@inproceedings{178d6cbc9822416e875cc87442060532,
title = "State of charge estimation of lithium-ion batteries considering model bias and parameter uncertainties",
abstract = "Up to date, model and parameter uncertainties are generally overlooked by majority of researchers in the field of battery study. As a consequence, accuracy of the SOC estimation is dominated by the model fidelity and may vary from cell-to-cell. This paper proposes a systematic framework with associated methodologies to quantify the battery model and parameter uncertainties for more effective battery SOC estimation. Such a framework is also generally applicable for estimating other battery performances of interest (e.g. capacity and power capability). There are two major benefits using the proposed framework: i) consideration of the cell-to-cell variability, and ii) accuracy improvement of the low fidelity model comparable to the high fidelity without scarifying computational efficiency. One case study is used to demonstrate the effectiveness of the proposed framework.",
keywords = "Lithium-ion battery, Model uncertainty, Parameter uncertainty, State of charge",
author = "Zhimin Xi and Rong Jing and Xiaoguang Yang and Ed Decker",
note = "Publisher Copyright: Copyright {\textcopyright} 2014 by ASME.; ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2014 ; Conference date: 17-08-2014 Through 20-08-2014",
year = "2014",
doi = "10.1115/DETC201435010",
language = "English (US)",
series = "Proceedings of the ASME Design Engineering Technical Conference",
publisher = "American Society of Mechanical Engineers (ASME)",
booktitle = "34th Computers and Information in Engineering Conference",
}