DocumentCode :
3720494
Title :
A novel lithium-ion battery model for state of charge estimation under dynamic currents
Author :
Ji Wu;Chenbin Zhang;Zonghai Chen
Author_Institution :
Department of Automation, University of Science and Technology of China, Hefei, China
fYear :
2015
Firstpage :
1
Lastpage :
6
Abstract :
An accurate battery model is one of the most important factors to improve the capability of battery state of charge (SoC) estimation. In this paper, battery hysteresis behaviors under different SoC are considered to decrease battery model error, and the hysteresis voltage based battery model (HVBBM) is presented. The experiment result shows that this model can describe the battery discharging process accurately under dynamic current conditions. A method of the adaptive extended Kalman filter (AEKF) based on HVBBM is applied to estimate battery SoC since AEKF can update the process and measurement noise covariances adaptively during the estimation. The comparison results indicate that the method proposed in this paper can improve SoC estimation accuracy under dynamic currents.
Keywords :
"Batteries","Hysteresis","Mathematical model","Estimation","Adaptation models","Integrated circuit modeling","Kalman filters"
Publisher :
ieee
Conference_Titel :
Electric Power and Energy Conversion Systems (EPECS), 2015 4th International Conference on
Type :
conf
DOI :
10.1109/EPECS.2015.7368513
Filename :
7368513
Link To Document :
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