Parallel Arithmetical Unscented Kalman Filter Technic for Lithium-ion Battery State-of-Charge Estimation

DOI

10.2991/icadme-16.2016.119How to use a DOI?

Keywords

Lithium-ion battery; State-of-Charge(SOC); Battery model; Parallel arithmetic; Unscented Kalman filter(UKF)

Abstract

In order to apply the lithium-ion batteries on the electric vehicles reliably and safely, estimating the internal statements of the batteries, such as the state-of-charge (SOC) is obligatory. The purpose of this work was to present a SOC estimation method named parallel arithmetical unscented Kalman filter which has obvious advantages that was validated by simulation. In this paper, a lumped circuit model and the parameter identification method were studied. And the state-space type battery model was derived. Then a novel SOC estimation method was proposed using the parallel arithmetical unscented Kalman filter (PAUKF) technique. Validation results showed that the presented SOC estimation algorithm could have an acceptable performance with the mean error less than 2.4%.

Copyright

© 2016, 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  - Weilong Liu
AU  - Liye Wang
AU  - Lifang Wang
AU  - Chenglin Liao
PY  - 2017/07
DA  - 2017/07
TI  - Parallel Arithmetical Unscented Kalman Filter Technic for Lithium-ion Battery State-of-Charge Estimation
BT  - Proceedings of the 2016 6th International Conference on Advanced Design and Manufacturing Engineering (ICADME 2017)
PB  - Atlantis Press
SP  - 669
EP  - 675
SN  - 2352-5401
UR  - https://doi.org/10.2991/icadme-16.2016.119
DO  - 10.2991/icadme-16.2016.119
ID  - Liu2017/07
ER  -