DocumentCode
575400
Title
State of charge estimation of HEV/EV battery with Series Kalman Filter
Author
Baba, Atsushi ; Adachi, Shuichi
Author_Institution
Dept. of Appl. Phys. & Physico-Inf., Keio Univ., Yokohama, Japan
fYear
2012
fDate
20-23 Aug. 2012
Firstpage
845
Lastpage
850
Abstract
This paper proposes a method of accurately estimating the state of charge (SOC) of lithium-ion rechargeable batteries in high fuel efficiency vehicles, such as hybrid electric vehicles (HEVs) and electric vehicles (EVs). Although it is important to accurately estimate SOC of the battery to maximize efficiency and safety, there exist many problems for conventional methods. To address this issue, a model-based approach using “Series Kalman Filters” is proposed and implemented in this paper. Its approach is verified with series of simulations under the basic HEV operating environment. A discussion on a limitation of the method is also included in this paper. The ultimate goal is to design a state estimator capable of providing accurate state estimation of batteries under any possible user conditions.
Keywords
Kalman filters; battery powered vehicles; hybrid electric vehicles; secondary cells; HEV/EV battery; Li; SOC; high fuel efficiency vehicles; hybrid electric vehicles; lithium-ion rechargeable batteries; model-based approach; series Kalman filter; state estimator; state of charge estimation; ultimate goal; Batteries; Estimation; Hybrid electric vehicles; Integrated circuit modeling; Kalman filters; System-on-a-chip; Voltage measurement; Electric vehicle (EV); Hybrid electric vehicle (HEV); Kalman filter; Parameter estimation; Rechargeable Battery; State of Charge (SOC);
fLanguage
English
Publisher
ieee
Conference_Titel
SICE Annual Conference (SICE), 2012 Proceedings of
Conference_Location
Akita
ISSN
pending
Print_ISBN
978-1-4673-2259-1
Type
conf
Filename
6318559
Link To Document