电池(电)
放松(心理学)
扩散
分布(数学)
材料科学
算法
计算机科学
电荷(物理)
传递函数
多项式的
图形
光学(聚焦)
荷电状态
生物系统
应用数学
传输(计算)
统计物理学
电荷守恒
样品(材料)
稳态(化学)
估计理论
数学优化
数学模型
电阻抗
数学
作者
Muhammad Sohaib,Woojin Choi
出处
期刊:Batteries
[Multidisciplinary Digital Publishing Institute]
日期:2025-10-02
卷期号:11 (10): 366-366
被引量:2
标识
DOI:10.3390/batteries11100366
摘要
In this paper, Distribution of Relaxation Time (DRT) analysis is presented as a powerful tool for understanding the aging mechanisms in lithium-ion batteries, with a focus on its application to estimating the State of Health (SOH). A novel parameter, the characteristic relaxation time, derived from DRT analysis, is introduced to enhance SOH estimation. By analyzing the ratio of the central relaxation time (τ) between the charge transfer and diffusion peaks, the battery status can be determined without the need for historical data. Experimental data from lithium-ion batteries, including 18650 cells and LR2032 coin cells, were examined until the end of their life. Nyquist and DRT plots across various frequency ranges revealed consistent aging trends, particularly in the charge transfer and diffusion processes. These processes appeared as shifting and merging peaks in the DRT plots, signifying progressive degradation. A polynomial equation fitted to the τ ratio graph achieved a high accuracy (Adj. R2 = 0.9994), enabling reliable battery lifespan prediction. Validation with a Samsung Galaxy S9+ battery demonstrated that the method could estimate its remaining life, predicting a total lifespan of approximately 2100 cycles (compared to 1000 cycles already completed). These results confirm that SOH estimation is feasible without prior data and highlight the potential of DRT analysis for accurate and quantitative prediction of battery longevity.
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