State of Charge Estimation of Lithium-Ion Batteries in Electric Drive Vehicles Using Extended Kalman Filtering

Author

Zheng Chen ; Yuhong Fu ; Mi, Chunting Chris

Author_Institution

Dept. of Electr. & Comput. Eng., Univ. of Michigan-Dearborn, Dearborn, MI, USA

Volume

62

Issue

3

fYear

2013

fDate

41334

Firstpage

1020

Lastpage

1030

Abstract

In this paper, a more accurate battery state of charge (SOC) estimation method for electric drive vehicles is developed based on a nonlinear battery model and an extended Kalman filter (EKF) supported by experimental data. A nonlinear battery model is constructed by separating the model into a nonlinear open circuit voltage and a two-order resistance-capacitance model. EKF is used to eliminate the measurement and process noise and remove the need of prior knowledge of initial SOC. A hardware-in-the-loop test bench was built to validate the method. The experimental results show that the proposed method can estimate the battery SOC with high accuracy.

Keywords

Kalman filters; battery powered vehicles; lithium; nonlinear filters; secondary cells; EKF; Li; SOC estimation method; electric drive vehicles; extended Kalman filtering; hardwarein-the-loop test bench; initial SOC; lithium-ion batteries; nonlinear battery model; state of charge estimation; two-order resistance-capacitance model; Batteries; Battery charge measurement; Current measurement; Discharges (electric); Integrated circuit modeling; System-on-a-chip; Voltage measurement; Extended Kalman filter (EKF); hardware-in-the-loop; lithium-ion battery; nonlinear battery model; state of charge (SOC);

fLanguage

English

Journal_Title

Vehicular Technology, IEEE Transactions on

Publisher

ieee

ISSN

0018-9545

Type

jour

DOI

10.1109/TVT.2012.2235474

Filename

6389785