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 journalArticle

31 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

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Keywords

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

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