荷电状态
航程(航空)
电池(电)
电荷(物理)
锂(药物)
容量损失
离子
国家(计算机科学)
线性回归
材料科学
分析化学(期刊)
化学
统计
数学
热力学
物理
算法
复合材料
功率(物理)
色谱法
有机化学
医学
量子力学
内分泌学
作者
Jiuchun Jiang,Yang Gao,Caiping Zhang,Weige Zhang,Yan Jiang
出处
期刊:Journal of The Electrochemical Society
[The Electrochemical Society]
日期:2019-01-01
卷期号:166 (6): A1070-A1081
被引量:21
摘要
This paper conducts battery cyclic life tests under a full state-of-charge range (0-100%) and five partitioned state-of-charge ranges (0–20%, 20%–40%, 40%–60%, 60%–80% and 80%–100%). The attenuation of state-of-health indicator parameters along with cycle times under different state-of-charge ranges is compared. For the batteries cycled under 20% state-of-charge depth, loss of lithium inventory (LLI) is the leading factor resulting in capacity degradation. Expanding cycle state-of-charge depth accelerates the loss of electrode active material, but has little effects on LLI. When suffering identical cycle times, the sum of the decrements of state-of- health indicator parameter related to LLI under the five partitioned state-of-charge ranges is equal to 0–100% state-of-charge, which proves the additivity of LLI. Considering the linear correlation between capacity and state-of-health indicator parameters, a linear regression capacity model is established. Then, based on the additivity of LLI and capacity estimation model, an innovative evaluation method of battery lifetime with less testing time consumption is proposed, which conducts cycle aging tests under the partitioned state-of-charge ranges replacing full state-of-charge range to reduce testing time. Using this method, time consumption can be reduced by 75%, and the estimation error of capacity and lifetime is 3% and 10% respectively.
科研通智能强力驱动
Strongly Powered by AbleSci AI