README.md

---
license: cc-by-4.0
language:
  - en
size_categories:
  - 100M<n<1B
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-2-canonical
  - parquet
  - bpx-1.1
pretty_name: "Severson 2019 LFP Fastcharge — BSEBench Canonical (Tier 2)"
---

# severson-2019

**Tier 2 BSEBench-canonical** Parquet harmonization of the Severson et al.
2019 commercial LFP fastcharge cycling dataset, derived from the
[Tier 1 raw mirror](https://huggingface.co/datasets/bsebench-org/severson-2019-raw)
of the three original `.mat` files.

This is the version most users want : column names normalized to the
BSEBench `TimeSeriesSchema`, current sign convention aligned to BPX-1.1,
cycles 1-indexed, exclusion mask from the published cohort applied,
partitioned by `cell_id` for parallel reading, and loadable in one line
through the `bsebench-datasets` Python package.

## Status

This is a **placeholder card**. The harmonized Parquet files are not
yet uploaded. Three preconditions must be satisfied before publication :

1. The Tier 1 raw mirror must be uploaded at
   [`bsebench-org/severson-2019-raw`](https://huggingface.co/datasets/bsebench-org/severson-2019-raw)
   with SHA-256 digests committed to
   `bsebench-datasets/manifests/severson_2019_lfp.yaml`.
2. The `bsebench-specs` package must reach v0.2.0 and publish the
   canonical `TimeSeriesSchema` Pydantic v2 model (currently v0.1.0 only
   ships `DatasetManifest`).
3. The harmonization adapter at
   [`bsebench-datasets/src/bsebench_datasets/adapters/severson_2019.py`](https://github.com/bsebench-org/bsebench-datasets/blob/main/src/bsebench_datasets/adapters/severson_2019.py)
   must be implemented (currently a documented stub raising
   `NotImplementedError`) and tested against the Tier 1 mirror with a
   round-trip schema check.

Until step 3 is reached, this card describes the **target schema** that
the upload will conform to, not a published artifact. Schema details
should be considered authoritative ; SHA-256 digests, exact byte sizes,
and Parquet partition counts will be filled in after upload.

## What this will be

The Severson 2019 dataset converted to the **BSEBench canonical
TimeSeriesSchema**, persisted as Parquet with Zstandard compression and
partitioned by `cell_id` for parallel reads :

| Column | Pandas / Arrow type | Description |
|---|---|---|
| `cell_id` | `string` | Stable cell identifier within the dataset (e.g., `b1c0`, `b1c1`, ..., `b3c45`). The Severson cohort uses `b<batch>c<channel>` IDs, where `<batch>` is `1`/`2`/`3` and `<channel>` is the within-batch zero-indexed channel number from the original `.mat` `channel_id` field. |
| `time_s` | `float64` | Seconds elapsed since the first sample of the cycling experiment for that cell (`t = 0` at the first sample). |
| `voltage_V` | `float64` | Terminal voltage, always positive. Range typically 2.0–3.6 V (the cycling cutoffs). |
| `current_A` | `float64` | Cell current under the **BPX-1.1 sign convention** : positive on charge, negative on discharge. |
| `temperature_C` | `float64` | Cell-can surface temperature, in degrees Celsius. |
| `cycle_number` | `int32` | 1-indexed cycle counter. The original Severson `summary.cycle` field is 0-indexed ; the adapter applies a `+1` offset to align with the BSEBench convention used across all benchmark datasets. |
| `step_id` | `string` | Within-cycle step identifier. For Severson 2019, derived from the protocol metadata as `charge`, `rest_after_charge`, `discharge`, or `rest_after_discharge`. |
| `capacity_Ah` | `float64` | Running cumulative capacity (Coulomb counting from Severson's per-cycle `Qc` and `Qd` fields). Optional in the BSEBench schema but populated for this dataset since it is directly derivable. |

Two further BSEBench schema columns (`soc_truth`, `soh_truth`) are
**not provided** for this dataset because Severson 2019 does not
publish a reference SOC trajectory and supplies only per-cycle
discharge-capacity summaries (`summary.QDischarge`, `summary.QCharge`)
rather than a continuous SOH ground truth. Filter benchmarks that
require ground-truth SOC must compute it from `capacity_Ah` themselves
or treat Severson 2019 as an SOC-blind benchmark.

