Binary multi-frequency signal for accurate and rapid electrochemical impedance spectroscopy acquisition in lithium-ion batteries

介电谱 电阻抗 锂离子电池 材料科学 电池(电) 计算机科学 电子工程 电气工程 工程类 化学 电化学 电极 物理 量子力学 物理化学 功率(物理)
作者
Xutao Liu,Shengyu Tao,Shiyi Fu,Ruifei Ma,Tingwei Cao,Hongtao Fan,Junxiong Zuo,Xuan Zhang,Yu Wang,Yaojie Sun
出处
期刊:Applied Energy [Elsevier BV]
卷期号:364: 123221-123221 被引量:12
标识
DOI:10.1016/j.apenergy.2024.123221
摘要

Electrochemical Impedance Spectroscopy (EIS) plays a crucial role in characterizing the internal electrochemical states of lithium-ion batteries and proves to be effective for estimating battery states. Traditional EIS measurement, however, requires expensive electrochemical workstations with time-consuming signal injection, especially in low-frequency regions, thus limiting its practical applications. Here we show that applying our proposed pulse-like Binary Multi-Frequency Signals (BMFS) as the excitation signal in the EIS measurement, which simultaneously possesses numerous frequency components and maintains high energy at each frequency component, will significantly improve test speed while retaining accuracy. The applicability of the BMFS under various cathode material types, including nickel cobalt manganese (NCM), lithium cobalt oxide (LCO), and lithium iron phosphate (LFP) is demonstrated. The robustness of the signal is experimentally verified through varying C-rates and measurement window lengths. The BMFS, requiring only 30 s per test, can achieve test results with an amplitude error of 1% and a phase error of 1° as compared with those obtained from traditional EIS tests. Moreover, BMFS can also be applied in online EIS measurement scenarios, favorable for real-world applications. This work enables accurate and rapid acquisition of EIS results, which is currently expensive and time-consuming to obtain, ensuring a faster and more nuanced characterization of the internal states of many battery systems in an affordable and accessible manner, especially in data-driven and machine-learning approaches.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
情怀应助青1995采纳,获得10
刚刚
刚刚
浮游应助薄雪草采纳,获得10
2秒前
Louislee发布了新的文献求助10
2秒前
宋祝福完成签到 ,获得积分10
3秒前
3秒前
Lumosii发布了新的文献求助10
4秒前
opp完成签到,获得积分10
5秒前
量子星尘发布了新的文献求助10
6秒前
拼搏凌雪发布了新的文献求助30
6秒前
文献发布了新的文献求助10
7秒前
8秒前
9秒前
rmbsLHC发布了新的文献求助10
10秒前
三桥aq完成签到,获得积分10
11秒前
Orange应助杨宁采纳,获得10
11秒前
虚心的灵煌完成签到,获得积分10
13秒前
13秒前
莫默应助yuananw采纳,获得10
14秒前
青1995发布了新的文献求助10
15秒前
卷aaaa完成签到,获得积分10
15秒前
梓歆完成签到 ,获得积分10
16秒前
不配.应助殷勤的紫槐采纳,获得300
16秒前
大意的柚子完成签到,获得积分10
17秒前
17秒前
Lynn完成签到,获得积分10
17秒前
19秒前
领导范儿应助小章鱼采纳,获得10
19秒前
打打应助YE采纳,获得10
20秒前
知性的千秋完成签到,获得积分10
21秒前
陈婷婷完成签到,获得积分10
22秒前
烤冷面发布了新的文献求助10
22秒前
eddy完成签到,获得积分10
22秒前
24秒前
Louislee完成签到,获得积分10
26秒前
量子星尘发布了新的文献求助150
26秒前
无限小霜完成签到,获得积分10
26秒前
29秒前
张泽轩发布了新的文献求助10
29秒前
猪猪侠完成签到 ,获得积分10
30秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Acute Mountain Sickness 2000
Cowries - A Guide to the Gastropod Family Cypraeidae 1200
Handbook of Milkfat Fractionation Technology and Application, by Kerry E. Kaylegian and Robert C. Lindsay, AOCS Press, 1995 1000
A novel angiographic index for predicting the efficacy of drug-coated balloons in small vessels 500
Textbook of Neonatal Resuscitation ® 500
The Affinity Designer Manual - Version 2: A Step-by-Step Beginner's Guide 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 内科学 生物化学 物理 计算机科学 纳米技术 遗传学 基因 复合材料 化学工程 物理化学 病理 催化作用 免疫学 量子力学
热门帖子
关注 科研通微信公众号,转发送积分 5057345
求助须知:如何正确求助?哪些是违规求助? 4282678
关于积分的说明 13346384
捐赠科研通 4099744
什么是DOI,文献DOI怎么找? 2244412
邀请新用户注册赠送积分活动 1250543
关于科研通互助平台的介绍 1181032