@inproceedings{d81057c7e06d4fcf8e7e8a6c32a80c0d,
title = "The research on battery SOC estimation within first-order Markov process",
abstract = "State of Charge(SOC) of batteries is one of the most important and the most difficult estimated parameters in battery management Kalman filtering algorithm is widely applied to the battery SOC estimation, but the premise of the application of Kalman filter is that the system model is accurate and system noise is white noise. For the problem that current measurements of electric cars are easily influenced by colored noise interference under the complicated conditions, this thesis focuses on studying the affects which the algorithm based on Extended Kalman Filter (EKF) puts on the battery SOC estimation value, influencing by colored noise in First-order Markov process.",
keywords = "Battery model, Colored noise, Electric vehicles, Extended Kalman Filter (EKF), First-order Markov process, Lithium-ion battery, State of Charge (SOC)",
author = "Lianbo Du and Ximing Cheng and Li Yang",
note = "Publisher Copyright: {\textcopyright} 2015 Technical Committee on Control Theory, Chinese Association of Automation.; 34th Chinese Control Conference, CCC 2015 ; Conference date: 28-07-2015 Through 30-07-2015",
year = "2015",
month = sep,
day = "11",
doi = "10.1109/ChiCC.2015.7260887",
language = "English",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "7849--7854",
editor = "Qianchuan Zhao and Shirong Liu",
booktitle = "Proceedings of the 34th Chinese Control Conference, CCC 2015",
address = "United States",
}
