淡出
电池(电)
计算机科学
电池容量
锂(药物)
容量损失
锂离子电池
可靠性工程
模拟
工程类
功率(物理)
量子力学
医学
操作系统
物理
内分泌学
作者
Venkatasailanathan Ramadesigan,Kejia Chen,Nancy A. Burns,Vijayasekaran Boovaragavan,Richard D. Braatz,Venkat R. Subramanian
出处
期刊:Journal of The Electrochemical Society
[The Electrochemical Society]
日期:2011-01-01
卷期号:158 (9): A1048-A1048
被引量:158
摘要
Many researchers have worked to develop methods to analyze and characterize capacity fade in lithium-ion batteries. As a complement to approaches to mathematically model capacity fade that require detailed understanding of each mechanism, capacity fade was accurately and efficiently predicted for future cycles using a discrete approach by extrapolating the change in effective transport and kinetic parameters with cycle number (N) for a battery tested under controlled experimental conditions. The effective parameters and their uncertainties are estimated using a mathematical reformulation of a porous electrode model, whose computational efficiency enables the integration of the proposed approach into an inexpensive microprocessor for estimating the remaining lifetime of a battery based on past charge-discharge curves. The approach may also provide some guidance for designers as to which battery components to focus on for redesign to reduce capacity fade.
科研通智能强力驱动
Strongly Powered by AbleSci AI