Estimated total size : **~50 GB** uncompressed, **~8 GB** after
Zstandard compression — comparable to the ~7.6 GB total of the three
raw `.mat` files. Final sizes will be locked at upload.

## Mapping from original

The Severson `.mat` v7.3 files store data as a single top-level `batch`
struct with one entry per cell. The BSEBench harmonization performs the
following mapping :

| BSEBench column | Severson source field | Conversion |
|---|---|---|
| `cell_id` | (synthesized) | `f"b{batch_idx}c{channel_idx}"` where `batch_idx ∈ {1,2,3}` matches the file date and `channel_idx` is the zero-indexed position in `batch.channel_id`. |
| `time_s` | `batch.cycles[i].t` | Per-cycle local time arrays are concatenated end-to-end with cumulative offset to produce a monotonically increasing global time axis. Severson stores `t` in seconds. |
| `voltage_V` | `batch.cycles[i].V` | Direct copy. |
| `current_A` | `batch.cycles[i].I` | Sign convention preserved as published (charge-positive). The Severson convention is consistent with BPX-1.1, so no sign flip is applied. See *Sign convention notes* below. |
| `temperature_C` | `batch.cycles[i].T` | Direct copy. Severson logs cell-can surface temperature in °C. |
| `cycle_number` | `batch.summary.cycle` (per cycle) | `+1` offset applied (Severson is 0-indexed, BSEBench is 1-indexed). |
| `step_id` | `batch.policy_readable` + step heuristics | Within a cycle, the policy plus current-sign transitions identify charge / rest / discharge / rest segments. |
| `capacity_Ah` | `batch.cycles[i].Qc`, `batch.cycles[i].Qd` | Cumulative capacity reconstructed from per-cycle charge / discharge throughput. |

Cells excluded from the published 124-cell cohort by Severson and
collaborators are also excluded by this Tier 2 harmonization, matching
the upstream Braatz Group `Load Data.ipynb` exclusion mask :

- Batch 1 : `b1c8`, `b1c10`, `b1c12`, `b1c13`, `b1c22` (did not reach
  80 % capacity threshold).
- Batch 2 : `b2c7`, `b2c8`, `b2c9`, `b2c15`, `b2c16` (re-assigned to
  batch 1, continued from earlier run ; remapped to their batch-1 IDs).
- Batch 3 : `b3c2`, `b3c23`, `b3c32`, `b3c37`, `b3c42`, `b3c43` (noisy
  channels excluded by Severson).

Total : 140 raw channels across 3 files → 124 published cells, exactly
matching the cohort cited in the Severson 2019 paper.

## Sign convention notes

The BSEBench canonical sign convention follows
[BPX 1.1](https://bpxstandard.com/) : **charge = positive current,
discharge = negative current**. Severson's published `.mat` files
appear to use the same convention based on the pattern seen in the
upstream Braatz Group BuildPkl notebooks, where charge capacity (`Qc`)
and discharge capacity (`Qd`) are plotted as separate strictly-positive
quantities aggregated from `I`. The harmonization adapter therefore
applies **no sign flip** to `current_A`.

The exact sign of the `'I'` field in the raw `.mat` data has not been
confirmed by direct inspection of the binary at the time this card was
drafted. The adapter implementation (see `severson_2019.py` docstring)
includes a runtime sanity check that verifies, on the first cycle of
the first cell loaded, that the integral of `I·dt` over the charge
phase produces a positive cumulative `capacity_Ah` matching `Qc`. If
this check fails, the upload is aborted and the convention is
re-evaluated.

