| --- |
| license: cc-by-4.0 |
| language: |
| - en |
| size_categories: |
| - 1B<n<10B |
| task_categories: |
| - time-series-forecasting |
| - tabular-regression |
| tags: |
| - battery |
| - state-of-charge |
| - state-of-health |
| - lithium-ion |
| - LFP |
| - lithium-iron-phosphate |
| - fast-charging |
| - cycling |
| - kalman-filter |
| - benchmark |
| - bsebench |
| - tier-1-raw |
| pretty_name: "Severson 2019 LFP Fastcharge — Tier 1 Raw Mirror" |
| --- |
| |
| # severson-2019-raw |
|
|
| **Tier 1 raw mirror** of the Severson et al. 2019 commercial LFP fastcharge |
| cycling dataset, hosted under the [BSEBench](https://bsebench.org) |
| organization on the HuggingFace Hub. The files in this repository are |
| preserved bit-exact as published on the original Toyota Research Institute |
| data portal at [data.matr.io](https://data.matr.io/1/). No values are |
| modified; no columns are renamed; no rows are dropped. Every file's |
| SHA-256 digest is recorded in the BSEBench manifest YAML and matches the |
| original distribution. |
|
|
| This repository exists for **provenance verification and audits only**. |
| For the BSEBench-canonical Parquet harmonization that consumers actually |
| use for filter benchmarking, see the Tier 2 sibling repository |
| [`bsebench-org/severson-2019`](https://huggingface.co/datasets/bsebench-org/severson-2019). |
|
|
| ## Status |
|
|
| This is a **placeholder card**. The raw `.mat` files are not yet uploaded |
| to the HuggingFace Hub. The planned upload pipeline is : |
|
|
| 1. Manual download of the three Severson batches from |
| `https://data.matr.io/1/projects/5c48dd2bc625d700019f3204` (registration |
| may be required by the TRI portal). |
| 2. Local SHA-256 computation via `scripts/upload_tier1_to_hf.py --src ./local |
| --repo-id bsebench-org/severson-2019-raw --private --dry-run`. |
| 3. Inventory cross-check against |
| `bsebench-datasets/manifests/severson_2019_lfp.yaml` (committed only after |
| real digests are populated — no fake checksums in this repository). |
| 4. Public upload (`--dry-run` removed) once the manifest validates. |
| 5. Update of this card with the populated `## File inventory` section, the |
| manifest commit SHA, and a `verified_at` timestamp. |
|
|
| Until step 5 is reached, treat the file inventory below as a **best-effort |
| estimate** based on community references (BatteryML, BEEP, MIT Braatz Group |
| GitHub repository), not as a directly verified manifest of HuggingFace |
| content. |
|
|
| ## What this is |
|
|
| A bit-exact mirror of the dataset published with : |
|
|
| > **Severson, K. A., Attia, P. M., Jin, N., Perkins, N., Jiang, B., |
| > Yang, Z., Chen, M. H., Aykol, M., Herring, P. K., Fraggedakis, D., |
| > Bazant, M. Z., Harris, S. J., Chueh, W. C., Braatz, R. D. (2019).** |
| > "Data-driven prediction of battery cycle life before capacity degradation." |
| > *Nature Energy*, **4**(5), 383–391. |
| > doi:[10.1038/s41560-019-0356-8](https://doi.org/10.1038/s41560-019-0356-8) |
|
|
| ```bibtex |
| @article{severson2019datadriven, |
| author = {Severson, Kristen A. and Attia, Peter M. and Jin, Norman |
| and Perkins, Nicholas and Jiang, Benben and Yang, Zi |
| and Chen, Michael H. and Aykol, Muratahan |
| and Herring, Patrick K. and Fraggedakis, Dimitrios |
| and Bazant, Martin Z. and Harris, Stephen J. |
| and Chueh, William C. and Braatz, Richard D.}, |
| title = {Data-driven prediction of battery cycle life before |
| capacity degradation}, |
