电池(电)
信号(编程语言)
可靠性工程
制造工艺
锂离子电池
计算机科学
过程(计算)
锂(药物)
工作(物理)
汽车工程
材料科学
工程类
机械工程
功率(物理)
操作系统
物理
内分泌学
复合材料
程序设计语言
医学
量子力学
作者
Andrew Weng,Peyman Mohtat,Peter M. Attia,Valentin Sulzer,Suhak Lee,Greg Less,Anna G. Stefanopoulou
出处
期刊:Joule
[Elsevier]
日期:2021-11-01
卷期号:5 (11): 2971-2992
被引量:66
标识
DOI:10.1016/j.joule.2021.09.015
摘要
Increasing the speed of battery formation can significantly lower lithium-ion battery manufacturing costs. However, adopting faster formation protocols in practical manufacturing settings is challenging due to a lack of inexpensive, rapid diagnostic signals that can inform possible impacts to long-term battery lifetime. This work identifies the cell resistance measured at low states of charge as an early-life diagnostic feature for screening new formation protocols. We show that this signal correlates to cycle life and improves the accuracy of data-driven battery lifetime prediction models. The signal is obtainable at the end of the manufacturing line, takes seconds to acquire, and does not require specialized test equipment. We explore a physical connection between this resistance signal and the quantity of lithium consumed during formation, suggesting that the signal may be broadly applicable for evaluating any manufacturing process change that could impact the total lithium consumed during formation.
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