Datasets:

bsebench-org
/

severson-2019

	---
	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)