DocumentCode :
2097383
Title :
Research on Improved EKF Algorithm Applied on Estimate EV Battery SOC
Author :
Wang, Liye ; Wang, Lifang ; Liao, Chenglin
Author_Institution :
Inst. of Electr. Eng., Chinese Acad. of Sci., Beijing, China
fYear :
2010
fDate :
28-31 March 2010
Firstpage :
1
Lastpage :
4
Abstract :
The paper mainly described how to estimate the state of battery charge (SOC) on electric vehicle (EV). Having deeply researched the lithium-ion (LiFePO4) battery characteristic, the paper established a kind of new battery equivalent circuit model. Meanwhile the paper improved the traditional EKF SOC estimate algorithm, including add the battery internal resistance as a new state variable, real time adjust the observation error variance Rk and add the gain factor to control the convergence speed. Through simulating analysis, the new method estimated error of SOC is less than traditional estimate method.
Keywords :
Kalman filters; battery powered vehicles; equivalent circuits; secondary cells; EKF algorithm; EV battery; SOC; battery equivalent circuit model; electric vehicle; lithium-ion battery; state of battery charge; Analytical models; Batteries; Circuit simulation; Convergence; Electric vehicles; Equivalent circuits; Error correction; Monitoring; State estimation; Voltage;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Engineering Conference (APPEEC), 2010 Asia-Pacific
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-4812-8
Electronic_ISBN :
978-1-4244-4813-5
Type :
conf
DOI :
10.1109/APPEEC.2010.5448581
Filename :
5448581
Link To Document :
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