Development and parameterization of a control-oriented electrochemical model of lithium-ion batteries for battery-management-systems applications

电池(电) 计算 等效电路 电压 测功机 控制理论(社会学) 计算机科学 MATLAB语言 电化学电池 生物系统
作者
Yizhao Gao,Chenghao Liu,Shun Chen,Xi Zhang,Guodong Fan,Chunbo Zhu
出处
期刊:Applied Energy [Elsevier BV]
卷期号:309: 118521-118521
标识
DOI:10.1016/j.apenergy.2022.118521
摘要

• A reduced-order electrochemical model is proposed. • Identify an accurate model with cell teardown and parameter estimation. • The cell terminal voltage and internal electrochemical states are validated. • The computation efficiency of the electrochemical model on hardware is analyzed. A precise electrochemical battery model is critical for advanced battery management systems to improve the safety and efficiency of electric vehicles. This paper presents a novel methodology to develop and parameterize the electrochemical model through cell teardown and current/voltage data estimation. The partial differential equations of ionic electrolyte and potential dynamics in the solid and liquid phases are solved and reduced to a low-order system with Padé approximation. The systematic identification procedure is proposed by first dividing the parameters into fixed geometric properties, thermodynamics, and kinetics. Then the cells are dismantled. Subsequent chemical and thermodynamic analyses, including half-cell tests, are conducted for parameter extraction. Next, the parameterized model is validated with extensive experimental data, illustrating the superior capability of predicting cell voltage with root-mean-square errors of 8.90 mV at 2C and 13.98 mV for Urban Dynamometer Driving Schedule profile at 0 °C. The accuracy of the cell internal electrochemical states of the reduced model is verified as well. Comparative studies concerning model accuracy and computation efficiency on hardware reveal that the model is 31% more accurate than equivalent circuit models but occupies similar computation resources. Finally, the need and advantages of combining cell teardown and parameter estimation in achieving a precise electrochemical model are addressed.

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
1秒前
111发布了新的文献求助10
2秒前
halo发布了新的文献求助10
2秒前
斯文败类应助水土洼采纳,获得10
3秒前
3秒前
好好完成签到,获得积分10
3秒前
Hello应助科研通管家采纳,获得10
4秒前
Lucas应助科研通管家采纳,获得10
4秒前
FashionBoy应助科研通管家采纳,获得10
4秒前
4秒前
le发布了新的文献求助30
4秒前
英俊的铭应助科研通管家采纳,获得10
4秒前
4秒前
香蕉觅云应助科研通管家采纳,获得10
4秒前
张欢馨应助科研通管家采纳,获得10
5秒前
领导范儿应助科研通管家采纳,获得10
5秒前
5秒前
明理西装应助可靠向日葵采纳,获得10
5秒前
大模型应助科研通管家采纳,获得10
5秒前
woshi123应助科研通管家采纳,获得10
5秒前
爆米花应助科研通管家采纳,获得10
5秒前
6秒前
Akim应助科研通管家采纳,获得10
6秒前
cxy发布了新的文献求助10
6秒前
woshi123应助科研通管家采纳,获得10
6秒前
星辰大海应助科研通管家采纳,获得10
6秒前
烟花应助科研通管家采纳,获得10
6秒前
明月发布了新的文献求助10
6秒前
6秒前
情怀应助科研通管家采纳,获得10
7秒前
小李爱喝梁白开完成签到,获得积分10
7秒前
7秒前
英姑应助科研通管家采纳,获得10
7秒前
woshi123应助科研通管家采纳,获得10
7秒前
桑姊完成签到,获得积分20
7秒前
胖凡应助科研通管家采纳,获得10
7秒前
无花果应助科研通管家采纳,获得10
8秒前
李春生完成签到,获得积分10
8秒前
woshi123应助科研通管家采纳,获得10
8秒前
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
Römisch-Germanische Forschungen 1000
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The fast track to determining transfer functions of linear circuits: The student guide 500
The Analytical and Numerical Solution of Electric and Magnetic Fields 500
Green Fire Retardants for Polymeric Materials 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7617360
求助须知:如何正确求助?哪些是违规求助? 9192687
关于积分的说明 19700949
捐赠科研通 7189614
什么是DOI,文献DOI怎么找? 3271994
关于科研通互助平台的介绍 2434795
邀请新用户注册赠送积分活动 2267100