Comprehensive battery aging dataset: capacity and impedance fade measurements of a lithium-ion NMC/C-SiO cell [dataset] 候选 · 未审核

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Battery degradation is critical to the cost-effectiveness and usability of battery-powered products. Aging studies can help to better understand and model degradation and to optimize the operation 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 some of the 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 operation strategies, or test battery impedance or state estimation algorithms using machine learning or Kalman filtering.

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落地页

https://zenodo.org/records/14555746

许可证

Open Access (置信:inferred)

发布年份

2024

发布方

Karlsruhe Institute of Technology

设备类型

battery

PHM 任务

degradation_trend_prediction

分发点

故障工况

运行工况