Metadata-Version: 2.5
Name: motulator
Version: 0.18.0
Summary: Motor Drive and Grid Converter Simulator in Python
Project-URL: Homepage, https://github.com/Aalto-Electric-Drives/motulator
Project-URL: Documentation, https://Aalto-Electric-Drives.github.io/motulator/
Author-email: Marko Hinkkanen <marko.hinkkanen@aalto.fi>
License-Expression: MIT
License-File: LICENSE
Keywords: control,converter,electric,grid,inverter,machine,motor,power,simulation
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Requires-Python: >=3.12
Requires-Dist: matplotlib
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: tqdm
Provides-Extra: dev
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Description-Content-Type: text/markdown

# motulator

**Motor drive and grid converter simulator in Python**

[![PyPI version](https://img.shields.io/pypi/v/motulator.svg)](https://pypi.org/project/motulator/)
[![Python versions](https://img.shields.io/badge/python-3.12%2B-blue.svg)](https://pypi.org/project/motulator/)
[![Build Status](https://github.com/Aalto-Electric-Drives/motulator/actions/workflows/update_gh-pages.yml/badge.svg)](https://github.com/Aalto-Electric-Drives/motulator/actions/workflows/update_gh-pages.yml)
[![License](https://img.shields.io/github/license/Aalto-Electric-Drives/motulator)](https://github.com/Aalto-Electric-Drives/motulator/blob/main/LICENSE)
[![DOI](https://zenodo.org/badge/377399301.svg)](https://zenodo.org/doi/10.5281/zenodo.10223090)

**[Documentation](https://aalto-electric-drives.github.io/motulator/)** ·
**[Drive examples](https://aalto-electric-drives.github.io/motulator/drive_examples/index.html)** ·
**[Grid examples](https://aalto-electric-drives.github.io/motulator/grid_examples/index.html)** ·
**[Installation](https://aalto-electric-drives.github.io/motulator/installation.html)**

<picture>
  <source media="(prefers-color-scheme: dark)" srcset=".github/assets/hero-dark.svg">
  <img src=".github/assets/hero-light.svg" alt="Simulated sensorless flux-vector control of a 2.2-kW IPMSM drive: speed step, load-torque step, and phase currents" width="100%">
</picture>

*motulator* provides simulation models and control algorithms for electric machine drives and grid converter systems. The system models are simulated in the continuous-time domain, while the control algorithms run in discrete time, as they would in a real converter.

## Features

- **Machine models:** induction machines, synchronous reluctance machines, and permanent-magnet synchronous machines, including magnetic saturation and two-mass mechanics
- **Grid converter models:** L and LCL filters, inductive-resistive grids, and DC-bus dynamics
- **Drive control:** V/Hz control, current-vector and flux-vector control, sensorless observers, and signal injection
- **Grid converter control:** grid-following and grid-forming control, including disturbance-observer-based and power-synchronization methods
- **Ready-to-run examples** as Python scripts and Jupyter notebooks, including neural-network-based flux maps learned from measured data

## Installation

Install the package from PyPI in a [virtual environment](https://packaging.python.org/en/latest/guides/installing-using-pip-and-virtual-environments/). On Linux and macOS:

```bash
python3 -m venv .venv
source .venv/bin/activate
pip install motulator
```

On Windows, the environment is created and activated with `py -m venv .venv` and `.venv\Scripts\activate`.

For development, clone the repository and install the package with `pip install -e ".[dev]"`, as described in the [installation guide](https://aalto-electric-drives.github.io/motulator/installation.html).

