Implementation of gas formation into a finite-element model for the mechanical swelling simulation of lithium-ion batteries

肿胀 的 电池(电) 材料科学 有限元法 复合材料 压缩(物理) 预加载 机械工程 结构工程 气体压力 机械 刚度 计算机模拟 降级(电信) 产量(工程) 电池组 机械压缩 核工程
作者
Jun Yin,Christoph Drießen,Rico Klink,Stephan Kizio,Jörg Moser,Christian Ellersdorfer,Patrick Höschele
出处
期刊:Journal of energy storage [Elsevier BV]
卷期号:150: 120376-120376
标识
DOI:10.1016/j.est.2026.120376
摘要

Lithium-ion batteries (LIBs) are playing an increasingly vital role in electric vehicles. LIBs are assembled into modules with a preload force to ensure stability and safety. During cycling, battery swelling increases the force within the module. In addition, gas formation, resulting from the battery aging mechanisms, may impact swelling behavior and impair battery performance and safety. While researchers have developed various models to analyze swelling mechanisms, few have considered implementing gas formation into mechanical swelling models. However, the effect of gas formation should not be overlooked, as it has a significant impact on aged batteries. Herein, we implement gas formation into a simplified finite element model to better evaluate the swelling mechanism of LIBs. We found that, for the model of an aged cell with 1900 cycles, it achieves a mean absolute percentage error (MAPE) of 10.24% for force change and 15.12% for thickness change with gas formation (as compared with experimental results), versus the 565.05% for force change and 228.30% for thickness change achieved without gas formation, thus underscoring the critical impact of gas formation on cell swelling mechanisms. These findings suggest that gas formation is a needed consideration in a swelling model to predict a change in battery thickness and swelling-related force fluctuation. The approach in our study is crucial for evaluating the impact of gas on battery mechanical behavior and can be applied to determine the optimal preload force in further investigations. • Gas formation is implemented into a finite-element battery swelling model. • Gas formation contributes to the reduction of battery compression modulus. • Model with gas formation shows higher accuracy for battery swelling behavior than the non-gas model.
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
科研通AI2S应助pengpeng采纳,获得30
刚刚
小蘑菇应助瑰慈采纳,获得10
刚刚
zhuo完成签到,获得积分10
刚刚
刚刚
1秒前
mlle完成签到,获得积分10
1秒前
1秒前
哈扎尔完成签到 ,获得积分0
1秒前
1秒前
印第安老斑鸠应助无趣采纳,获得10
1秒前
kksk完成签到,获得积分10
1秒前
脑洞疼应助snowman采纳,获得10
2秒前
2秒前
gold发布了新的文献求助10
2秒前
彭于晏应助kingcoming采纳,获得10
3秒前
3秒前
4秒前
4秒前
applelpypies完成签到 ,获得积分10
5秒前
5秒前
5秒前
kksk发布了新的文献求助10
5秒前
Yoki完成签到,获得积分20
5秒前
5秒前
荷包蛋发布了新的文献求助10
5秒前
隐形曼青应助hu123采纳,获得10
6秒前
GAO完成签到,获得积分10
6秒前
6秒前
JUN发布了新的文献求助10
6秒前
六六发布了新的文献求助10
6秒前
yuan发布了新的文献求助10
6秒前
wanci应助博修采纳,获得10
6秒前
狂的没边完成签到,获得积分10
6秒前
ShawnFusion完成签到,获得积分10
6秒前
7秒前
zhao完成签到 ,获得积分20
7秒前
7秒前
7秒前
8秒前
富川完成签到,获得积分10
8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
The Multiple Self-States Drawing Technique 600
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Rosenblum, Global Change Biology 500
CLSI VET01S-2024 Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals (7th Ed) 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7769771
求助须知:如何正确求助?哪些是违规求助? 9312748
关于积分的说明 20330652
捐赠科研通 7355024
什么是DOI,文献DOI怎么找? 3316114
关于科研通互助平台的介绍 2464976
邀请新用户注册赠送积分活动 2330817