Lithium-ion batteries(LIBs),as the first choice for green batteries,have been widely used in energy stor-age,electric vehicles,3C devices,and other related fields,and will have greater application prospects in the future.However,one of the obstacles hindering the future development of battery technology is how to accurately evaluate and monitor battery health,which affects the entire lifespan of battery use.It is not enough to assess battery health comprehensively through the state of health(SoH)alone,especially when nonlinear aging occurs in onboard applications.Here,for the first time,we propose a brand-new health evaluation indicator-state of nonlinear aging(SoNA)to explain the nonlinear aging phenomenon that occurs during the battery use,and also design a knee-point identification method and two SoNA quanti-tative methods.We apply our health evaluation indicator to build a complete LIB full-lifespan grading evaluation system and a ground-to-cloud service framework,which integrates multi-scenario data col-lection,multi-dimensional data-based grading evaluation,and cloud management functions.Our works fill the gap in the LIBs'health evaluation of nonlinear aging,which is of great significance for the health and safety evaluation of LIBs in the field of echelon utilization such as vehicles and energy storage.In addition,this comprehensive evaluation system and service framework are expected to be extended to other battery material systems other than LIBs,yet guiding the design of new energy ecosystem.

School of Automotive Studies,Tongji University,Shanghai 201804,China;National Fuel Cell Vehicle&Powertrain System Research&Engineering Center,Shanghai 201804,China;School of Transportation Science and Engineering,Beihang University,Beijing 100191,China;Institute for Advanced Study,Tongji University,Shanghai 200092,China;Shanghai AI NEV Innovative Platform Co.,Ltd.,Shanghai 201804,China;Electrochemical Energy Conversion and Storage Systems,Institute for Power Electronics and Electrical Drives(ISEA),RWTH Aachen University,Aachen 52062,Germany

[1]Heze You;Jiangong Zhu;Xueyuan Wang;Bo Jiang;Hao Sun;Xinhua Liu;Xuezhe Wei;Guangshuai Han;Shicong Ding;Hanqing Yu;Weihan Li;Dirk Uwe Sauer;Haifeng Dai-.Nonlinear health evaluation for lithium-ion battery within full-lifespan)[J].能源化学,2022(09):333-341

SoNA

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