Advances in Radio Science
Advances in Radio Science
ARS
Articles | Volume 15
Articles | Volume 15
https://doi.org/10.5194/ars-15-93-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/ars-15-93-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Articles | Volume 15
21 Sep 2017
 | 21 Sep 2017

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

Marian Patrik Felder and Jürgen Götze

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Short summary
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 internal characteristics, several existing methods cannot be used. This work describes an impedance based approach using the Taylor Fourier transformation. The parameters extracted by the method can be used as features in machine learning algorithms.
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