| journal = {Nature Energy}, |
| volume = {4}, |
| number = {5}, |
| pages = {383--391}, |
| year = {2019}, |
| doi = {10.1038/s41560-019-0356-8}, |
| url = {https://www.nature.com/articles/s41560-019-0356-8}, |
| } |
| ``` |
|
|
| ## Cell specifications |
|
|
| | Property | Value | |
| |---|---| |
| | Manufacturer | A123 Systems | |
| | Model | APR18650M1A | |
| | Form factor | 18650 cylindrical | |
| | Cathode chemistry | LFP (lithium iron phosphate, LiFePO4) | |
| | Anode chemistry | Graphite | |
| | Nominal capacity | 1.1 Ah | |
| | Nominal voltage | 3.3 V | |
| | Charge cutoff (used) | 3.6 V | |
| | Discharge cutoff (used) | 2.0 V | |
| | Number of cells (this dataset) | 124 | |
| | End-of-life threshold | 80 % capacity retention | |
|
|
| ## Cycling protocol |
|
|
| All cells were cycled inside a 30 °C controlled environmental chamber. |
| Charging was performed under one-step or two-step fast-charging policies |
| spanning charge rates from 1C to 6C (corresponding to 8 to 13.3 minutes |
| to reach 80 % SOC), giving a total of 72 distinct fast-charging strategies |
| across the cohort. Discharging was uniform : 4C constant-current to the |
| discharge cutoff. A 1-minute rest was enforced after reaching 80 % SOC |
| during charging, and a 1-second rest after each discharge. Internal |
| resistance was probed once per cycle by 10 pulses of ±3.6C with a pulse |
| width of 30 or 33 ms. |
|
|
| This protocol is what makes Severson 2019 a strong stress-test for filter |
| benchmarks : the cell-to-cell variation is dominated by *charging policy* |
| rather than ambient conditions, isolating the protocol-driven aging |
| mechanisms that filters are typically asked to compensate for. |
|
|
| ## File inventory (best-effort) |
|
|
| Severson 2019 is distributed as **three** `.mat` files (HDF5 v7.3 format) |
| on the TRI data portal : |
|
|
| | File | Date | Cells | Size (approx.) | |
| |---|---|---|---| |
| | `2017-05-12_batchdata_updated_struct_errorcorrect.mat` | 2017-05-12 | 46 | 2.82 GB | |
| | `2017-06-30_batchdata_updated_struct_errorcorrect.mat` | 2017-06-30 | 48 | 1.80 GB | |
| | `2018-04-12_batchdata_updated_struct_errorcorrect.mat` | 2018-04-12 | 46 | 3.01 GB | |
| | **Total** | | **140 channels → 124 cells after exclusions** | **~7.6 GB** | |
|
|
| A fourth file dated 2019-01-24 is sometimes seen in the same data.matr.io |
| project ; that file belongs to **Attia et al. 2020** |
| ("Closed-loop optimization of fast-charging protocols for batteries with |
| machine learning") and is **not** part of Severson 2019. This Tier 1 |
| mirror covers only the three Severson 2019 batches. |
|
|
| The 16 channels that account for the gap between the 140 raw channels and |
| the published cohort of 124 cells are documented in the upstream Braatz |
| Group `Load Data.ipynb` notebook : five cells in batch 1 did not reach |
| the 80 % capacity threshold (`b1c8`, `b1c10`, `b1c12`, `b1c13`, `b1c22`), |
| five cells in batch 2 were re-assigned to batch 1 because they were |
| continued from the first experimental run (`b2c7`, `b2c8`, `b2c9`, |
| `b2c15`, `b2c16`), and six cells in batch 3 were excluded as noisy |
| channels (`b3c37`, `b3c2`, `b3c23`, `b3c32`, `b3c42`, `b3c43`). The Tier 1 |
| mirror still preserves these channels in the raw `.mat` files ; the Tier 2 |
| canonical Parquet repository will apply the published exclusion mask. |
|
|
| Sizes are rounded community estimates (see BatteryML and the BatteryBits |
