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Title: On state-of-charge determination for lithium-ion batteries

Abstract

The estimation of state-of-charge (SOC) of a battery is a challenging topic in battery research. Although improved precisions have been reported at times, almost all are based on empirical approaches. Without sufficient fundamental understanding, the accuracy and precision of any SOC estimation remain questionable and to assess if a SOC estimation method were properly constructed remains difficult. Here, we review a range of topics including SOC definitions, methodologies of SOC estimation, calibration, regression (including modeling methods), and validation in terms of precision and accuracy. At the end, we intend to answer fundamental questions, such as: 1) can SOC estimation be self-adaptive without bias? 2) Why Ah-counting is a necessity in most battery-model-assisted regression methods? 3) How to determine the principle of multi-physical coupling in battery models? 4) To assess the accuracy in the SOC estimation, statistical methods should be employed to analyze factors that contribute to the uncertainty. By answering these questions, we shall reveal how fundamental principles work to aid the understanding of proper SOC estimation.

Authors:
 [1]; ORCiD logo [1]; ORCiD logo [2];  [3]
  1. Tsinghua Univ., Beijing (China). State Key Lab. of Automotive Safety and Energy, Dept. of Automotive Engineering
  2. Idaho National Lab. (INL), Idaho Falls, ID (United States). Energy Storage and Advanced Vehicles
  3. Tsinghua Univ., Beijing (China). State Key Lab. of Automotive Safety and Energy, Dept. of Automotive Engineering; Beijing Inst. of Technology, Beijing (China). Beijing Co-innovation Center for Electric Vehicles
Publication Date:
Research Org.:
Idaho National Laboratory (INL), Idaho Falls, ID (United States)
Sponsoring Org.:
USDOE Office of Nuclear Energy (NE)
OSTI Identifier:
1470981
Alternate Identifier(s):
OSTI ID: 1416199; OSTI ID: 1484715
Report Number(s):
INL/JOU-17-40852-Rev001; INL/JOU-17-40852-Rev000
Journal ID: ISSN 0378-7753
Grant/Contract Number:  
AC07-05ID14517
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Journal of Power Sources
Additional Journal Information:
Journal Volume: 348; Journal Issue: C; Journal ID: ISSN 0378-7753
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
25 ENERGY STORAGE; State of charge; Lithium ion batteries; Accuracy; determination methodology

Citation Formats

Li, Zhe, Huang, Jun, Liaw, Bor Yann, and Zhang, Jianbo. On state-of-charge determination for lithium-ion batteries. United States: N. p., 2017. Web. doi:10.1016/j.jpowsour.2017.03.001.
Li, Zhe, Huang, Jun, Liaw, Bor Yann, & Zhang, Jianbo. On state-of-charge determination for lithium-ion batteries. United States. https://doi.org/10.1016/j.jpowsour.2017.03.001
Li, Zhe, Huang, Jun, Liaw, Bor Yann, and Zhang, Jianbo. 2017. "On state-of-charge determination for lithium-ion batteries". United States. https://doi.org/10.1016/j.jpowsour.2017.03.001. https://www.osti.gov/servlets/purl/1470981.
@article{osti_1470981,
title = {On state-of-charge determination for lithium-ion batteries},
author = {Li, Zhe and Huang, Jun and Liaw, Bor Yann and Zhang, Jianbo},
abstractNote = {The estimation of state-of-charge (SOC) of a battery is a challenging topic in battery research. Although improved precisions have been reported at times, almost all are based on empirical approaches. Without sufficient fundamental understanding, the accuracy and precision of any SOC estimation remain questionable and to assess if a SOC estimation method were properly constructed remains difficult. Here, we review a range of topics including SOC definitions, methodologies of SOC estimation, calibration, regression (including modeling methods), and validation in terms of precision and accuracy. At the end, we intend to answer fundamental questions, such as: 1) can SOC estimation be self-adaptive without bias? 2) Why Ah-counting is a necessity in most battery-model-assisted regression methods? 3) How to determine the principle of multi-physical coupling in battery models? 4) To assess the accuracy in the SOC estimation, statistical methods should be employed to analyze factors that contribute to the uncertainty. By answering these questions, we shall reveal how fundamental principles work to aid the understanding of proper SOC estimation.},
doi = {10.1016/j.jpowsour.2017.03.001},
url = {https://www.osti.gov/biblio/1470981}, journal = {Journal of Power Sources},
issn = {0378-7753},
number = C,
volume = 348,
place = {United States},
year = {Thu Mar 09 00:00:00 EST 2017},
month = {Thu Mar 09 00:00:00 EST 2017}
}

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Cited by: 176 works
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Works referencing / citing this record:

An Improved Model-Based Self-Adaptive Filter for Online State-of-Charge Estimation of Li-Ion Batteries
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