Model-based method for estimating LiCoO2 battery state of health and behaviors

Junfu Li; Chao Lyu; Lixin Wang; Tengfei Ge

doi:10.1109/ICPHM.2016.7542819

Model-based method for estimating LiCoO₂ battery state of health and behaviors

Junfu Li
, Chao Lyu^*
, Lixin Wang
, Tengfei Ge

^*Corresponding author for this work

School of Electrical Engineering and Automation, Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

Simplified mechanistic models can accurately simulate battery behaviors and are more suitable for studies on mechanistic parameters. Battery remaining useful life can be predicted by analyzing the variations of parameters at different aging stages. The main work of this paper is listed below: (i) Parameters of mechanistic model at different stages are analyzed according to their variation laws, (ii) Based on the variations of these selected parameters, battery discharge behaviors are predicted. The simulated results show good agreement with measurements.

Original language	English
Title of host publication	2016 IEEE International Conference on Prognostics and Health Management, ICPHM 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509003822
DOIs	https://doi.org/10.1109/ICPHM.2016.7542819
State	Published - 12 Aug 2016
Externally published	Yes
Event	2016 IEEE International Conference on Prognostics and Health Management, ICPHM 2016 - Ottawa, Canada Duration: 20 Jun 2016 → 22 Jun 2016

Publication series

Name	2016 IEEE International Conference on Prognostics and Health Management, ICPHM 2016

Conference

Conference	2016 IEEE International Conference on Prognostics and Health Management, ICPHM 2016
Country/Territory	Canada
City	Ottawa
Period	20/06/16 → 22/06/16

Keywords

battery discharge behaviors
battery remaining useful life
parameters of mechanistic model
simplified mechanistic model

Access to Document

10.1109/ICPHM.2016.7542819

Cite this

Li, J., Lyu, C., Wang, L., & Ge, T. (2016). Model-based method for estimating LiCoO₂ battery state of health and behaviors. In 2016 IEEE International Conference on Prognostics and Health Management, ICPHM 2016 Article 7542819 (2016 IEEE International Conference on Prognostics and Health Management, ICPHM 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICPHM.2016.7542819

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title = "Model-based method for estimating LiCoO2 battery state of health and behaviors",

abstract = "Simplified mechanistic models can accurately simulate battery behaviors and are more suitable for studies on mechanistic parameters. Battery remaining useful life can be predicted by analyzing the variations of parameters at different aging stages. The main work of this paper is listed below: (i) Parameters of mechanistic model at different stages are analyzed according to their variation laws, (ii) Based on the variations of these selected parameters, battery discharge behaviors are predicted. The simulated results show good agreement with measurements.",

keywords = "battery discharge behaviors, battery remaining useful life, parameters of mechanistic model, simplified mechanistic model",

author = "Junfu Li and Chao Lyu and Lixin Wang and Tengfei Ge",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE International Conference on Prognostics and Health Management, ICPHM 2016 ; Conference date: 20-06-2016 Through 22-06-2016",

year = "2016",

month = aug,

day = "12",

doi = "10.1109/ICPHM.2016.7542819",

language = "英语",

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Li, J, Lyu, C, Wang, L & Ge, T 2016, Model-based method for estimating LiCoO₂ battery state of health and behaviors. in 2016 IEEE International Conference on Prognostics and Health Management, ICPHM 2016., 7542819, 2016 IEEE International Conference on Prognostics and Health Management, ICPHM 2016, Institute of Electrical and Electronics Engineers Inc., 2016 IEEE International Conference on Prognostics and Health Management, ICPHM 2016, Ottawa, Canada, 20/06/16. https://doi.org/10.1109/ICPHM.2016.7542819

Model-based method for estimating LiCoO₂ battery state of health and behaviors. / Li, Junfu; Lyu, Chao; Wang, Lixin et al.
2016 IEEE International Conference on Prognostics and Health Management, ICPHM 2016. Institute of Electrical and Electronics Engineers Inc., 2016. 7542819 (2016 IEEE International Conference on Prognostics and Health Management, ICPHM 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - Simplified mechanistic models can accurately simulate battery behaviors and are more suitable for studies on mechanistic parameters. Battery remaining useful life can be predicted by analyzing the variations of parameters at different aging stages. The main work of this paper is listed below: (i) Parameters of mechanistic model at different stages are analyzed according to their variation laws, (ii) Based on the variations of these selected parameters, battery discharge behaviors are predicted. The simulated results show good agreement with measurements.

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Li J, Lyu C, Wang L, Ge T. Model-based method for estimating LiCoO₂ battery state of health and behaviors. In 2016 IEEE International Conference on Prognostics and Health Management, ICPHM 2016. Institute of Electrical and Electronics Engineers Inc. 2016. 7542819. (2016 IEEE International Conference on Prognostics and Health Management, ICPHM 2016). doi: 10.1109/ICPHM.2016.7542819