Published April 1, 2022 | Version v2
Dataset Open

Data-driven capacity estimation of commercial lithium-ion batteries from voltage relaxation

  • 1. Tongji Univerisity, Karlsruhe Institute of Technology
  • 2. University of British Columbia
  • 3. Karlsruhe Institute of Technology, Technische Universität München
  • 4. Karlsruhe Institute of Technology
  • 5. Tongji University
  • 6. Beihang University
  • 7. Technische Universität München

Description

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.

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Dataset_1_NCA_battery.zip

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