A calorimetric approach to fast entropy-variations extraction for lithium-ion batteries using optimized galvanostatic intermittent titration technique

IF 5.4 Q2 CHEMISTRY, PHYSICAL
Abdul Muiz Ahmad, Guillaume Thenaisie, Sang-Gug Lee
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引用次数: 0

Abstract

A fast entropy-variations (ΔS) extraction method has been proposed based on calorimetry, which determines the heat associated with ΔS by analyzing the electro-thermal response of a battery to a sequence of constant current pulses, i.e., the galvanostatic intermittent titration technique (GITT). The rest times in GITT are reduced by only considering limited relaxation of the ionic concentration gradients inside the battery after the current interruptions while completely ignoring the thermal equilibrium conditions inside the calorimeter. The resulting thermal signal of the battery is analyzed using an algorithm that adopts exponential regression to characterize the generated heat energy corresponding to each current pulse. Additionally, the polarization heat inside the battery is investigated by taking into account the initial presence of the concentration gradients when a current pulse is applied. Thus, the optimized rest times between the successive current pulses can reduce the measurement time manyfold compared to the previously reported methods, which require the battery to reach both electrochemical and thermal equilibriums. This work shows that the ΔS profiles of a 1 Ah NMC811/graphite pouch cell with 2.5% state of charge (SOC) resolution can be extracted at least three times faster than the method with unoptimized rest times, in a highly repeatable manner.

基于优化恒流间歇滴定技术的锂离子电池熵变快速提取热法研究
提出了一种基于量热法的快速熵变(ΔS)提取方法,该方法通过分析电池对一系列恒流脉冲的电热响应来确定与ΔS相关的热量,即恒流间歇滴定技术(git)。通过只考虑电流中断后电池内部离子浓度梯度的有限松弛,而完全忽略量热计内部的热平衡条件,可以减少GITT的休息时间。利用指数回归的算法对电池产生的热信号进行分析,以表征每个电流脉冲对应的产生的热能。此外,考虑到电流脉冲时浓度梯度的初始存在,对电池内部的极化热进行了研究。因此,与之前报道的需要电池达到电化学和热平衡的方法相比,连续电流脉冲之间的优化休息时间可以将测量时间减少许多倍。这项工作表明,具有2.5%荷电状态(SOC)分辨率的1 Ah NMC811/石墨袋电池的ΔS轮廓可以比未优化休息时间的方法提取至少快3倍,并且具有高度可重复性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
9.10
自引率
0.00%
发文量
18
审稿时长
64 days
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