淡出
电池(电)
可靠性(半导体)
可靠性工程
锂离子电池
降级(电信)
人口
充电周期
泄流深度
故障率
汽车工程
工程类
计算机科学
模拟
电气工程
功率(物理)
汽车蓄电池
热力学
物理
人口学
社会学
操作系统
作者
Saurabh Saxena,Yinjiao Xing,Daeil Kwon,Michael Pecht
标识
DOI:10.1016/j.ijepes.2018.12.016
摘要
As Li-ion batteries are used in increasingly diverse applications, their performance and reliability become more critical. Reliability testing of Li-ion batteries involves battery capacity fade monitoring over repeated charging/discharging cycles. Cycling at a nominal charge/discharge current requires an extensive amount of time and resources, and hence a battery qualification process based on battery cycle testing may cause delays in time to market. Discharge C-rate variable can be used for accelerating Li-ion battery cycle testing. This paper develops an accelerated capacity fade model for Li-ion batteries under multiple C-rate loading conditions, to translate the performance and degradation of a battery population at accelerated C-rate conditions to normal C-rate conditions. A nonlinear mixed-effects regression modeling technique is used to take into account the variability of repeated capacity measurements on individual batteries in a population. The model is validated using the experimental data from two battery populations that have been fielded.
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