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作 者:束登峰 汪志成[1] 王海洋 黄泽海 陈金明 SHU Dengfeng;WANG Zhicheng;WANG Haiyang;HUANG Zehai;CHEN Jinming(School of Mechanical and Electronic Engineering,East China University of Technology,Nanchang 330013)
机构地区:[1]东华理工大学机械与电子工程学院,南昌330013
出 处:《现代制造技术与装备》2024年第1期13-16,共4页Modern Manufacturing Technology and Equipment
基 金:2022年抚州市揭榜挂帅重点项目(H202300027);东华理工大学江西省新能源工艺与装备工程技术研究中心开放基金(JXNE2018-04)。
摘 要:提出一种基于高压放电声音识别快速评估电池健康状态的方法,目的在于以尽可能短的时间评估锂电池的健康状态(State of Health,SOH),以便电池的重组和梯次利用。研究主要从电子迁移能力方面建立电池高压放电与健康状态的联系,分析电池在高压静电场中发生放电的声谱图特征,并将其作为电池SOH快速评估的依据。同时,针对方壳型磷酸铁锂电池搭建了一套自动化检测装置,并进行装置的结构和控制系统设计,实现了在5 min内完成单体电池的检测,极大地提高了锂电池的检测效率。A method for rapid battery health assessment based on high-voltage discharge sound recognition was proposed to evaluate the State of Health(SOH)of lithium batteries in the shortest possible time for battery recombination and cascade utilization.The relationship between the high voltage discharge and the health state of the battery was established from the aspect of electron migration ability,and the acoustic characteristics of the battery discharge in the high voltage electrostatic field were analyzed,which was used as the basis for the rapid assessment of the battery SOH.At the same time,a set of automatic detection device was built for the square-shell lithium iron phosphate battery,and the structure and control system of the device were designed.It is estimated that the detection of the single battery will be completed within 5 min,which greatly improves the detection efficiency of the lithium battery.
分 类 号:TM912[电气工程—电力电子与电力传动]
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