| "Comparison of Open Datasets for Lithium-ion Battery Testing" article). |
| Exact bytes will be locked once the actual upload to HuggingFace |
| completes and `manifests/severson_2019_lfp.yaml` is populated with |
| SHA-256 digests. |
|
|
| ## Why "raw mirror" tier |
|
|
| BSEBench follows a **dual-tier** dataset strategy : |
|
|
| - **Tier 1 (this repository)** — the original `.mat` files, preserved |
| byte-for-byte, with SHA-256 digests recorded in our manifest and |
| cross-checked against the original publication's distribution. |
| Use this tier if you need to verify provenance, run independent |
| harmonizations, or audit our adapter's correctness. |
| - **Tier 2** — the BSEBench-canonical Parquet harmonization at |
| [`bsebench-org/severson-2019`](https://huggingface.co/datasets/bsebench-org/severson-2019). |
| Consistent column names, BPX-1.1 sign convention, unified schema across |
| all benchmark datasets. Use this tier for filter benchmarking and most |
| downstream work. |
|
|
| ## Original source |
|
|
| The original Severson 2019 dataset was distributed via |
| [data.matr.io](https://data.matr.io/1/) (the Toyota Research Institute |
| Experimental Data Platform), specifically project |
| [`5c48dd2bc625d700019f3204`](https://data.matr.io/1/projects/5c48dd2bc625d700019f3204). |
| This URL is recorded as **citation and provenance metadata** only. |
|
|
| **The HuggingFace Hub mirror at this repository is the BSEBench |
| single source of truth for fetching.** Adapters in |
| `bsebench-datasets` never hit `data.matr.io` at runtime. This insulates |
| the benchmark from upstream availability changes (URL shifts, registration |
| requirements, bandwidth limits, eventual portal retirement) while |
| preserving the citation chain back to the original publishers. |
|
|
| ## License |
|
|
| The Severson 2019 dataset is distributed under the |
| [Creative Commons Attribution 4.0 International (CC-BY-4.0)](https://creativecommons.org/licenses/by/4.0/) |
| license, consistent with the licensing policy of the `data.matr.io` |
| platform's earlier (pre-2025) datasets per the |
| [TRI Energy & Materials Datasets](https://data.matr.io/) catalog. |
|
|
| Verbatim core grant from the |
| [CC-BY-4.0 legal code](https://creativecommons.org/licenses/by/4.0/legalcode) : |
|
|
| > "Subject to the terms and conditions of this Public License, the |
| > Licensor hereby grants You a worldwide, royalty-free, non-sublicensable, |
| > non-exclusive, irrevocable license to exercise the Licensed Rights in |
| > the Licensed Material to: (1) reproduce and Share the Licensed Material, |
| > in whole or in part; and (2) produce, reproduce, and Share Adapted |
| > Material." |
|
|
| The redistribution rights granted by this license are the legal basis on |
| which BSEBench mirrors the dataset on the HuggingFace Hub. Attribution |
| is given to the original authors via the BibTeX block above and via the |
| manifest's `citation_bibtex` field. Derivative material (the Tier 2 |
| Parquet harmonization at `bsebench-org/severson-2019`) is offered under |
| the same CC-BY-4.0 license, with BSEBench attribution added on top of |
| the original Severson 2019 attribution chain. |
|
|
| Note : the *publication text* of the Nature Energy paper is governed by |
| Springer-Nature's text-and-data-mining terms (CrossRef license type |
| `tdm`, effective 2019-03-25), which is a separate licensing regime from |
| the dataset hosted on data.matr.io. CC-BY-4.0 covers the experimental |
