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Current and State of Charge Estimation of Lithium-Ion Battery Packs Using Distributed Fractional Extended Kalman Filters

Kupper, Martin; Creutz, Andreas; Stark, Oliver; Krebs, Stefan; Hohmann, Sören

In this paper, a method for current and state of charge estimation of lithium-ion battery packs is proposed. On the basis of a fractional 1-RQ equivalent circuit cell model, a string model containing cells in serial connection, and a pack model containing strings in parallel connection is built up. In order to reduce computational costs, the model is distributed string-wise into subsystems. An algorithm using distributed fractional extended Kalman filters is applied to estimate the state of charge of all cells of each string, locally. To avoid costly measurements of numerous currents, a model based calculation is proposed which describes how the total battery current is split up between the strings. The algorithm is tested and validated using measurement data.

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Postprint §
DOI: 10.5445/IR/1000095027
Veröffentlicht am 06.12.2020
DOI: 10.1109/CCTA.2019.8920558
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Regelungs- und Steuerungssysteme (IRS)
Publikationstyp Proceedingsbeitrag
Publikationsdatum 05.12.2019
Sprache Englisch
Identifikator ISBN: 978-1-7281-2768-2
KITopen-ID: 1000095027
HGF-Programm 37.06.01 (POF III, LK 01) Networks and Storage Integration
Erschienen in IEEE CCTA 2019
Veranstaltung IEEE Conference on Control Technology and Applications (CCTA 2019), Hongkong, Hongkong, 19.08.2019 – 21.08.2019
Verlag Institute of Electrical and Electronics Engineers (IEEE)
Seiten 462-469
Nachgewiesen in Scopus
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