Knowledge-Guided Data-Driven Model With Transfer Concept for Battery Calendar Ageing Trajectory Prediction

作     者：Kailong Liu Qiao Peng Remus Teodorescu Aoife M.Foley Kailong Liu;Qiao Peng;Remus Teodorescu;Aoife M.Foley

作者机构：IEEE the Warwick Manufacturing GroupUniversity of WarwickCoventry CV47ALUK the School of Control Science and EngineeringShandong UniversityChina the Queen’s University BelfastBelfast BT71NNUK the Department of Energy TechnologyAalborg UniversityAalborg 9220Denmark 

出 版 物：《IEEE/CAA Journal of Automatica Sinica》 (自动化学报（英文版）)

年 卷 期：2023年第10卷第1期

页      面：272-274页

核心收录：

学科分类：08[工学] 0835[工学-软件工程] 0802[工学-机械工程] 080201[工学-机械制造及其自动化] 

主　　题：battery Battery Calendar 

摘      要：Dear Editor, Lithium-ion(Li-ion) battery has become a promising source to supply and absorb energy/power for many energy-transportation applications. However, Li-ion battery capacity would inevitably degrade over time, making its related ageing prediction necessary.