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

Antti Pohjoranta; Matias Halinen; Jari Pennanen; Jari Kiviaho

doi:10.1016/j.jpowsour.2014.11.126

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 journal › Article › Scientific › peer-review

29 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 language	English
Pages (from-to)	239 - 250
Journal	Journal of Power Sources
Volume	277
DOIs	https://doi.org/10.1016/j.jpowsour.2014.11.126
Publication status	Published - 2015
MoE publication type	A1 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

Pohjoranta, A., Halinen, M., Pennanen, J., & Kiviaho, J. (2015). Model predictive control of the solid oxide fuel cell stack temperature with models based on experimental data. Journal of Power Sources, 277, 239 - 250. https://doi.org/10.1016/j.jpowsour.2014.11.126

Pohjoranta, Antti ; Halinen, Matias ; Pennanen, Jari ; Kiviaho, Jari. / Model predictive control of the solid oxide fuel cell stack temperature with models based on experimental data. In: Journal of Power Sources. 2015 ; Vol. 277. pp. 239 - 250.

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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",

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Pohjoranta, A, Halinen, M, Pennanen, J & Kiviaho, J 2015, 'Model predictive control of the solid oxide fuel cell stack temperature with models based on experimental data', Journal of Power Sources, vol. 277, pp. 239 - 250. https://doi.org/10.1016/j.jpowsour.2014.11.126

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 journal › Article › Scientific › peer-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

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