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it - Information Technology

Methods and Applications of Informatics and Information Technology

Editor-in-Chief: Molitor, Paul

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2196-7032
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Modeling of battery life optimal charging strategies based on empirical mobility data

Jennifer Schoch
  • Karlsruhe Institute of Technology, Englerstr. 14, 76131 Karlsruhe
  • :
Published Online: 2016-02-09 | DOI: https://doi.org/10.1515/itit-2015-0043

Abstract

Battery electric vehicles (EVs) have a more limited range and longer refueling, i. e. charging times accompanied by battery aging as conventional vehicles. Initial field studies about the behavior of EV users also have identified the presence of range anxiety, which is expressed by frequent recharging. Battery aging is a non-linear process with numerous interactions, but generally pronounced around higher state of charge (SoC) levels. Therefore, range anxiety potentially provokes elevated battery degradation due to the resulting operating conditions. Based on 2966 empirical driving profiles, I analyze different user groups as well as the effect of different charging strategies in a simulation-based analysis. In comparison to charging strategies, for instance as fast as possible (AFAP) charging or critical SoC charging (such that the next trip is feasible), I calculate the degradation optimal charging pattern based on a realistic battery cell aging model. The model is derived from accelerated aging tests of Li-NMC 18650 cells, but can be adjusted to individual degradation parameters, in order to account for different battery chemistries. Preliminary results show that degradation can be reduced by up to 46% by the optimized charging strategy as compared to AFAP or critical SoC charging.

Keywords: Battery aging; smart charging; range anxiety; electric vehicle

ACM CCS: Hardware→Power and energy

Jennifer Schoch

Jennifer Schoch received her M.Sc. in Electrical Engineering and Information Technology from the Karlsruhe Institute of Technology (KIT) in 2014. She is currently a PhD student at KIT. Her research interests include electric mobility, battery degradation and user behavior.

Karlsruhe Institute of Technology, Englerstr. 14, 76131 Karlsruhe


Accepted: 2015-11-06

Received: 2015-10-15

Published Online: 2016-02-09

Published in Print: 2016-02-01


Citation Information: it - Information Technology. Volume 58, Issue 1, Pages 22–28, ISSN (Online) 2196-7032, ISSN (Print) 1611-2776, DOI: https://doi.org/10.1515/itit-2015-0043, February 2016

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