DocumentCode
2928379
Title
Research on SOC Hybrid Estimation Algorithm of Power Battery Based on EKF
Author
Wu, Tiezhou ; Chen, Xueguang ; Xia, Fangzhen ; Xiang, Jianfeng
Author_Institution
Dept. of Control Sci. & Eng., Huazhong Univ. of Sci. & Technol., Wuhan, China
fYear
2011
fDate
25-28 March 2011
Firstpage
1
Lastpage
3
Abstract
Accurate estimation of power battery SOC (state of charge) is the basis of HE V power control strategy. SOC estimation algorithm has a significant impact on the accuracy of SOC estimation. This paper described the basic concept of SOC, discussed the significance of SOC estimation algorithm, difficulties and the main factors affecting SOC estimation, proposed a hybrid battery SOC estimation method with combination of extended Kalman filtering algorithm and improved Ampere Hour (AH) Method based on analyzing existed algorithms. Experimental results show that the hybrid SOC estimation method can meet the accuracy requirement of HEV SOC estimation excellently and is superior to the individual EKF method.
Keywords
Kalman filters; battery chargers; secondary cells; EKF; SOC hybrid estimation algorithm; ampere hour method; extended Kalman filtering algorithm; power battery; power control strategy; state of charge; Batteries; Battery charge measurement; Equations; Estimation; Kalman filters; Mathematical model; System-on-a-chip;
fLanguage
English
Publisher
ieee
Conference_Titel
Power and Energy Engineering Conference (APPEEC), 2011 Asia-Pacific
Conference_Location
Wuhan
ISSN
2157-4839
Print_ISBN
978-1-4244-6253-7
Type
conf
DOI
10.1109/APPEEC.2011.5748464
Filename
5748464
Link To Document