DocumentCode :
2655612
Title :
A joint model and SOC estimation method for lithium battery based on the sigma point KF
Author :
He, Zhiwei ; Liu, Yuanyuan ; Gao, Mingyu ; Wang, Caisheng
Author_Institution :
Dept. of Electron. & Inf. Eng., Hangzhou Dianzi Univ., Hangzhou, China
fYear :
2012
fDate :
18-20 June 2012
Firstpage :
1
Lastpage :
5
Abstract :
Lithium-ion batteries have been widely used in electric vehicles (EV). The working state of the battery is very important to the safety of an EV. Online estimation of the state of charge (SOC) is essential in obtaining the battery working conditions. In order to achieve an accurate estimation of the SOC, the battery model should be adjustable when the battery is aged. A joint battery model and SOC estimation method based on the sigma point kalman filter (SPKF) is presented. A combined battery model is used to depict the relationship between the open circuit voltage (OCV) and the SOC of the battery. The main battery model parameter for estimation is the internal resistance and it is jointly estimated with the SOC online. Experimental results show that the SPKF based joint estimation method is effective.
Keywords :
Kalman filters; battery powered vehicles; lithium; secondary cells; EV; OCV; SOC estimation method; SPKF based joint estimation method; electric vehicles; joint battery model; lithium-ion battery; open circuit voltage; sigma point Kalman filter; state of charge estimation method; Batteries; Estimation; Joints; Kalman filters; Mathematical model; Resistance; System-on-a-chip; SOC; joint estimation; sigma point kalman filter;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Transportation Electrification Conference and Expo (ITEC), 2012 IEEE
Conference_Location :
Dearborn, MI
Print_ISBN :
978-1-4673-1407-7
Electronic_ISBN :
978-1-4673-1406-0
Type :
conf
DOI :
10.1109/ITEC.2012.6243505
Filename :
6243505
Link To Document :
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