Research On The Estimation Of Lithium Battery SOC Based On EKF

DOI

10.2991/mmat.2013.18How to use a DOI?

Keywords

Lithium-ion battery, State of charge, Extended Kalman filter, Battery model.

Abstract

In the battery management system, the SOC estimation is the most basic and most important part. The exact estimation of SOC can prevent battery over-change or over-change, and extend battery life. Based on traditional SOC estimate algorithm and analysis of factors affecting SOC, the method to estimate stalling state and charge-discharge state of battery respectively is applied to predict SOC of lithium-ion battery. Especially in charge-discharge state, extended Kalman filter is applied in estimation. A state space model of a lithium-ion battery based on Thevenin model is established, which has the advantage of simplicity and could be easily implemented. Matlab simulation and experiments were carried out. Comparison indicates that performance of the model accords well with that of lithium-ion battery. The extended Kalman filter keeps an excellent precision in full range of the SOC, and performs well when initial error of disturbance happens.

Copyright

© 2013, 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  - Zhi-sheng An
AU  - Zhi-yi Sun
AU  - Qiu-sheng He
PY  - 2012/11
DA  - 2012/11
TI  - Research On The Estimation Of Lithium Battery SOC Based On EKF
BT  - Proceedings of the 2012 International Conference on Automobile and Traffic Science, Materials and Metallurgy Engineering
PB  - Atlantis Press
SP  - 91
EP  - 95
SN  - 1951-6851
UR  - https://doi.org/10.2991/mmat.2013.18
DO  - 10.2991/mmat.2013.18
ID  - An2012/11
ER  -