. Apart of advancement in fabrication of new materials and stack designs, there emerges a strong need for innovative control strategies capable of balancing maximal stack life and efficiency of power conversion in a trade-off manner. Reliable online estimation of stack health and prediction of the remaining useful life (RUL) play a key role in new generation of SOFC control systems. In most works until today, the authors utilize voltage as a health index and based on that predict the RUL. Unfortunately, such an approach becomes inappropriate when the SOFC is operating under varying load conditions and, in particular, when the SOFC ages. In this paper, we propose a novel hybrid approach to RUL prediction of SOFC systems, which overcomes the limitations of the known approaches and allows for reliable RUL prediction in non-stationary operating conditions. The approach consists of three main parts, executed continuously online: (i) estimation of area specific resistance (ASR) of the stack, (ii) prediction of its future progress based on collected data, and (iii) prediction of RUL. The methodology is evaluated on a 6 kW SOFC system.
    Original languageEnglish
    Pages (from-to)2251-2264
    JournalECS Transactions
    Issue number1
    Publication statusPublished - 30 May 2017
    MoE publication typeA1 Journal article-refereed
    Event15th International Symposium on Solid Oxide Fuel Cells, SOFC XV - Hollywood, United States
    Duration: 23 Jul 201728 Jul 2017


    The research leading to these results received funding from the European Union’s Seventh Framework Program (FP7/2007-2013) for the Fuel Cells and Hydrogen Joint Technology Initiative under grant agreement No. 621208 (Project - DIAMOND, Diagnosis-Aided Control for SOFC Power Systems). The support of the Slovenian Research Agency through Research Program P2-0001 and the research project L2-7663 is gratefully acknowledged.


    • SOFC
    • diagnostics
    • estimation


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