介电谱
电阻抗
等效电路
软件
计算机科学
宽带
电池(电)
电子工程
锂(药物)
电气工程
电压
材料科学
工程类
电化学
电信
电极
功率(物理)
化学
物理
内分泌学
物理化学
程序设计语言
医学
量子力学
作者
Emanuele Buchicchio,Alessio De Angelis,Francesco Santoni,Paolo Carbone,Francesco Bianconi,Fabrizio Smeraldi
标识
DOI:10.1016/j.simpa.2022.100447
摘要
Electrochemical impedance spectroscopy (EIS) is a fundamental tool used in numerous research fields and applications. In particular, EIS is commonly employed for studying and monitoring lithium-ion batteries, to ensure their safe and efficient operation. The LiBEIS software tool computes EIS data by processing the voltage and current time series acquired from a battery under test, which is excited with a broadband current signal. Furthermore, LiBEIS performs fitting of the EIS data to an equivalent circuit model, which is often employed in practice to analyse the behaviour of the battery. Finally, LiBEIS implements exploratory data analysis tools and machine-learning methods aimed at estimating the state-of-charge (SOC) from EIS data.
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