A novel method for state-of-charge estimation for battery with kalman filtering algorithm
Release Time:2019-03-11 Hits:
Indexed by: Journal Article
Date of Publication: 2015-08-01
Journal: ICIC Express Letters
Included Journals: Scopus、EI
Volume: 9
Issue: 9
Page Number: 2409-2414
ISSN: 1881803X
Abstract: With the increasing popularity of battery, the state-of-charge (SOC) estimation has attracted increasingly attention for reliability and safety of battery operation. In this paper, the online least square method is employed to calculate the corresponding parameters of the lithium battery model. Furthermore, the Unscented Kalman Filtering (UKF) Algorithm is adopted to carry out the SOC estimation. The experiment results demonstrate that UKF can conduct the SOC estimation with good tracking performance and small steady error. The UKF error is no more than 0.25%. ? ICIC International 2015.