阳极
阴极
电池(电)
内阻
材料科学
电极
电化学
锂离子电池
扩散
热扩散率
锂(药物)
电流密度
功率(物理)
核工程
电气工程
分析化学(期刊)
化学
工程类
热力学
物理
内分泌学
物理化学
医学
量子力学
色谱法
作者
Haijun Ruan,Bingxiang Sun,Weige Zhang,Xiaojia Su,Xitian He
出处
期刊:IEEE Transactions on Intelligent Transportation Systems
[Institute of Electrical and Electronics Engineers]
日期:2020-09-30
卷期号:22 (1): 640-650
被引量:33
标识
DOI:10.1109/tits.2020.3024801
摘要
The mechanism revelation of performance decrease and fast-charging limitation of lithium-ion batteries at low temperatures is indispensable to optimize battery design and develop fast-charging methods. In this article, an electrochemical model-based quantitative analysis method is proposed to uncover the dominant reason for performance decrease and fast-charging limitation of batteries at low temperatures. The highly important dynamic parameters are carefully determined by the experimental data from the checked three-electrode battery and optimized by the genetic algorithm, rather than directly taken from the references. Validation results confirm that the electrochemical model can well reproduce battery behaviors under different conditions and that identified parameters are accurate. The quantitative analysis indicates that the sluggish diffusion in cathode and anode electrodes is the principal reason for battery available capacity loss. Battery available power attenuation is primarily attributed to the increased film resistance of anode and the reduced exchange current density of cathode, and it is substantially independent of the reduced diffusivity. The comparison result from the lithium-plating-prevention charging current reveals that the increased film resistance of the anode is responsible for the predominant limitation of low-temperature fast-charging, despite the most change in the exchange current density of the anode. This quantitative revelation breaks through the traditional understanding from the qualitative analysis that performance decrease and fast-charging limitation of batteries at low temperatures are highly associated with the degree of the change of characteristic parameters.
科研通智能强力驱动
Strongly Powered by AbleSci AI