Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications

SOC estimation for Power Lithium-ion Battery Based on AUKF

Authors
Enguang Hou, Xin Qiao, Guangmin Liu
Corresponding Author
Enguang Hou
Available Online November 2016.
DOI
https://doi.org/10.2991/aiea-16.2016.3How to use a DOI?
Keywords
Power lithium-ion battery; Adaptive unscented Kalman filter; SOC; Unscented transform.
Abstract

In order to improve vehicle performance and safety, need to accurately estimate the power lithium battery state of charge (SOC), in allusion to nonlinear characteristic of power lithium-ion battery, presented a method estimation of power lithium-ion battery SOC based on AUKF. Introduced the principle of adaptive estimation based on UKF, and estimated the varying noise statistics, in order to improve the stability of the filter and reduce the estimation error. Simulation results show that the method can convergence even in the case of the initial value is unknown.

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/).

Download article (PDF)

Volume Title
Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications
Series
Advances in Computer Science Research
Publication Date
November 2016
ISBN
978-94-6252-270-1
ISSN
2352-538X
DOI
https://doi.org/10.2991/aiea-16.2016.3How to use a DOI?
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/).

Cite this article

TY  - CONF
AU  - Enguang Hou
AU  - Xin Qiao
AU  - Guangmin Liu
PY  - 2016/11
DA  - 2016/11
TI  - SOC estimation for Power Lithium-ion Battery Based on AUKF
BT  - Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications
PB  - Atlantis Press
SP  - 14
EP  - 18
SN  - 2352-538X
UR  - https://doi.org/10.2991/aiea-16.2016.3
DO  - https://doi.org/10.2991/aiea-16.2016.3
ID  - Hou2016/11
ER  -