## Why "canonical" tier

Tier 2 is the version users should consume for filter benchmarking. It :

- Maps Severson's idiosyncratic struct schema to the standardized
  BSEBench `TimeSeriesSchema` shared with all other BSEBench datasets
  (NASA Randomized Walk 2014, Sandia 2020, Oxford 2017, Empa Aurora 2025,
  ...) so that filter pipelines work cross-dataset without per-dataset
  glue code.
- Harmonizes the sign convention to BPX 1.1 (no-op for Severson since
  it already matches).
- Applies the published exclusion mask, so users do not have to
  re-implement the cell-quality filters from the upstream notebooks.
- Strips analysis-only metadata (`Qdlin`, `Tdlin`, `discharge_dQdV`,
  `Vdlin` interpolation grids) that are not needed for state estimation.
- Ships as Parquet with column-statistics indexing, partitioned by
  `cell_id` so that filter benchmarks can read individual cells in
  ~milliseconds instead of loading the full 8 GB.
- Loads in one line via the `bsebench-datasets` Python package's
  `load_bsebench()` helper.

For provenance, audits, or independent harmonizations, see the
[Tier 1 raw mirror](https://huggingface.co/datasets/bsebench-org/severson-2019-raw).

## Anchor standards

- **Sign convention** : [BPX 1.1](https://bpxstandard.com/) (charge =
  positive, discharge = negative).
- **Time-series schema** : aligned with the
  [LF Energy Battery Data Format (BDF)](https://lfenergy.org/lf-energy-battery-data-alliance-announces-the-battery-data-format-bdf/),
  released December 2025, where applicable.
- **Manifest schema** : `bsebench-dataset-manifest/v1` (Pydantic v2,
  defined in `bsebench-specs`).

## License

[Creative Commons Attribution 4.0 International (CC-BY-4.0)](https://creativecommons.org/licenses/by/4.0/) —
inherited from the original Severson 2019 dataset on the
[TRI Energy & Materials Datasets platform](https://data.matr.io/) (whose
earlier (pre-2025) datasets are distributed under CC-BY-4.0). The
BSEBench-canonical Parquet harmonization is a derivative work of the
original `.mat` files and is offered under the same CC-BY-4.0 license,
with BSEBench attribution added on top of the Severson 2019 attribution.

Verbatim core grant of the underlying license, 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."

## How to use (target API)

```python
# Once shipped (M2.1 milestone)
from bsebench_datasets import load_bsebench

ds = load_bsebench("severson-2019", revision="v1.0")
print(ds.chemistry)                # "LFP"
print(ds.n_cells)                  # 124
print(ds.first_cell_data().head()) # canonical Parquet columns
```

Equivalent pure-pandas / Arrow access for users who do not want the
`bsebench-datasets` package :

```python
import pandas as pd
from huggingface_hub import snapshot_download

local_dir = snapshot_download(
    "bsebench-org/severson-2019",
    repo_type="dataset",
)

# Load one cell's full timeseries
df = pd.read_parquet(f"{local_dir}/cell_id=b1c0")
print(df.dtypes)
# cell_id           string[python]
# time_s                    float64
# voltage_V                 float64
# current_A                 float64    (BPX-1.1 sign)
# temperature_C             float64
# cycle_number                int32
# step_id           string[python]
# capacity_Ah               float64
```

## Citation

```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},
}

@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

This Tier 2 harmonization is derived from
[`bsebench-org/severson-2019-raw`](https://huggingface.co/datasets/bsebench-org/severson-2019-raw)
via [`bsebench-datasets/src/bsebench_datasets/adapters/severson_2019.py`](https://github.com/bsebench-org/bsebench-datasets/blob/main/src/bsebench_datasets/adapters/severson_2019.py).

Once published, the manifest YAML
[`bsebench-datasets/manifests/severson_2019_lfp.yaml`](https://github.com/bsebench-org/bsebench-datasets/tree/main/manifests)
will record :

- the Tier 1 commit SHA whose `.mat` files were the input to harmonization
- the adapter file commit SHA at the time of the Parquet build
- the per-Parquet-partition `sha256` and `size_bytes`
- the Pydantic-validated `bsebench-dataset-manifest/v1` block

These provenance pointers are not yet populated because the upload has
not yet occurred. The card will be updated with concrete SHAs at
publication time.

## See also

- [Tier 1 raw mirror](https://huggingface.co/datasets/bsebench-org/severson-2019-raw)
- [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)
- [Adapter source code](https://github.com/bsebench-org/bsebench-datasets/blob/main/src/bsebench_datasets/adapters/severson_2019.py)
- [BSEBench documentation site](https://bsebench.org)