DocumentCode
3589781
Title
The Lithium-ion battery capacity prediction error analysis based on extended Kalman filtering
Author
Zhenwei Zhou ; Yun Huang ; Yudong Lu ; Zhengyu Shi ; Liangbiao Zhu ; Jiliang Wu ; Hui Li
Author_Institution
China Electron. Product Reliability & Environ. Testing Res. Inst., Guangzhou, China
fYear
2014
Firstpage
252
Lastpage
256
Abstract
The Lithium-ion battery capacity prediction error is analyzed by use of extended Kalman filtering(EKF) and curve fitting algorithms. This paper employs the capacity degradation model described by Colum efficient factor, rest time and other two unknown parameters. Then, a nonlinear state-space model is introduced, and the EKF is presented to estimate the capacity and the two unknown parameters. The parameter setting in EKF is discussed in details. The capacity prediction error is analyzed with the help of curve fitting. The experiment example demonstrates the algorithms efficiency.
Keywords
Kalman filters; curve fitting; error analysis; nonlinear filters; secondary cells; Colum efficient factor; Li; capacity degradation model; capacity prediction error; curve fitting algorithms; extended Kalman filtering; lithium-ion battery capacity prediction error analysis; nonlinear state-space model; Algorithm design and analysis; Batteries; Degradation; Estimation; Fitting; Prediction algorithms; Predictive models; Lithiun-ion battery; capacity; curve fitting; extended Kalman filtering; prediction erro;
fLanguage
English
Publisher
ieee
Conference_Titel
Reliability, Maintainability and Safety (ICRMS), 2014 International Conference on
Print_ISBN
978-1-4799-6631-8
Type
conf
DOI
10.1109/ICRMS.2014.7107181
Filename
7107181
Link To Document