Abstract: 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 almost 600 days under a wide range of operating conditions. We investigate calendar and cyclic aging and also apply different driving cycles to some of the cells.
This dataset is an update to the dataset previously published under the DOI 10.35097/1947 and described in the publication with the DOI 10.1038/s41597-024-03831-x. This dataset only includes log data. The result data is published under the DOI 10.35097/1969.
TechnicalRemarks: Version 1 of the dataset [1] is described in detail in [2] and Chapter 7.1 of [3]. The differences between version 1 and version 2 (this dataset) are described in the "Readme" file in [4].
[1] Luh, M., Blank, T. Comprehensive battery aging dataset: capacity and impedance fade measurements of a lithium-ion NMC/C-SiO cell [dataset]. RADAR4KIT, 2024, DOI 10.35097/1947
[2] Luh, M., Blank, T. Comprehensive battery aging dataset: capacity and impedance fade measurements of a lithium-ion NMC/C-SiO cell. Sci Data 11, 1004 (2024). https://doi.org/10.1038/s41597-024-03831-x
[3] Luh, M.: Bidirectional Charging Systems and Battery Lifetime Modeling for Vehicle-to-Grid Applications, dissertation, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany, 2024, DOI: 10.5445/IR/1000174456
[4] Luh, M., Blank, T. Comprehensive battery aging dataset: capacity and impedance fade measurements of a lithium-ion NMC/C-SiO cell [dataset – version 2: result data]. RADAR4KIT, 2024, DOI 10.35097/1969
