DocumentCode :
3413791
Title :
An adaptive algorithm of NiMH battery state of charge estimation for hybrid electric vehicle
Author :
Qiang, JiaXi ; Ao, Guoqiang ; He, Jianhui ; Chen, Ziqiang ; Yang, Lin
Author_Institution :
Sch. of Mech. Eng., Shanghai Jiaotong Univ., Shanghai
fYear :
2008
fDate :
June 30 2008-July 2 2008
Firstpage :
1556
Lastpage :
1561
Abstract :
An adaptive algorithm for battery state of charge (SOC) estimation is presented in this paper to solve the critical issue of calculating the remaining energy of battery in hybrid electric vehicle (HEV). To obtain a more accurate SOC estimation value, both coulomb-accumulation and open-circuit voltage contributions are considered in this study. The extended Kalman filter (EKF) theory which has good adaptability is used respectively in these two contributions. The adaptive control effectiveness is achieved in two aspects: one is the application of Kalman filter which can filter the noise of voltage and current measurement and the other is the open-circuit voltage correction when the battery is in steady state to compensate the deficiencies of coulomb-accumulation. The test results show this adaptive algorithm has high robust property, noise-immune ability and accuracy which is suitable for HEV application.
Keywords :
Kalman filters; hybrid electric vehicles; nickel; nonlinear filters; secondary cells; system-on-chip; HEV; Ni; adaptive control; coulomb-accumulation; extended Kalman filter; hybrid electric vehicle; noise-immune ability; open-circuit voltage; open-circuit voltage correction; state of charge estimation; voltage-current measurement; Adaptive algorithm; Adaptive control; Adaptive filters; Batteries; Current measurement; Hybrid electric vehicles; State estimation; Steady-state; Testing; Voltage;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics, 2008. ISIE 2008. IEEE International Symposium on
Conference_Location :
Cambridge
Print_ISBN :
978-1-4244-1665-3
Electronic_ISBN :
978-1-4244-1666-0
Type :
conf
DOI :
10.1109/ISIE.2008.4677229
Filename :
4677229
Link To Document :
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