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综合电池老化数据集：锂离子NMC/C-SiO电池的容量和阻抗衰减测量

Comprehensive battery aging dataset: capacity and impedance fade measurements of a lithium-ion NMC/C-SiO cell.

作者信息

Luh Matthias, Blank Thomas

机构信息

Karlsruhe Institute of Technology (KIT), Institute for Data Processing and Electronics (IPE), Eggenstein-Leopoldshafen, 76344, Germany.

出版信息

Sci Data. 2024 Sep 16;11(1):1004. doi: 10.1038/s41597-024-03831-x.

DOI:10.1038/s41597-024-03831-x
PMID:39284828
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11405776/
Abstract

Battery degradation is critical to the cost-effectiveness and usability of battery-powered products. Aging studies help to better understand and model degradation and to optimize the operating strategy. Nevertheless, there are only a few comprehensive and freely available aging datasets for these applications. To our knowledge, the dataset presented in the following is one of the largest published to date. It contains over 3 billion data points from 228 commercial NMC/C+SiO lithium-ion cells aged for more than a year under a wide range of operating conditions. We investigate calendar and cyclic aging and also apply different driving cycles to cells. The dataset includes result data (such as the remaining usable capacity or impedance measured in check-ups) and raw data (i.e., measurement logs with two-second resolution). The data can be used in a wide range of applications, for example, to model battery degradation, gain insight into lithium plating, optimize operating strategies, or test battery impedance or state estimation algorithms using machine learning or Kalman filtering.

摘要

电池退化对于电池供电产品的成本效益和可用性至关重要。老化研究有助于更好地理解和模拟退化，并优化运行策略。然而，针对这些应用的全面且免费可用的老化数据集却很少。据我们所知，以下呈现的数据集是迄今为止已发布的最大数据集之一。它包含来自228个商用NMC/C+SiO锂离子电池在广泛运行条件下经过一年多老化的超过30亿个数据点。我们研究日历老化和循环老化，并对电池应用不同的驱动循环。该数据集包括结果数据（如在检查中测量的剩余可用容量或阻抗）和原始数据（即具有两秒分辨率的测量日志）。这些数据可用于广泛的应用，例如，对电池退化进行建模、深入了解锂镀层、优化运行策略，或使用机器学习或卡尔曼滤波测试电池阻抗或状态估计算法。

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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cfa6/11405776/8d76f47a859a/41597_2024_3831_Fig10_HTML.jpg
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