电池容量
可靠性工程
健康状况
计算机科学
电池(电)
容量损失
共因失效
共同事业与特殊事业
工程类
运营管理
物理
量子力学
功率(物理)
作者
Samarth Agarwal,Subramanian Swernath Brahmadathan,Krishnan S. Hariharan,Sangmin Han,Anshul Kaushik,Rajkumar S. Patil,Subramanya Mayya Kolake,Bookeun Oh
出处
期刊:Journal of The Electrochemical Society
[The Electrochemical Society]
日期:2020-10-19
卷期号:167 (14): 140502-140502
被引量:2
标识
DOI:10.1149/1945-7111/abbfdd
摘要
The "sudden death" of a battery because of an abrupt capacity loss is a major cause of concern as it will leave electronic devices inoperable. Existing methodologies predict only the State of Health (SOH), Remaining Useful life (RUL) or detect abrupt capacity loss too close to the actual event, not allowing time for any corrective action. Sudden death does not happen at the same SOH, making the detection crucial. Specialized measurements or extensive number crunching are impractical for online battery health monitoring. Here, a novel lightweight framework, amenable for device implementation, with about 100 cycle advanced prediction has been proposed.
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