GIC//NMC Solar Battery Synthetic Data 1 - 700,000 degradation for 03/21 clear-sky irradiance
This dataset consists of part 1 of the data associated with publication "Data-driven Direct Diagnosis of PV Connected Batteries " The synthetic cycles were generated 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 Li-ion Diagnosis and Prognosis" (Energies 2021, 14, 2371 ) for more details. These datasets were 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. Each dataset contains more than 700,000 unique voltage vs. capacity curves. Two datasets are provided, one for training and one for validation. There were generated with slightly different cell parameters to account for cell-to-cell variations. Details are available in publication. For each dataset, 3 set of files are provided, the *_V_* files contains V vs. Q data, the *_t_* files contains V vs. time data and the *_R_* files contains rate vs. Q data. More details on content is provided in the read me file. All simulations were performed with the 2022 version of the alawa toolbox using stock electrode data. Voltage and kinetics of electrodes from different manufacturers, with different composition, or with different architecture might differ significantly.