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发布时间：2019-03-11

论文类型：期刊论文

发表时间：2015-08-01

发表刊物：ICIC Express Letters

收录刊物：Scopus、EI

卷号：9

期号：9

页面范围：2409-2414

ISSN号：1881803X

摘要：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.