Lithium-ion battery calendar aging mechanism analysis and impedance-based State-of-Health estimation method

健康状况 锂离子电池 电池(电) 计算机科学 可靠性工程 工程类 物理 功率(物理) 量子力学
作者
Qi Zhang,Dafang Wang,Erik Schaltz,Daniel‐Ioan Stroe,Alejandro Gismero,Bowen Yang
出处
期刊:Journal of energy storage [Elsevier BV]
卷期号:64: 107029-107029 被引量:14
标识
DOI:10.1016/j.est.2023.107029
摘要

Calendar aging is an important part of lithium-ion battery aging research. In response to the problem that the aging history of a battery cell, whose State-of-Health (SOH) needs to be estimated, may be not available, this paper proposes a SOH estimation model not relying on calendric aging conditions such as storage State-of-Charge (SOC) and storage temperature. The aging mechanisms of lithium-ion batteries in different calendric aging conditions are analyzed to investigate the influences of different aging conditions on battery internal behaviors. The neural network is used to build the SOH estimation model. To prove that the model accuracy is not affected by battery aging history, SOH indicators of cells aged at different conditions are set as training data set and testing data set respectively, and trained SOH estimation accuracy and tested SOH estimation accuracy are compared. The comparison shows that increments of mean absolute error (MAE) of SOH estimation introduced by the aging condition difference between trained data and tested data are less than 2 %. Using SOH indicators obtained at different SOC levels as inputs of the model also hardly reduce the model accuracy. The increase of MAE of SOH estimation because of the SOC difference between trained data and tested data are less than 1.5 %.
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
狗大王发布了新的文献求助10
刚刚
XYJ发布了新的文献求助10
刚刚
1秒前
希望天下0贩的0应助嬛嬛采纳,获得10
1秒前
星海进完成签到,获得积分10
2秒前
3秒前
情怀应助安静雅阳采纳,获得10
4秒前
4秒前
5秒前
shinysparrow应助淡淡从安采纳,获得100
5秒前
Augenstern完成签到,获得积分20
6秒前
7秒前
充电宝应助MingqingFang采纳,获得10
7秒前
喏晨发布了新的文献求助10
8秒前
8秒前
拉长的初蓝完成签到,获得积分10
8秒前
8秒前
9秒前
10秒前
Augenstern发布了新的文献求助10
10秒前
10秒前
10秒前
11秒前
wanci应助苗条的小肥羊采纳,获得10
11秒前
董菲音发布了新的文献求助10
12秒前
12秒前
FFFFcom发布了新的文献求助30
12秒前
七月流火应助pw采纳,获得50
12秒前
SciGPT应助张晓东采纳,获得10
13秒前
shs发布了新的文献求助10
13秒前
CipherSage应助Rainbow采纳,获得10
13秒前
科研yu完成签到,获得积分10
13秒前
彳亍发布了新的文献求助10
13秒前
13秒前
djy发布了新的文献求助10
14秒前
14秒前
机灵的海蓝完成签到,获得积分10
14秒前
14秒前
香蕉觅云应助Young采纳,获得10
14秒前
传奇3应助HANK2024采纳,获得10
14秒前
高分求助中
A new approach to the extrapolation of accelerated life test data 1000
ACSM’s Guidelines for Exercise Testing and Prescription, 12th edition 500
Picture Books with Same-sex Parented Families: Unintentional Censorship 500
Nucleophilic substitution in azasydnone-modified dinitroanisoles 500
不知道标题是什么 500
A Preliminary Study on Correlation Between Independent Components of Facial Thermal Images and Subjective Assessment of Chronic Stress 500
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 360
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 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3971277
求助须知:如何正确求助?哪些是违规求助? 3515939
关于积分的说明 11180280
捐赠科研通 3251061
什么是DOI,文献DOI怎么找? 1795664
邀请新用户注册赠送积分活动 875937
科研通“疑难数据库(出版商)”最低求助积分说明 805209