淡出
阳极
容量损失
开路电压
电压
锂(药物)
指数函数
材料科学
参数化复杂度
降级(电信)
控制理论(社会学)
电气工程
化学
计算机科学
工程类
数学
算法
医学
数学分析
控制(管理)
物理化学
电极
内分泌学
人工智能
操作系统
作者
Alexander Karger,Julius Schmitt,Cedric Kirst,Jan P. Singer,Leo Wildfeuer,Andreas Jossen
标识
DOI:10.1016/j.jpowsour.2023.233947
摘要
Cycling lithium-ion batteries causes capacity fade, but also changes the shape of the open-circuit voltage (OCV) curve, due to loss of active material (LAM) and loss of lithium inventory (LLI). To model this change, we recently proposed a novel empirical calendar aging model that is parameterized on component states of health (SOHs) instead of capacity fade only. In this work, we present a mechanistic aging model for cycle aging, allowing prediction of capacity fade, OCV curve change and component degradation. The model is parameterized on cycling data of 59 commercial lithium-ion batteries with NCA cathode and silicon–graphite anode, which were cycled for 2500 equivalent full cycles under varying conditions. We propose a stepwise approach to identify the most relevant stress parameters causing LLI and LAM, where we also separate between loss of accessible graphite and silicon in the blend anode. Stress parameter dependence is modeled with linear combinations of exponential functions and the model predicts capacity fade with 1.04% mean absolute error (MAE). For all test conditions, LLI is the dominating degradation mode and loss of accessible graphite is negligible. Reconstructed OCV curves reduce the median voltage MAE by a factor of 8, compared to not updating the OCV.
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