Electrochemical State-Based Sinusoidal Ripple Current Charging Control

涟漪 电池(电) 电阻抗 电动汽车 控制理论(社会学) 计算机科学 电气工程 电压 电子工程 材料科学 工程类 功率(物理) 控制(管理) 物理 量子力学 人工智能
作者
Yong-Duk Lee,Sung-Yeul Park
出处
期刊:IEEE Transactions on Power Electronics [Institute of Electrical and Electronics Engineers]
卷期号:30 (8): 4232-4243 被引量:74
标识
DOI:10.1109/tpel.2014.2354013
摘要

This paper presents a sinusoidal ripple current charging algorithm based on embedded impedance measurements. Existing battery charging strategies typically do not take into account the electrochemical properties of batteries, because these factors are difficult to obtain during charging operation. Factors of concern include lithium plating, growth of a solid electrolyte interphase, limited exchange current, and slow diffusion rates. It is beneficial to utilize these parameters during charging operation, because the charging current can adapt to the time-varying characteristics of a battery. Consequently, battery life cycle, charging speed, and charging efficiency all improve. In this paper, rigorous analysis of electrochemical characteristics is performed and a method for minimization of variations of charge transfer impedance is explained based on a sinusoidal ripple current charging algorithm. To obtain the optimal ripple current frequency, ac impedance analysis based on the dq transformation method is proposed. As a result, this method improved charging efficiency and reduced lithium plating by activation polarization. Simulation and experimental results using a 14.6-V LiFeMgPO 4 battery are used to validate and demonstrate the performance of the proposed control scheme. Based on the proposed control scheme, the charging time and efficiency of the Li-ion battery are improved by 5.1% and 5.6%, respectively.
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
西瓜发布了新的文献求助10
1秒前
科研通AI2S应助无私惜雪采纳,获得30
2秒前
2秒前
3秒前
4秒前
4秒前
5秒前
molihuakai应助mojomars采纳,获得10
5秒前
6秒前
6秒前
6秒前
7秒前
奕奕发布了新的文献求助10
7秒前
8秒前
cdercder应助负责的问雁采纳,获得10
9秒前
归海平灵发布了新的文献求助10
9秒前
香爆脆发布了新的文献求助10
10秒前
pcg发布了新的文献求助10
11秒前
ymmmjjd发布了新的文献求助10
12秒前
12秒前
12秒前
毛毛余发布了新的文献求助10
12秒前
12秒前
13秒前
14秒前
15秒前
linshunan发布了新的文献求助10
15秒前
16秒前
乐乐应助李硕采纳,获得10
16秒前
香蕉觅云应助Clare采纳,获得10
17秒前
17秒前
科研通AI2S应助pcg采纳,获得10
17秒前
共享精神应助hata采纳,获得10
17秒前
YHY发布了新的文献求助10
18秒前
Owen应助阿花采纳,获得10
19秒前
19秒前
20秒前
20秒前
大模型应助西瓜采纳,获得10
21秒前
21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
An Introduction to Foreign Language Learning and Teaching 750
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Cosmos as Art Object: Studies in Plato's Timaeus and Other Dialogues 500
What is the Future of Psychotherapy in Digital Age? Technology, AI Bots, and Psychotherapy after Covid 444
煤炭地下气化渗流燃烧方法的研究 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 7632041
求助须知:如何正确求助?哪些是违规求助? 9206467
关于积分的说明 19744653
捐赠科研通 7201360
什么是DOI,文献DOI怎么找? 3274739
关于科研通互助平台的介绍 2436632
邀请新用户注册赠送积分活动 2271402