Model predictive control of the solid oxide fuel cell stack temperature with models based on experimental data

Antti Pohjoranta (Corresponding Author), Matias Halinen, Jari Pennanen, Jari Kiviaho

    Research output: Contribution to journalArticleScientificpeer-review

    35 Citations (Scopus)

    Abstract

    Generalized predictive control (GPC) is applied to control the maximum temperature in a solid oxide fuel cell (SOFC) stack and the temperature difference over the stack. GPC is a model predictive control method and the models utilized in this work are ARX-type (autoregressive with extra input), multiple input-multiple output, polynomial models that were identified from experimental data obtained from experiments with a complete SOFC system. The proposed control is evaluated by simulation with various input–output combinations, with and without constraints. A comparison with conventional proportional-integral-derivative (PID) control is also made. It is shown that if only the stack maximum temperature is controlled, a standard PID controller can be used to obtain output performance comparable to that obtained with the significantly more complex model predictive controller. However, in order to control the temperature difference over the stack, both the stack minimum and the maximum temperature need to be controlled and this cannot be done with a single PID controller. In such a case the model predictive controller provides a feasible and effective solution.
    Original languageEnglish
    Pages (from-to)239 - 250
    JournalJournal of Power Sources
    Volume277
    DOIs
    Publication statusPublished - 2015
    MoE publication typeA1 Journal article-refereed

    Keywords

    • solid oxide fuel cells
    • predictive control systems
    • MIMO systems
    • temperature control
    • ARX model

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