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

30 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

Fingerprint

Model predictive control
solid oxide fuel cells
Solid oxide fuel cells (SOFC)
controllers
Controllers
Derivatives
Temperature
temperature
temperature gradients
MIMO (control systems)
polynomials
output
Experiments
simulation

Keywords

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

Cite this

@article{38c8ac035ed240afbcb77ef1782e38f0,
title = "Model predictive control of the solid oxide fuel cell stack temperature with models based on experimental data",
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.",
keywords = "solid oxide fuel cells, predictive control systems, MIMO systems, temperature control, ARX model",
author = "Antti Pohjoranta and Matias Halinen and Jari Pennanen and Jari Kiviaho",
note = "Project code: 78850",
year = "2015",
doi = "10.1016/j.jpowsour.2014.11.126",
language = "English",
volume = "277",
pages = "239 -- 250",
journal = "Journal of Power Sources",
issn = "0378-7753",
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}

Model predictive control of the solid oxide fuel cell stack temperature with models based on experimental data. / Pohjoranta, Antti (Corresponding Author); Halinen, Matias; Pennanen, Jari; Kiviaho, Jari.

In: Journal of Power Sources, Vol. 277, 2015, p. 239 - 250.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - Model predictive control of the solid oxide fuel cell stack temperature with models based on experimental data

AU - Pohjoranta, Antti

AU - Halinen, Matias

AU - Pennanen, Jari

AU - Kiviaho, Jari

N1 - Project code: 78850

PY - 2015

Y1 - 2015

N2 - 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.

AB - 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.

KW - solid oxide fuel cells

KW - predictive control systems

KW - MIMO systems

KW - temperature control

KW - ARX model

U2 - 10.1016/j.jpowsour.2014.11.126

DO - 10.1016/j.jpowsour.2014.11.126

M3 - Article

VL - 277

SP - 239

EP - 250

JO - Journal of Power Sources

JF - Journal of Power Sources

SN - 0378-7753

ER -