| data only ; do not assume it covers the paper PDF. |
|
|
| ## How to use |
|
|
| ```python |
| from huggingface_hub import snapshot_download |
| |
| local_dir = snapshot_download( |
| "bsebench-org/severson-2019-raw", |
| repo_type="dataset", |
| ) |
| # local_dir contains the three .mat files, SHA-256 verified |
| # against bsebench-datasets/manifests/severson_2019_lfp.yaml |
| ``` |
|
|
| To then read a `.mat` file in Python (the files are HDF5 v7.3, not |
| classic v5, so `scipy.io.loadmat` will not work — use `h5py`) : |
|
|
| ```python |
| import h5py |
| from pathlib import Path |
| |
| p = Path(local_dir) / "2017-05-12_batchdata_updated_struct_errorcorrect.mat" |
| with h5py.File(p, "r") as f: |
| print(list(f.keys())) # ['#refs#', '#subsystem#', 'batch', 'batch_date'] |
| batch = f["batch"] |
| print(list(batch.keys())) # ['Vdlin', 'barcode', 'channel_id', |
| # 'cycle_life', 'cycles', 'policy', |
| # 'policy_readable', 'summary'] |
| ``` |
|
|
| For the BSEBench-harmonized Parquet version that exposes a clean |
| benchmark-ready API, prefer |
| [`bsebench-org/severson-2019`](https://huggingface.co/datasets/bsebench-org/severson-2019). |
|
|
| ## Citation |
|
|
| Cite the **original** Severson 2019 paper (BibTeX above). BSEBench's |
| contribution is hosting and harmonization, not the data itself. |
|
|
| If you also use BSEBench tooling for filter benchmarking, additionally |
| cite : |
|
|
| ```bibtex |
| @misc{bsebench2026, |
| author = {Akir, Oussama and {BSEBench Contributors}}, |
| title = {{BSEBench}: an open-source benchmark for battery |
| state-estimation filters}, |
| year = {2026}, |
| url = {https://bsebench.org}, |
| } |
| ``` |
|
|
| ## Provenance manifest |
|
|
| A machine-readable manifest validating this dataset's metadata against |
| the [`bsebench-dataset-manifest/v1`](https://github.com/bsebench-org/bsebench-specs) |
| Pydantic v2 schema lives at |
| [`bsebench-org/bsebench-datasets/manifests/severson_2019_lfp.yaml`](https://github.com/bsebench-org/bsebench-datasets/tree/main/manifests). |
|
|
| The manifest records, for every `.mat` file in this repository : |
|
|
| - `source.canonical_url` — the data.matr.io project URL |
| - `source.canonical_doi` — the Nature Energy DOI for citation |
| - `source.publication_authors` and `source.publication_year` |
| - per-file `path`, `sha256`, and `size_bytes` |
| - the dataset-wide `license` (SPDX `CC-BY-4.0`) and `redistribution_allowed` |
| flag (true) |
| - the `citation_bibtex` block (verbatim copy of the BibTeX above) |
| - `huggingface_tier1_repo` (= `bsebench-org/severson-2019-raw`) and |
| `huggingface_tier2_repo` (= `bsebench-org/severson-2019`) |
|
|
| The manifest is committed only after the SHA-256 digests are populated |
| from the actual HuggingFace mirror — never with placeholder values. |
|
|
| ## See also |
|
|
| - [Tier 2 canonical Parquet sibling repository](https://huggingface.co/datasets/bsebench-org/severson-2019) |
| - [Original publication (Nature Energy)](https://doi.org/10.1038/s41560-019-0356-8) |
| - [Original data portal (TRI / data.matr.io)](https://data.matr.io/1/projects/5c48dd2bc625d700019f3204) |
| - [Upstream Braatz Group GitHub starter code](https://github.com/rdbraatz/data-driven-prediction-of-battery-cycle-life-before-capacity-degradation) |
| - [BSEBench organization on HuggingFace](https://huggingface.co/bsebench-org) |
| - [BSEBench documentation site](https://bsebench.org) |
|
|