## Quick start

A complete simulation takes about 20 lines. This example runs sensorless flux-vector control of a 2.2-kW interior permanent-magnet synchronous machine drive:

```python
import motulator.drive.control.sm as control
from motulator.drive import model, utils

# Continuous-time system model: 2.2-kW IPMSM, mechanics, and converter
par = model.SynchronousMachinePars(n_p=3, R_s=3.6, L_d=0.036, L_q=0.051, psi_f=0.545)
mdl = model.Drive(
    model.SynchronousMachine(par),
    model.MechanicalSystem(J=0.015),
    model.VoltageSourceConverter(u_dc=540),
)

# Discrete-time control system: sensorless flux-vector control
cfg = control.FluxVectorControllerCfg(i_s_max=6.5, sensorless=True)
ctrl = control.VectorControlSystem(
    control.FluxVectorController(par, cfg), control.SpeedController(J=0.015, alpha_s=25)
)

# Speed reference and load torque
ctrl.set_speed_ref(lambda t: (t > 0.1) * 50)  # rad/s
mdl.mechanics.set_external_load_torque(lambda t: (t > 0.7) * 10)  # Nm

res = model.Simulation(mdl, ctrl).simulate(t_stop=1.2)
utils.plot(res)
```

To go further, start from the [drive examples](https://aalto-electric-drives.github.io/motulator/drive_examples/index.html) and [grid examples](https://aalto-electric-drives.github.io/motulator/grid_examples/index.html). New system models and controllers can be developed using the existing ones as templates.

## From simulation to the laboratory

<img src=".github/assets/testbench.jpg" alt="Laboratory test bench: a permanent-magnet synchronous machine coupled to a load machine through a torque sensor, with the converter cabinet in the background" width="360" align="right">

Almost all control methods in the examples have also been implemented and tested on laboratory test benches at Aalto University, such as the one shown here. The simulation models aim to capture the dynamics that matter for control design.

<br clear="right">

## Related packages

The following packages extend *motulator*, each maintained in its own repository:

- [motulator-export](https://github.com/Aalto-Electric-Drives/motulator-export): export of drive and grid converter systems to PLECS and Simulink, with the control algorithms ported to C
- [motulator-gradnet](https://github.com/Aalto-Electric-Drives/motulator-gradnet): training of gradient-network magnetic models of synchronous machines from measured or finite-element data
- [motulator-impedance](https://github.com/Aalto-Electric-Drives/motulator-impedance): mechanical impedance of machine drives and output admittance of grid converters, measured by frequency sweeps
- [motulator-multiphase](https://github.com/Aalto-Electric-Drives/motulator-multiphase): multi-three-phase machine drives based on the decoupled multi-stator transformation

See the [related packages](https://aalto-electric-drives.github.io/motulator/related_packages.html) page for the tested releases and for listing a package.

## Contributors

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      <td align="center" valign="top" width="14.28%"><a href="https://github.com/lauritapio"><img src="https://avatars.githubusercontent.com/u/85596019?v=4?s=50" width="50px;" alt="Lauri Tiitinen"/><br /><sub><b>Lauri Tiitinen</b></sub></a><br /><a href="https://github.com/Aalto-Electric-Drives/motulator/commits?author=lauritapio" title="Code">💻</a> <a href="#ideas-lauritapio" title="Ideas, Planning, & Feedback">🤔</a> <a href="#example-lauritapio" title="Examples">💡</a> <a href="#mentoring-lauritapio" title="Mentoring">🧑‍🏫</a></td>
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      <td align="center" valign="top" width="14.28%"><a href="https://research.aalto.fi/en/persons/marko-hinkkanen"><img src="https://avatars.githubusercontent.com/u/76600872?v=4?s=50" width="50px;" alt="Marko Hinkkanen"/><br /><sub><b>Marko Hinkkanen</b></sub></a><br /><a href="https://github.com/Aalto-Electric-Drives/motulator/commits?author=mhinkkan" title="Code">💻</a> <a href="#ideas-mhinkkan" title="Ideas, Planning, & Feedback">🤔</a> <a href="#example-mhinkkan" title="Examples">💡</a> <a href="#mentoring-mhinkkan" title="Mentoring">🧑‍🏫</a></td>
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## Acknowledgment

This project has been sponsored by ABB Oy and by the Research Council of Finland *Centre of Excellence in High-Speed Electromechanical Energy Conversion Systems*. The example control methods included in this repository are based on published algorithms (available in textbooks and scientific articles). They do not present any proprietary control software.
