Graphite//LFP synthetic V vs. Q dataset (>700,000 unique curves)
Description
This training dataset was calculated using the mechanistic modeling approach. See “Big data training data for artificial intelligence-based Li-ion diagnosis and prognosis“ (Journal of Power Sources, Volume 479, 15 December 2020, 228806) and "Analysis of Synthetic Voltage vs. Capacity Datasets for Big Data Diagnosis and Prognosis" (Energies, under review) for more details The V vs. Q dataset was compiled with a resolution of 0.01 for the triplets and C/25 charges. This accounts for more than 5,000 different paths. Each path was simulated with at most 0.85% increases for each The training dataset, therefore, contains more than 700,000 unique voltage vs. capacity curves. 4 Variables are included, see read me file for details and example how to use. Cell info: Contains information on the setup of the mechanistic model Qnorm: normalize capacity scale for all voltage curves pathinfo: index for simulated conditions for all voltage curves volt: voltage data. Each column corresponds to the voltage simulated under the conditions of the corresponding line in pathinfo.