Graphite/LNMO BattMo Dataset and Workflow

This repository accompanies the paper "Comprehensive parameter and electrochemical dataset for a 1 Ah graphite/LNMO battery cell for physical modelling as a blueprint for data reporting in battery research" by Schmitt et al.

The repository demonstrates the P2D model calibration workflow described in the paper, starting with low-rate calibration under equilibrium assumptions, a calibration against high-rate data and final validation.

Get Started

1. Clone this repository.
2. Clone BattMo locally.
3. Set BATTMO_DIR to the BattMo root containing startupBattMo.m.
4. Start MATLAB and run the startupBattMo.m script.

Entry Points

After installing and configuring BattMo as described above, the main entry point is to run the full MATLAB-side publication reproduction script (typical duration: 1 - 3 h): runReproduction

Optionally, the components can also be run individually using the following scripts:

• Low-rate calibration only (typical duration: 2 - 10 min): scripts/low-rate-calibration/runEquilibriumCalibration.m
• High-rate calibration only (typical duration: 45 - 180 min): scripts/high-rate-calibration/runHighRateCalibration.m
• Validation plot only (typical duration: 5 - 15 min): scripts/runValidation.m
• Figure export only (typical duration: 10 - 30 min): scripts/exportPublicationFigures.m
• Python-side validation summary only (typical duration: < 1 min; 5 - 15 min with -IncludeBpx): run-validation.ps1

These are rough wall-clock estimates on a typical workstation or laptop. The high-rate calibration dominates runtime and can vary substantially with MATLAB release, CPU, and BattMo setup.

FAIR Data and Interoperability

The data is available at https://doi.org/10.5281/zenodo.18256663 .

This repository includes FAIR-data exports alongside the primary BattMo workflow.

The BattMo JSON files are the canonical model inputs for the published workflow. In particular, parameters/IMP5-70-120-H0B_graphite-lnmo_schmitt-2026_validation.battmo.json is the single-file merged BattMo counterpart to the publication BPX export. The JSON-LD and BPX files are included to support machine readability and interoperability with PyBaMM and BattMo.

To export the BattMo validation reference curves from MATLAB, do

startup
run(fullfile('scripts', 'exportValidationReference.m'));

Then compare BattMo and PyBaMM with

python scripts/compare_battmo_pybamm.py

Some BattMo-specific features cannot be represented exactly in standard BPX:

• the graphite negative-electrode j0(soc) table
• independent volumetric surface area and active-material volume fraction
• cathode OCP boundary behavior outside the first tabulated stoichiometry point Accordingly:
• the graphite j0(soc) data is approximated by a single BPX reaction-rate constant
• BattMo surface-area scaling is folded into exported reaction-rate constants
• the cathode OCP table includes a boundary extrapolation

See also

.\run-validation.ps1 -IncludeBpx

Citation

Citation metadata is in CITATION.cff. The accompanying paper is available at https://arxiv.org/abs/2601.10507.

License

This repository is distributed under the GNU General Public License v3.0 or later. See COPYING.