{"url":"/dataset/hnei-diagnosis-dataset","name":"HNEI diagnosis dataset","full_name":null,"description_markdown":"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.\r\n\r\nThis 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.","description_withheld":null,"homepage":"https://data.mendeley.com/datasets/bs2j56pn7y/3","introduced_date":"2021-03-19","introduced_date_note":null,"introduced_by":null,"license":{"name":"CC BY 4.0","url":null},"modalities":[],"tasks":[],"languages":[],"variants":["HNEI diagnosis dataset"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-25T09:33:49+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}