Dataset Open Access
Data-driven capacity estimation of commercial lithium-ion batteries from voltage relaxation
Jiangong Zhu;
Yixiu Wang;
Yuan Huang;
R. Bhushan Gopaluni;
Yankai Cao;
Michael Heere;
Martin J. Mühlbauer;
Liuda Mereacre;
Haifeng Dai;
Xinhua Liu;
Anatoliy Senyshyn;
Xuezhe Wei;
Michael Knapp;
Helmut Ehrenberg
Here are the datasets for the publication named "Data-driven capacity estimation of commercial lithium-ion batteries from voltage relaxation" published in Nature Communications. Experimental cycling data for three commercial 18650 type batteries (Dataset_1:NCA battery, Dataset_2:NCM battery, and Dataset_3:NCM+NCA_battery) are given, where each csv file corresponds to one cell cycling data. The cells are named as CYX-Y_Z-#N according to their cycling conditions. X means the temperature, Y_Z represents the charge_discharge current rate, #N is the cell tag. Each csv file has 9 columns, including cycle time ('time/s'), controlled voltage and current ('control/V/mA'), battery voltage ('Ecell/V'), applied current ('<I>/mA'), charge or discharge electricity ('Q discharge/mA.h' and 'Q discharge/mA.h'), controlled voltage or current ('control/V', 'control/mA' and ), and cycle number ('cycle number'). In the impedance data, one representative cell from each cycling condition is chosen for the discussion in the main text. More detailed descriptions can be found in the zip file.
| Name | Size | |
|---|---|---|
|
Dataset_1_NCA_battery.zip
md5:cbd6d7eab2a296b52385e025e8d0f42a |
579.6 MB | Download |
|
Dataset_2_NCM_battery.zip
md5:a05c485df92f4af560d1d8d7f659ce1b |
737.0 MB | Download |
|
Dataset_3_NCM_NCA_battery.zip
md5:d11e68e410a638058906af5e2f5f60f3 |
356.1 MB | Download |
|
Impedance raw data and fitting data.zip
md5:be9a8088847edd6528ce888372b42465 |
1.3 MB | Download |
| All versions | This version | |
|---|---|---|
| Views | 4,283 | 4,099 |
| Downloads | 4,105 | 3,939 |
| Data volume | 2.2 TB | 2.1 TB |
| Unique views | 3,350 | 3,262 |
| Unique downloads | 1,246 | 1,216 |
- Publication date:
- April 1, 2022
- DOI:
-
- Keyword(s):
- Lithium-ion battery Cycling datasets Degradation
- License (for files):
- Creative Commons Attribution 4.0 International