Multi-level intelligence empowering lithium-ion batteries

被引:6
|
作者
Zhang, Guangxu [1 ,2 ]
Zhu, Jiangong [2 ]
Dai, Haifeng [2 ]
Wei, Xuezhe [2 ]
机构
[1] Tongji Univ, Sch Mat Sci & Engn, Shanghai 201804, Peoples R China
[2] Tongji Univ, Sch Automot Studies, Shanghai 201804, Peoples R China
来源
关键词
Battery intelligence; Intelligent response; Intelligent sensing; Intelligent management; REDOX SHUTTLE ADDITIVES; OVERCHARGE PROTECTION; IN-SITU; ELECTROCHEMICAL PERFORMANCE; POLYETHYLENE SEPARATORS; ELECTROLYTE ADDITIVES; NEGATIVE ELECTRODES; ACOUSTIC-EMISSION; POLYMERIC BINDERS; FLAME-RETARDANTS;
D O I
10.1016/j.jechem.2024.06.020
中图分类号
O69 [应用化学];
学科分类号
081704 ;
摘要
With the significant and widespread application of lithium -ion batteries, there is a growing demand for improved performances of lithium -ion batteries. The intricate degradation throughout the whole lifecycle profoundly impacts the safety, durability, and reliability of lithium -ion batteries. To ensure the long-term, safe, and efficient operation of lithium -ion batteries in various fields, there is a pressing need for enhanced battery intelligence that can withstand extreme events. This work reviews the current status of intelligent battery technology from three perspectives: intelligent response, intelligent sensing, and intelligent management. The intelligent response of battery materials forms the foundation for battery stability, the intelligent sensing of multi -dimensional signals is essential for battery management, and the intelligent management ensures the long-term stable operation of lithium -ion batteries. The critical challenges encountered in the development of intelligent battery technology from each perspective are thoroughly analyzed, and potential solutions are proposed, aiming to facilitate the rapid development of intelligent battery technologies. CO 2024 Science Press and Dalian Institute of Chemical Physics, Chinese Academy of Sciences. Published by ELSEVIER B.V. and Science Press. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
引用
收藏
页码:535 / 552
页数:18
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