Detection of Impedance Inhomogeneity in Lithium-Ion Battery Packs Based on Local Outlier Factor

电阻抗 锂(药物) 离群值 电池(电) 局部异常因子 离子 锂离子电池 因子(编程语言) 异常检测 材料科学 汽车工程 核工程 计算机科学 电气工程 化学 物理 工程类 人工智能 医学 热力学 功率(物理) 有机化学 内分泌学 程序设计语言
作者
Lijun Zhu,Jian Wang,Wei Wang,Bin Pan,Lujun Wang
出处
期刊:Energies [Multidisciplinary Digital Publishing Institute]
卷期号:17 (20): 5123-5123
标识
DOI:10.3390/en17205123
摘要

The inhomogeneity between cells is the main cause of failure and thermal runaway in Lithium-ion battery packs. Electrochemical Impedance Spectroscopy (EIS) is a non-destructive testing technique that can map the complex reaction processes inside the battery. It can detect and characterise battery anomalies and inconsistencies. This study proposes a method for detecting impedance inconsistencies in Lithium-ion batteries. The method involves conducting a battery EIS test and Distribution of Relaxation Times (DRT) analysis to extract characteristic frequency points in the full frequency band. These points are less affected by the State of Charge (SOC) and have a strong correlation with temperature, charge/discharge rate, and cycles. An anomaly detection characteristic impedance frequency of 136.2644 Hz was determined for a cell in a Lithium-ion battery pack. Single-frequency point impedance acquisition solves the problem of lengthy measurements and identification of anomalies throughout the frequency band. The experiment demonstrates a significant reduction in impedance measurement time, from 1.05 h to just 54 s. The LOF was used to identify anomalies in the EIS data at this characteristic frequency. The detection results were consistent with the actual conditions of the battery pack in the laboratory, which verifies the feasibility of this detection method. The LOF algorithm was chosen due to its superior performance in terms of FAR (False Alarm Rate), MAR (Missing Alarm Rate), and its fast anomaly identification time of only 0.1518 ms. The method does not involve complex mathematical models or parameter identification. This helps to achieve efficient anomaly identification and timely warning of single cells in the battery pack.
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
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
valley发布了新的文献求助10
1秒前
2秒前
老阳发布了新的文献求助10
2秒前
科研通AI5应助叙温雨采纳,获得10
3秒前
传奇3应助自信谷冬采纳,获得10
4秒前
肥肥完成签到,获得积分10
5秒前
5秒前
科研通AI2S应助1x采纳,获得10
7秒前
隐形曼青应助武玲玲采纳,获得10
7秒前
忆梦发布了新的文献求助10
8秒前
默默地读文献应助年轻契采纳,获得10
8秒前
SciGPT应助tutulucky采纳,获得10
9秒前
清秀的砖头完成签到,获得积分10
9秒前
xiaoxioayixi发布了新的文献求助10
10秒前
10秒前
10秒前
12秒前
12秒前
12秒前
Xy完成签到,获得积分10
12秒前
家伟完成签到,获得积分10
15秒前
kanohola完成签到 ,获得积分10
15秒前
16秒前
16秒前
咕噜发布了新的文献求助10
16秒前
嘿嘿完成签到 ,获得积分10
16秒前
今后应助yyyy采纳,获得10
17秒前
17秒前
baishuo完成签到,获得积分10
17秒前
机灵柚子应助忆梦采纳,获得10
17秒前
17秒前
小蘑菇应助pp采纳,获得10
19秒前
changjiaren完成签到,获得积分10
19秒前
羊羊完成签到 ,获得积分10
19秒前
19205100313应助Hresearch采纳,获得10
19秒前
cdercder应助Hresearch采纳,获得10
19秒前
19205100313应助Hresearch采纳,获得10
19秒前
高大的黎昕完成签到,获得积分10
19秒前
可爱的函函应助hyominhsu采纳,获得10
20秒前
3131879775发布了新的文献求助10
20秒前
高分求助中
All the Birds of the World 4000
Production Logging: Theoretical and Interpretive Elements 3000
Les Mantodea de Guyane Insecta, Polyneoptera 2000
Am Rande der Geschichte : mein Leben in China / Ruth Weiss 1500
CENTRAL BOOKS: A BRIEF HISTORY 1939 TO 1999 by Dave Cope 1000
Machine Learning Methods in Geoscience 1000
Resilience of a Nation: A History of the Military in Rwanda 888
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3737910
求助须知:如何正确求助?哪些是违规求助? 3281470
关于积分的说明 10025533
捐赠科研通 2998170
什么是DOI,文献DOI怎么找? 1645135
邀请新用户注册赠送积分活动 782612
科研通“疑难数据库(出版商)”最低求助积分说明 749843