Article | Proceedings of the 13th International Modelica Conference, Regensburg, Germany, March 4–6, 2019 | A Model Predictive Control Application for a Constrained Fast Charge of Lithium-ion Batteries Linköping University Electronic Press Conference Proceedings
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Title:
A Model Predictive Control Application for a Constrained Fast Charge of Lithium-ion Batteries
Author:
Alberto Romero: Service d’Automatique et d’Analyse des Systèmes, Université libre de Bruxelles, Belgium Alejandro Goldar: Service d’Automatique et d’Analyse des Systèmes, Université libre de Bruxelles, Belgium Emanuele Garone: Service d’Automatique et d’Analyse des Systèmes, Université libre de Bruxelles, Belgium
DOI:
10.3384/ecp19157229
Download:
Full text (pdf)
Year:
2019
Conference:
Proceedings of the 13th International Modelica Conference, Regensburg, Germany, March 4–6, 2019
Issue:
157
Article no.:
024
Pages:
10
No. of pages:
229-238
Publication type:
Abstract and Fulltext
Published:
2019-02-01
ISBN:
978-91-7685-122-7
Series:
Linköping Electronic Conference Proceedings
ISSN (print):
1650-3686
ISSN (online):
1650-3740
Publisher:
Linköping University Electronic Press, Linköpings universitet


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The spread of electrical storage devices continues to be underpinned by the limited charging currents that can be applied. The limitation arises from the lack of sufficient high power charging stations, either at home or along roads and highways, and from the maximum admissible current that can be applied to the battery before undesirable degradation mechanisms are triggered. Accordingly, most traditional charging protocols limit the charging current as a function of the standing state of charge of the battery. These protocols are designed empirically and restrict the potential benefit of more flexible charging options. However, the alternative to traditional protocols must rely on a more precise knowledge of the operating constraints and on advanced control techniques to compute online the best operating plan. This work presents a model predictive control (MPC) application to minimize the charging time of a lithium-ion battery subject to electrochemical and thermal constraints. The satisfaction of these constraints ensures that the battery degradation is minimized, or at least mitigated. The programming language Modelica and the optimization and simulation framework JModelica. org is used in combination with Python language to assess the computing time and potential use of MPC and the developed cell models in commercial batteries.

Keywords: Fast-charge, nonlinear MPC, optimization, battery aging

Proceedings of the 13th International Modelica Conference, Regensburg, Germany, March 4–6, 2019

Author:
Alberto Romero, Alejandro Goldar, Emanuele Garone
Title:
A Model Predictive Control Application for a Constrained Fast Charge of Lithium-ion Batteries
DOI:
http://dx.doi.org/10.3384/ecp19157229
References:
No references available

Proceedings of the 13th International Modelica Conference, Regensburg, Germany, March 4–6, 2019

Author:
Alberto Romero, Alejandro Goldar, Emanuele Garone
Title:
A Model Predictive Control Application for a Constrained Fast Charge of Lithium-ion Batteries
DOI:
https://doi.org10.3384/ecp19157229
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Last updated: 2019-06-04