期刊
ENERGY
卷 74, 期 -, 页码 795-803出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2014.07.051
关键词
Unscented particle filter; State of charge; Kalman filter; Electrical battery model; Normalized least mean square
Accurate prediction of cell SOC (state of charge) is important for the safety and functional capabilities of the battery energy storage application system. This paper presents a hybrid UPF (unscented particle filter) based SOC determination combined model for batteries. To simulate the entire dynamic electrical characteristics of batteries, a novel combined state space model, which takes current as a control input and let SOC and two constructed parameters as state variables, is advanced to represent cell behavior. Besides that, an improved UPF method is used to evaluate cell SOC. Taking lead-acid batteries for example, we apply the established model for test. Results show that the evolved combined state space cell model simulates battery dynamics robustly with high accuracy and the prediction value based on the improved UPF method converges to the real SOC very quickly within the error of +/- 2%. (C) 2014 Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据