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研究测量时间尺度对锂离子电池内阻特征化方法的影响。

A study of the influence of measurement timescale on internal resistance characterisation methodologies for lithium-ion cells.

机构信息

WMG, University of Warwick, Coventry, CV4 7AL, United Kingdom.

出版信息

Sci Rep. 2018 Jan 8;8(1):21. doi: 10.1038/s41598-017-18424-5.

Abstract

The power capability of a lithium ion battery is governed by its resistance, which changes with battery state such as temperature, state of charge, and state of health. Characterizing resistance, therefore, is integral in defining battery operational boundaries, estimating its performance and tracking its state of health. There are many techniques that have been employed for estimating the resistance of a battery, these include: using DC pulse current signals such as pulse power tests or Hybrid Pulse Power Characterization (HPPC) tests; using AC current signals, i.e., electrochemical impedance spectroscopy (EIS) and using pulse-multisine measurements. From existing literature, these techniques are perceived to yield differing values of resistance. In this work, we apply these techniques to 20 Ah LiFePO/C pouch cells and use the results to compare the techniques. The results indicate that the computed resistance is strongly dependent on the timescales of the technique employed and that when timescales match, the resistances derived via different techniques align. Furthermore, given that EIS is a perturbative characterisation technique, employing a spectrum of perturbation frequencies, we show that the resistance estimated from any technique can be identified - to a high level of confidence - from EIS by matching their timescales.

摘要

锂离子电池的功率能力受其内阻的控制,内阻会随着电池的状态(如温度、荷电状态和健康状态)而变化。因此,内阻的特性分析对于定义电池的工作边界、估计其性能和跟踪其健康状态是必不可少的。已经有许多技术被用于估计电池的内阻,包括:使用直流脉冲电流信号,如脉冲功率测试或混合脉冲功率特性(HPPC)测试;使用交流电流信号,即电化学阻抗谱(EIS)和使用脉冲多音测量。根据现有文献,这些技术被认为会产生不同的内阻值。在这项工作中,我们将这些技术应用于 20AhLiFePO/C 软包电池,并使用结果进行比较。结果表明,计算出的内阻强烈依赖于所采用技术的时间尺度,并且当时间尺度相匹配时,通过不同技术得出的内阻是一致的。此外,由于 EIS 是一种微扰特性分析技术,采用了一系列的微扰频率,我们表明,通过匹配它们的时间尺度,可以从 EIS 中非常有信心地识别出任何技术估计的内阻。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ba1/5758786/747c6358f247/41598_2017_18424_Fig1_HTML.jpg

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