Improved SOC Estimation Algorithm Based on Temperature Correction

DOI

10.2991/icmse-18.2018.92How to use a DOI?

Keywords

Extended Kalman Filter, Least squares method, Temperature correction, State of charge

Abstract

In order to solve the problem of low accuracy of SOC estimation under complex operating environment, an improved SOC estimation algorithm based on temperature correction is proposed. First of all, considering the influence of temperature on the parameters of the battery model, the parameters of the model at different temperatures are obtained by the least square method, and the accuracy of the model parameters is verified. Secondly, under the FUDS conditions, the accurate estimation of SOC is realized by extended Kalman filter. Finally, the effect of temperature correction on SOC estimation accuracy is analyzed. The results show that the improved SOC estimation algorithm based on temperature correction improves the SOC estimation accuracy and robustness.

Copyright

© 2018, 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  - Libiao Jiang
AU  - Jie Yang
AU  - Qilong Tai
PY  - 2018/05
DA  - 2018/05
TI  - Improved SOC Estimation Algorithm Based on Temperature Correction
BT  - Proceedings of the 2018 8th International Conference on Manufacturing Science and Engineering (ICMSE 2018)
PB  - Atlantis Press
SP  - 488
EP  - 495
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmse-18.2018.92
DO  - 10.2991/icmse-18.2018.92
ID  - Jiang2018/05
ER  -