State of charge classification for lithium-ion batteries using impedance based features

Currently, the electrification of the drive train of passenger cars takes place, and the task of obtaining precise knowledge about the condition of the on board batteries gains importance. Due to a flat open circuit voltage (OCV) to state of charge (SoC) characteristic of lithium ion batteries, m...

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Main Authors: M. P. Felder, J. Götze
Format: Article
Language:deu
Published: Copernicus Publications 2017-09-01
Series:Advances in Radio Science
Online Access:https://www.adv-radio-sci.net/15/93/2017/ars-15-93-2017.pdf
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spelling doaj-0ca0d374f46946258c5f293d8ed561cb2020-11-24T21:14:34ZdeuCopernicus PublicationsAdvances in Radio Science 1684-99651684-99732017-09-0115939710.5194/ars-15-93-2017State of charge classification for lithium-ion batteries using impedance based featuresM. P. Felder0J. Götze1Information Processing Lab, TU Dortmund University, 44221 Dortmund, GermanyInformation Processing Lab, TU Dortmund University, 44221 Dortmund, GermanyCurrently, the electrification of the drive train of passenger cars takes place, and the task of obtaining precise knowledge about the condition of the on board batteries gains importance. Due to a flat open circuit voltage (OCV) to state of charge (SoC) characteristic of lithium ion batteries, methods employed in applications with other cell chemistries cannot be adapted. Exploiting the higher significance of the impedance for state estimation for that chemistry, new impedance based features are proposed by this work. To evaluate the suitability of these features, simulations have been conducted using a simplified on-board power supply net as excitation source. The simulation outcome has been investigated regarding the cross correlation factor <i>r</i><sub><i>x</i><i>y</i></sub> and in a polynomial regression scenario. The results of the simulations show a best case error below 1 <i>%</i> SoC, which is 3 percentage points lower than using terminal voltage and impedance. When increasing the measurement uncertainty, the difference remains around 2 percent points.https://www.adv-radio-sci.net/15/93/2017/ars-15-93-2017.pdf
collection DOAJ
language deu
format Article
sources DOAJ
author M. P. Felder
J. Götze
spellingShingle M. P. Felder
J. Götze
State of charge classification for lithium-ion batteries using impedance based features
Advances in Radio Science
author_facet M. P. Felder
J. Götze
author_sort M. P. Felder
title State of charge classification for lithium-ion batteries using impedance based features
title_short State of charge classification for lithium-ion batteries using impedance based features
title_full State of charge classification for lithium-ion batteries using impedance based features
title_fullStr State of charge classification for lithium-ion batteries using impedance based features
title_full_unstemmed State of charge classification for lithium-ion batteries using impedance based features
title_sort state of charge classification for lithium-ion batteries using impedance based features
publisher Copernicus Publications
series Advances in Radio Science
issn 1684-9965
1684-9973
publishDate 2017-09-01
description Currently, the electrification of the drive train of passenger cars takes place, and the task of obtaining precise knowledge about the condition of the on board batteries gains importance. Due to a flat open circuit voltage (OCV) to state of charge (SoC) characteristic of lithium ion batteries, methods employed in applications with other cell chemistries cannot be adapted. Exploiting the higher significance of the impedance for state estimation for that chemistry, new impedance based features are proposed by this work. To evaluate the suitability of these features, simulations have been conducted using a simplified on-board power supply net as excitation source. The simulation outcome has been investigated regarding the cross correlation factor <i>r</i><sub><i>x</i><i>y</i></sub> and in a polynomial regression scenario. The results of the simulations show a best case error below 1 <i>%</i> SoC, which is 3 percentage points lower than using terminal voltage and impedance. When increasing the measurement uncertainty, the difference remains around 2 percent points.
url https://www.adv-radio-sci.net/15/93/2017/ars-15-93-2017.pdf
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AT jgotze stateofchargeclassificationforlithiumionbatteriesusingimpedancebasedfeatures
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