Accuracy state of charge estimation used in energy storage system for electric transportation

Author

Di Li ; Jian Ouyang ; Huiqi Li ; Jinhong Xie

Author_Institution

Sch. of Mech. & automotive Eng., South China Univ. of Technol., Guangzhou, China

fYear

2014

fDate

Aug. 31 2014-Sept. 3 2014

Firstpage

1

Lastpage

6

Abstract

Electric transportation is the development tendency of the transportation systems in future world. Energy storage systems are the key components of the electric transportation systems. Accuracy state of charge (SOC) estimation of energy storage system is crucial not only for improve energy used efficiency, but also for electric transportation drive safety. This paper choose LiFePO4 Li-ion battery as energy storage medium, use equivalent circuit modeling the battery, estimate the SOC of the battery through SMFEKF algorithm. The comparison between the SMFEKF algorithm simulation data and the experimental data shows that the SMFEKF algorithm has a better accuracy in SOC estimation.

Keywords

Kalman filters; electric vehicles; energy conservation; energy storage; equivalent circuits; estimation theory; iron compounds; lithium compounds; nonlinear filters; secondary cells; transportation; LiFePO₄; SMFEKF algorithm simulation data; SOC estimation; accuracy state of charge estimation; electric transportation drive safety system; electric vehicles; energy storage system; energy used efficiency improvement; equivalent circuit modeling; li-ion battery; suboptimal multiple fading factor extended Kalman filter; Batteries; Discharges (electric); Equations; Estimation; Integrated circuit modeling; Mathematical model; System-on-chip; Electric Transportation; Energy Storage System; State of Charge Estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Transportation Electrification Asia-Pacific (ITEC Asia-Pacific), 2014 IEEE Conference and Expo

Conference_Location

Beijing

Print_ISBN

978-1-4799-4240-4

Type

conf

DOI

10.1109/ITEC-AP.2014.6940736

Filename

6940736