DocumentCode :
587396
Title :
State of charge estimation of lithium-ion battery using Kalman filters
Author :
Baba, Akiya ; Adachi, Shuichi
Author_Institution :
Dept. of Appl. Phys. & Physico-Inf., Keio Univ., Yokohama, Japan
fYear :
2012
fDate :
3-5 Oct. 2012
Firstpage :
409
Lastpage :
414
Abstract :
In this paper we propose an accurate state of charge (SOC) estimation method for a lithium-ion battery for hybrid electric vehicle (HEV) and electric vehicles (EV) use. Although it is important to accurately determine the SOC of a battery to achieve maximum efficiency and safety, none of the existing methods has achieved this perfectly. To address this issue, a model-based approach using a cascaded combination of two Kalman filters, “Series Kalman Filters,” is proposed and implemented. Its validity is verified by performing a series of simulations under a basic HEV operating environment.
Keywords :
Kalman filters; hybrid electric vehicles; secondary cells; hybrid electric vehicle; lithium-ion battery; series Kalman filters; state of charge estimation; Accuracy; Batteries; Estimation; Hybrid electric vehicles; Kalman filters; System-on-a-chip; Voltage measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Applications (CCA), 2012 IEEE International Conference on
Conference_Location :
Dubrovnik
ISSN :
1085-1992
Print_ISBN :
978-1-4673-4503-3
Electronic_ISBN :
1085-1992
Type :
conf
DOI :
10.1109/CCA.2012.6402456
Filename :
6402456
Link To Document :
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