Modelling Li-V2O5 Batteries Using Galvanostatic Intermittent Titration Technique and Electrochemical Impedance Spectroscopy: Towards Final Applications

IF 4.6 4区 化学 Q2 ELECTROCHEMISTRY Batteries Pub Date : 2024-05-23 DOI:10.3390/batteries10060172
Johanna Naranjo-Balseca, Cynthia Martínez-Cisneros, A. Várez
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Abstract

Given the relevance of lithium and post-lithium batteries as electrochemical energy storage systems, the peculiar crystalline structure of V2O5 and its doping capacity play key roles in lithium-ion battery technology. To integrate them in high-efficiency modules, systematic methodologies are required to estimate the state of charge in a reliable way and predict the Li-V2O5 battery’s performance according to their electrochemical phenomena, including two plateaus in the galvanostatic cycling curves and the dynamic behavior governed by the energy demand. Most state of charge estimation and battery modeling procedures are focused on conventional Li-batteries that show a unique plateau. In this work, we propose a systematic methodology based on the galvanostatic intermittent titration technique and electrochemical impedance spectroscopy to study battery performance in the time and frequency domains, respectively. The proposed methodology, with a time–frequency correlation, promotes a deeper understanding of the electrochemical phenomena and general behavior of Li-V2O5 batteries, allowing for its subsequent extrapolation to more complex and higher-capacity lithium and post-lithium batteries used in high-power applications with a minimum error.
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利用静电间歇滴定技术和电化学阻抗能谱建立 Li-V2O5 电池模型:走向最终应用
鉴于锂电池和后锂电池作为电化学储能系统的重要性,V2O5 的特殊晶体结构及其掺杂能力在锂离子电池技术中发挥着关键作用。要将它们集成到高效模块中,需要系统的方法来可靠地估计电荷状态,并根据其电化学现象预测锂-V2O5 电池的性能,包括电静态循环曲线中的两个高原和受能量需求支配的动态行为。大多数电荷状态估算和电池建模程序都集中在传统锂电池上,而传统锂电池显示出独特的高原现象。在这项工作中,我们提出了一种基于静电间歇滴定技术和电化学阻抗谱的系统方法,分别在时域和频域研究电池性能。所提出的方法具有时频相关性,有助于加深对锂-V2O5 电池的电化学现象和一般行为的理解,从而可以在误差最小的情况下,将其推导到用于大功率应用的更复杂、容量更大的锂电池和后锂电池。
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来源期刊
Batteries
Batteries Energy-Energy Engineering and Power Technology
CiteScore
4.00
自引率
15.00%
发文量
217
审稿时长
7 weeks
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