Machine learning for battery quality classification and lifetime prediction using formation data

被引：0
|
作者：
Zou, Jiayu [1 ,2 ,5 ]
Gao, Yingbo [3 ]
Frieges, Moritz H. [4 ]
Börner, Martin F. [1 ,2 ,5 ]
Kampker, Achim [4 ]
Li, Weihan [1 ,2 ,5 ]
机构：
[1] Chair for Electrochemical Energy Conversion and Storage Systems, Institute for Power Electronics and Electrical Drives (ISEA), RWTH Aachen University, Campus-Boulevard 89, Aachen,52074, Germany
[2] Center for Ageing, Reliability and Lifetime Prediction of Electrochemical and Power Electronic Systems (CARL), RWTH Aachen University, Campus-Boulevard 89, Aachen, Germany
[3] Department of Computer Science, RWTH Aachen University, Aachen,52056, Germany
[4] Chair of Production Engineering of E-Mobility Components (PEM), RWTH Aachen University, Bohr 12, Aachen,52072, Germany
[5] Juelich Aachen Research Alliance, JARA-Energy, Germany
来源：
Energy and AI | 2024年 / 18卷
关键词：
All Open Access; Gold;
D O I：
10.1016/j.egyai.2024.100451
中图分类号：
学科分类号：
摘要：
Prediction models
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