SOC Estimation of Lead-Acid Batteries Based on UKF

Author

Piao, Changhao ; Sun, Zhihua ; Liang, Zhanghou ; Cho, Chongdu

Author_Institution

Minist. of Educ. Key Lab. of Network Control Tech. & Intell. Instrum., Chongqing Univ. of Posts & Commun., Chongqing, China

fYear

2010

fDate

25-27 June 2010

Firstpage

1968

Lastpage

1972

Abstract

A novel self-adaptive state of charge (SOC) estimation model of lead-acid batteries based on Unscented Kalman Filter (UKF) algorithm is presented in here. The model state and measurement equations are constituted by the Ah counting method and load voltage method. In order to ensure the estimation accuracy, we establish a new function model for the Variable Rated Capacity of lead-acid batteries, and so the Ah counting method has been improved. On this basis, the SOC Algorithm is compared in three experimental conditions (including constant-current, constant-voltage and pulse-charge/discharge). The results show that this algorithm can effectively estimate SOC.

Keywords

Kalman filters; lead acid batteries; power filters; Ah counting method; constant current; constant voltage; lead-acid batteries; load voltage method; measurement equations; model state; pulse charge-discharge; self-adaptive state of charge estimation model; unscented Kalman filter algorithm; variable rated capacity; Batteries; Discharges; Equations; Estimation; Lead; Mathematical model; System-on-a-chip; Lead-Acid Battery; SOC; UKF; Variable Rated Capacity;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical and Control Engineering (ICECE), 2010 International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-6880-5

Type

conf

DOI

10.1109/iCECE.2010.484

Filename

5630725