Transferable data-driven capacity estimation for lithium-ion batteries with deep learning: A case study from laboratory to field applications

Applied Energy - Tập 350 - Trang 121747 - 2023
Qiao Wang1,2,3,4, Min Ye1, Xue Cai5,2,3,4, Dirk Uwe Sauer2,3,4,6, Weihan Li2,3,4
1National Engineering Research Center for Highway Maintenance Equipment, Chang'an University, Xi'an, 710064, China
2Chair for Electrochemical Energy Conversion and Storage Systems, Institute for Power Electronics and Electrical Drives (ISEA), RWTH Aachen University, Aachen 52074, Germany
3Center for Ageing, Reliability and Lifetime Prediction of Electrochemical and Power Electronics Systems (CARL), RWTH Aachen University, Aachen 52074, Germany
4Jülich Aachen Research Alliance, JARA-Energy, Aachen, Germany
5National Active Distribution Network Technology Research Center, Beijing Jiaotong University, Beijing 100044, China
6Helholtz Institute Münster (HI MS), Forschungszentrum Jülich, Jülich, Germany

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Applied Energy

Tập 350

121747

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