> ## Documentation Index
> Fetch the complete documentation index at: https://mintlify.com/pybamm-team/PyBaMM/llms.txt
> Use this file to discover all available pages before exploring further.

# Introduction

> PyBaMM is an open-source battery simulation package written in Python for multi-institutional, interdisciplinary research.

PyBaMM (Python Battery Mathematical Modelling) is an open-source battery simulation package written in Python. Its mission is to accelerate battery modelling research by providing open-source tools for multi-institutional, interdisciplinary collaboration.

PyBaMM consists of three main components:

1. **A framework for writing and solving systems of differential equations** — flexible ODE/PDE definitions with multiple spatial discretisation methods and solvers.
2. **A library of battery models and parameters** — ready-to-use physics-based models (SPM, SPMe, DFN, and more) backed by published parameter sets.
3. **Specialized tools for battery simulation** — experiment definitions, result visualization, and batch study utilities.

Together, these components enable flexible model definitions and fast battery simulations, letting you explore the effect of different battery designs and modelling assumptions under a variety of operating scenarios.

## Key features

<CardGroup cols={2}>
  <Card title="Physics-based models" icon="flask">
    Run the Single Particle Model (SPM), Single Particle Model with electrolyte (SPMe), Doyle-Fuller-Newman (DFN), and several other full-order lithium-ion models out of the box.
  </Card>

  <Card title="Solvers" icon="bolt">
    Choose from CasADi-based solvers, SciPy integrators, and an optional JAX-based solver. PyBaMM automatically selects a sensible default for each model.
  </Card>

  <Card title="Parameter sets" icon="database">
    Access a curated library of published parameter sets including Chen2020, Marquis2019, Ecker2015, OKane2022, and others. Swap parameters with a single line of code.
  </Card>

  <Card title="Experiments" icon="list-checks">
    Define realistic cycling protocols in plain English — constant-current discharge, CC/CV charge, rest steps, and multi-cycle sequences via `pybamm.Experiment`.
  </Card>

  <Card title="Plotting" icon="chart-line">
    Visualize any model variable over time or through the electrode thickness. `sim.plot()` produces an interactive plot of the most common outputs.
  </Card>

  <Card title="Batch studies" icon="layer-group">
    Run parameter sweeps and compare results across models, parameter sets, or operating conditions using PyBaMM's simulation and solution APIs.
  </Card>
</CardGroup>

## Get started

<CardGroup cols={2}>
  <Card title="Quickstart" icon="rocket" href="/quickstart">
    Run your first simulation in under five minutes.
  </Card>

  <Card title="Installation" icon="download" href="/installation">
    Install PyBaMM on Linux, macOS, or Windows.
  </Card>
</CardGroup>

## NumFOCUS sponsorship

PyBaMM uses an open governance model and is fiscally sponsored by [NumFOCUS](https://numfocus.org/). Consider making a [tax-deductible donation](https://numfocus.org/donate-for-pybamm) to help the project pay for developer time, professional services, travel, workshops, and other needs.

## Citing PyBaMM

If you use PyBaMM in your work, please cite:

> Sulzer, V., Marquis, S. G., Timms, R., Robinson, M., & Chapman, S. J. (2021). Python Battery Mathematical Modelling (PyBaMM). *Journal of Open Research Software, 9(1)*. [https://doi.org/10.5334/jors.309](https://doi.org/10.5334/jors.309)

To find out which additional papers you should cite based on the models and solvers you use, add the following line to the end of your script:

```python theme={null}
pybamm.print_citations()
```

Passing a filename to `print_citations` writes the BibTeX output to that file instead of the terminal.