@inproceedings{10c9948ba8c447a190003237bf54d895,
title = "Implementation of unscented kalman filter-based online state-of-charge estimation in lifepo4 battery-powered electric vehicle applications",
abstract = "This paper proposes an online state-of-charge (SoC) estimation method based on a 2nd-order RC model. The open circuit voltage (OCV) of the battery is calculated through two adaptive filtering stage, which is then used to determine the SoC via a dynamic OCV- SoC curve. In the first stage a variable step-size least mean square (VSS-LMS) algorithm is employed to adaptively estimate the model parameters in real-Time; in the second stage, an unscented Kalman filter (UKF) is used to estimate the OCV from the parameters. The proposed SoC estimation method with its simplified model was implemented in DSP system for real-Time application. Plenty of experiments under different conditions were carried out to confirm the effectiveness and superiority of the proposed system.",
author = "Boyan Huang and Chenxi Wang and Zheng Zhu and Yi Shen and Yegui Xiao",
year = "2016",
doi = "10.1149/07518.0003ecst",
language = "英语",
series = "ECS Transactions",
publisher = "Electrochemical Society Inc.",
number = "18",
pages = "3--11",
editor = "M. Doeff and M. Manivannan and R. Jow and V. Kalra and G. Liu",
booktitle = "Batteries and Energy Technology Joint General Session",
address = "美国",
edition = "18",
note = "Symposium on Batteries and Energy Technology Joint General Session - PRiME 2016/230th ECS Meeting ; Conference date: 02-10-2016 Through 07-10-2016",
}