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State of charge and state of health diagnosis of batteries with voltage-controlled models

  • The accurate diagnosis of state of charge (SOC) and state of health (SOH) is of utmost importance for battery users and for battery manufacturers. State diagnosis is commonly based on measuring battery current and using it in Coulomb counters or as input for a current-controlled model. Here we introduce a new algorithm based on measuring battery voltage and using it as input for aThe accurate diagnosis of state of charge (SOC) and state of health (SOH) is of utmost importance for battery users and for battery manufacturers. State diagnosis is commonly based on measuring battery current and using it in Coulomb counters or as input for a current-controlled model. Here we introduce a new algorithm based on measuring battery voltage and using it as input for a voltage-controlled model. We demonstrate the algorithm using fresh and pre-aged lithium-ion battery single cells operated under well-defined laboratory conditions on full cycles, shallow cycles, and a dynamic battery electric vehicle load profile. We show that both SOC and SOH are accurately estimated using a simple equivalent circuit model. The new algorithm is self-calibrating, is robust with respect to cell aging, allows to estimate SOH from arbitrary load profiles, and is numerically simpler than state-of-the-art model-based methods.show moreshow less

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Metadaten
Document Type:Article (reviewed)
Zitierlink: https://opus.hs-offenburg.de/6049
Bibliografische Angaben
Title (English):State of charge and state of health diagnosis of batteries with voltage-controlled models
Author:Jonas A. BraunStaff MemberORCiD, René BehmannStaff MemberORCiDGND, David SchmiderStaff MemberORCiD, Wolfgang G. BesslerStaff MemberORCiDGND
Year of Publication:2022
Date of first Publication:2022/10/01
Publisher:Elsevier
First Page:1
Last Page:11
Article Number:231828
Parent Title (English):Journal of Power Sources
Volume:544
ISSN:0378-7753 (Print)
ISSN:1873-2755 (eISSN)
DOI:https://doi.org/10.1016/j.jpowsour.2022.231828
URL:https://www.sciencedirect.com/science/article/pii/S0378775322008175?via%3Dihub
Language:English
Inhaltliche Informationen
Institutes:Forschung / INES - Institut für nachhaltige Energiesysteme
Fakultät Maschinenbau und Verfahrenstechnik (M+V)
DDC classes:600 Technik, Medizin, angewandte Wissenschaften
Tag:batteries; charge; voltage
Formale Angaben
Relevance:Wiss. Zeitschriftenartikel reviewed: Listung in Master Journal List
Open Access: Open Access 
 Diamond 
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International