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at - Automatisierungstechnik

Methoden und Anwendungen der Steuerungs-, Regelungs- und Informationstechnik

[AT - Automation Technology: Methods and Applications of Control, Regulation, and Information Technology
]

Editor-in-Chief: Jumar, Ulrich


IMPACT FACTOR 2017: 0.503

CiteScore 2017: 0.47

SCImago Journal Rank (SJR) 2017: 0.212
Source Normalized Impact per Paper (SNIP) 2017: 0.546

Online
ISSN
2196-677X
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Volume 62, Issue 4

Issues

Model-based On-board Monitoring for Lithium-Ion Batteries

Modellbasierte On-board-Überwachung von Lithium-Ionen-Batterien

Jürgen Remmlinger / Michael Buchholz / Klaus Dietmayer
Published Online: 2014-03-28 | DOI: https://doi.org/10.1515/auto-2013-1046

Abstract

Monitoring of lithium-ion batteries is a challenging task due to the nonlinear behavior, especially on-board a vehicle. In this article, a model-based monitoring method for an automotive battery pack is presented based on a linear parameter-varying model. The model is obtained by system identification using cell measurement data and extended to the battery pack. It is shown how such a model can be used either for cell temperature monitoring or for monitoring of the state of health of the battery. Results are demonstrated using driving cycle measurements from a battery pack for hybrid vehicles.

Zusammenfassung

Die Überwachung von Lithium-Ionen Batterien im Betrieb ist aufgrund ihres nichtlinearen Verhaltens eine herausfordernde Aufgabe, insbesondere in Elektrofahrzeugen. In diesem Beitrag wird ein modellbasierter Überwachungsansatz präsentiert, der auf einem linearen Modell mit variierenden Parametern beruht. Das Modell wird mittels Methoden der Systemidentifikation aus Messdaten von Batteriezellen gewonnen und auf die Gesamtbatterie erweitert. Es wird gezeigt, wie dieses Modell entweder zur Temperaturüberwachung der einzelnen Batteriezellen oder für die Überwachung des Alterungszustands der Batterie genutzt werden kann. Die Ergebnisse werden anhand von Fahrzyklus-Messdaten einer Batterie für Hybridfahrzeuge veranschaulicht.

Schlagwörter: Lithium-Ionen-Batterie; State-of-Health; Batterietemperatur; Batterie-Überwachung; LPV-Modell

Keywords: Lithium-Ion Battery; State-of-Health; Battery Temperature; Battery Monitoring; LPV model

About the article

Jürgen Remmlinger

Dipl.-Ing. Jürgen Remmlinger received his diploma degree in Electrical Engineering and Information Technology from Karlsruhe Institute of Technology in 2009. Since 2010, he is a Researcher at the Institute of Measurement, Control, and Microtechnology at Ulm University, working towards his Ph.D degree in the field of modeling and diagnosis of lithium-ion batteries.

Universität Ulm, Institut für Mess-, Regel- und Mikrotechnik, Albert-Einstein-Allee 41, D-89081 Ulm, Tel.: +49-(0)731-50-26308 Fax: +49-(0)731-50-26301

Michael Buchholz

Dr.-Ing. Michael Buchholz is a Group Leader and Lecturer (“Akademischer Oberrat”) at the Institute of Measurement, Control, and Microtechnology at Ulm University. His main research interests comprise system identification and diagnosis, electric mobility, and mechatronical systems.

Universität Ulm, Institut für Mess-, Regel- und Mikrotechnik, Albert-Einstein-Allee 41, D-89081 Ulm, Tel.: +49-(0)731-50-26334 Fax: +49-(0)731-50-12-26334

Klaus Dietmayer

Prof. Dr.-Ing. Klaus Dietmayer is director of the Institute of Measurement, Control, and Microtechnology at Ulm University and head of driveU. His main research interests are information fusion, classification methods, stochastic filters and tracking, signal processing, and dynamical modeling.

Universität Ulm, Institut für Mess-, Regel- und Mikrotechnik, Albert-Einstein-Allee 41, D-89081 Ulm, Tel.: +49-(0)731-50-26300 Fax: +49-(0)731-50-26301


Accepted: 2014-02-05

Received: 2013-06-17

Published Online: 2014-03-28

Published in Print: 2014-04-28


Citation Information: at – Automatisierungstechnik, Volume 62, Issue 4, Pages 282–295, ISSN (Online) 2196-677X, ISSN (Print) 0178-2312, DOI: https://doi.org/10.1515/auto-2013-1046.

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