HNEI diagnosis dataset

CC BY 4.0Introduced 2021-03-19

This dataset contains more than 700,000 unique voltage vs. capacity curves for training Artificial Intelligence (AI) systems for lithium-ion battery diagnosis and prognosis. It 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 Li-ion Diagnosis and Prognosis" (Energies, under review) for more details.

This 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 degradation mode.