Investigation on Early-stage Internal Short Circuit Identification for Power Battery Pack

DOI

10.2991/seeie-19.2019.54How to use a DOI?

Keywords

lithium-ion battery; internal short circuit; identification algorithm; mean-difference model; early stage

Abstract

The spontaneous internal short circuit is a very important way for the thermal runaway of lithium-ion battery. Identification of the internal short circuit accurately and in time during the working process is critical for the safety of lithium-ion battery. In this study, a modified algorithm for the early-stage internal short circuit identification is investigated. This method is based on the mean-difference model and the recursive least square algorithm. An equivalent experiment is setup to validate the feasibility of this method for the identification of early-stage internal short circuit. The results indicate that this method can identify the internal short circuit only when the SOC is very low. For ordinary operation conditions of the power battery pack, this method is not suitable for early-stage internal short circuit identification.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xu Zhang
AU  - Yue Pan
AU  - Enhua Wang
AU  - Minggao Ouyang
AU  - Languang Lu
AU  - Xuebing Han
AU  - Guoqing Jin
AU  - Anjian Zhou
AU  - Huiqian Yang
PY  - 2019/05
DA  - 2019/05
TI  - Investigation on Early-stage Internal Short Circuit Identification for Power Battery Pack
BT  - Proceedings of the 2019 2nd International Conference on Sustainable Energy, Environment and Information Engineering (SEEIE 2019)
PB  - Atlantis Press
SP  - 233
EP  - 235
SN  - 2352-5401
UR  - https://doi.org/10.2991/seeie-19.2019.54
DO  - 10.2991/seeie-19.2019.54
ID  - Zhang2019/05
ER  -