Combination Algorithm for State of Charge Estimation

Author

Bo Zhang ; Changhua Lu ; Jinghan Liu

Author_Institution

Hefei Univ. of Technol., Hefei, China

fYear

2013

fDate

6-8 April 2013

Firstpage

865

Lastpage

867

Abstract

When using the Ah counting method to estimate state of charge of battery on electric vehicle, it is difficult to measure the initial SOC, and will bring accumulated errors. In order to solve the above problem, we design an algorithm which integrates the open circuit voltage method (OCV), Kalman filter (KF) and Ah counting method (Ah) in this paper. With the help of Matlab/Simulink platform, a test is designed to simulate the above algorithm, which shows the feasibility and accuracy of the algorithm were better than the Ah counting method alone.

Keywords

Kalman filters; battery powered vehicles; mathematics computing; secondary cells; Ah counting method; KF; Kalman filter; Matlab/Simulink platform; OCV; SOC; accumulated errors; battery charging; charge estimation; combination algorithm; electric vehicle; open circuit voltage method; Batteries; Battery charge measurement; Electric vehicles; Estimation; Kalman filters; Mathematical model; System-on-chip; Kalman filter (KF); Neural Network; Regression Analysis; Time Series; ampere hour (Ah)jStock Market Forecasting; electric vehicle (EV); open circuit voltage (OCV); state of charge (SOC);

fLanguage

English

Publisher

ieee

Conference_Titel

Communication Systems and Network Technologies (CSNT), 2013 International Conference on

Conference_Location

Gwalior

Print_ISBN

978-1-4673-5603-9

Type

conf

DOI

10.1109/CSNT.2013.186

Filename

6524529