电池(电)
荷电状态
电压
开路电压
工作(物理)
锂离子电池
汽车工程
极限(数学)
锂(药物)
可再生能源
电气工程
可靠性工程
工程类
计算机科学
功率(物理)
数学
机械工程
物理
数学分析
内分泌学
医学
量子力学
作者
Simone Barcellona,Lorenzo Codecasa,Silvia Colnago,Luigi Piegari
出处
期刊:Energies
[Multidisciplinary Digital Publishing Institute]
日期:2023-06-22
卷期号:16 (13): 4869-4869
被引量:10
摘要
In recent years, lithium-ion batteries (LiBs) have gained a lot of importance due to the increasing use of renewable energy sources and electric vehicles. To ensure that batteries work properly and limit their degradation, the battery management system needs accurate battery models capable of precisely predicting their parameters. Among them, the state of charge (SOC) estimation is one of the most important, as it enables the prediction of the battery’s available energy and prevents it from operating beyond its safety limits. A common method for SOC estimation involves utilizing the relationship between the state of charge and the open circuit voltage (OCV). On the other hand, the latter changes with battery aging. In a previous work, the authors studied a simple function to model the OCV curve, which was expressed as a function of the absolute state of discharge, q, instead of SOC. They also analyzed how the parameters of such a curve changed with the cycle aging. In the present work, a similar analysis was carried out considering the calendar aging effect. Three different LiB cells were stored at three different SOC levels (low, medium, and high levels) for around 1000 days, and an analysis of the change in the OCV-q curve model parameters with the calendar aging was performed.
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