With the widespread application of lithium batteries in electric vehicles and energy storage systems,battery-related safety and reliability issues have become increasingly prominent.Conventional monitoring methods oft...With the widespread application of lithium batteries in electric vehicles and energy storage systems,battery-related safety and reliability issues have become increasingly prominent.Conventional monitoring methods often struggle to address dynamic changes under complex operando.In recent years,flexible sensing technology has emerged as a promising solution for battery health monitoring due to its high adaptability and conformability to complex structures.Meanwhile,empowered by artificial intelligence(AI)for data analysis,the collected data enables efficient and accurate state assessment,offering robust support for accident prevention.Against this background,this paper first explores the integrated applications of flexible sensors in battery health monitoring and their unique advantages in addressing complex battery operating conditions,while analyzing the potential of AI in battery state analysis.Subsequently,it systematically reviews mainstream flexible sensing technologies(e.g.,film sensors,thermocouples,and optical fiber sensors),elucidating their mechanisms for revealing intricate internal battery processes during operation.Finally,the paper discusses AI’s role in enhancing monitoring efficiency and accuracy,and envisions future research directions and application prospects.This work aims to provide technical references for the battery health monitoring field as well as promote the application of flexible sensing technologies in improving battery system safety and reliability.展开更多
基金supported by the grant of State Key Laboratory of Space Environment Interaction with Matters,the Science and Technology on Vacuum Technology and Physics Laboratory Fund(HTKJ2023KL510008)Key Program of the National Natural Science Foundation of China(No.62433017)+6 种基金the National Natural Science Foundation of China(No.62274140)the Fundamental Research Funds for the Central Universities(20720230030)the Xiaomi Young Talents Program/Xiaomi Foundation,Shenzhen Science and Technology Program(JCYJ20230807091401003)the Young Elite Scientist Sponsorship Program by Cast(No.YESS20230523)the State Key Laboratory of Space Environment Interaction with Matters(WDZC-HGD-2022-08)the Gansu Provincial Science and Technology Major Project(2244ZZDD1133GGAA000077)the China Aerospace Science and Technology Group Corporation Young Top Talents.
文摘With the widespread application of lithium batteries in electric vehicles and energy storage systems,battery-related safety and reliability issues have become increasingly prominent.Conventional monitoring methods often struggle to address dynamic changes under complex operando.In recent years,flexible sensing technology has emerged as a promising solution for battery health monitoring due to its high adaptability and conformability to complex structures.Meanwhile,empowered by artificial intelligence(AI)for data analysis,the collected data enables efficient and accurate state assessment,offering robust support for accident prevention.Against this background,this paper first explores the integrated applications of flexible sensors in battery health monitoring and their unique advantages in addressing complex battery operating conditions,while analyzing the potential of AI in battery state analysis.Subsequently,it systematically reviews mainstream flexible sensing technologies(e.g.,film sensors,thermocouples,and optical fiber sensors),elucidating their mechanisms for revealing intricate internal battery processes during operation.Finally,the paper discusses AI’s role in enhancing monitoring efficiency and accuracy,and envisions future research directions and application prospects.This work aims to provide technical references for the battery health monitoring field as well as promote the application of flexible sensing technologies in improving battery system safety and reliability.
