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A Precise Life Estimation Method for Retired Energy Storage Batteries Based on Energy Storage Batteries Attenuation Characteristics and XGBoost Algorithm

Authors :
Xiaolin Chen
Junting Hua
Chong Yin
Zhang Chen
Yangming Chen
Zhonghao Li
Source :
IEEE Access, Vol 11, Pp 135968-135978 (2023)
Publication Year :
2023
Publisher :
IEEE, 2023.

Abstract

With the increasing scale of energy storage batteries, the number of retired energy storage batteries is also rapidly increasing, and the energy storage life, as an important indicator for evaluating the safety of retired energy storage, has received widespread attention. The existing methods for estimating the life of retired energy storage have the problem of considering attenuation characteristics (AC) that do not fully reflect the actual operating characteristics of batteries, which can affect the estimation accuracy. Therefore, this article proposes a precise estimation method for the life of retired energy storage batteries to improve the accuracy of estimating the life of retired energy storage. Firstly, an AC extraction method was proposed to fully explore the potential relationship between various feature data and the operational status of retired energy storage. Then, a method was proposed to screen and optimize ACs that are highly correlated with the life of retired energy storage batteries, selecting ACs that are highly correlated with the life of retired energy storage batteries. Finally, an accurate method for estimating the life of retired energy storage batteries was proposed, which effectively improved the accuracy of estimating the life. The proposed method was validated on the NASA dataset with an accuracy of no less than 99.784% for estimating life.

Details

Language :
English
ISSN :
21693536
Volume :
11
Database :
Directory of Open Access Journals
Journal :
IEEE Access
Publication Type :
Academic Journal
Accession number :
edsdoj.1d90af4adb284d72a88ee4ab58ed512f
Document Type :
article
Full Text :
https://doi.org/10.1109/ACCESS.2023.3336813