motulator

Motor drive and grid converter simulator in Python

Documentation · Drive examples · Grid examples · Installation

Simulated sensorless flux-vector control of a 2.2-kW IPMSM drive: speed step, load-torque step, and phase currents

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

pip install motulator

To develop motulator itself, clone the repository as described in the installation guide.

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:

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 and grid examples. New system models and controllers can be developed using the existing ones as templates.

From simulation to the laboratory

Laboratory test bench: a permanent-magnet synchronous machine coupled to a load machine through a torque sensor, with the converter cabinet in the background

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.

Contributing

If you would like to help us develop motulator, see these guidelines first.

Contributors

Thanks go to these wonderful people:

_{Lauri Tiitinen} 💻 🤔 💡 🧑‍🏫	_HannuHar 💻 🐛	_{Marko Hinkkanen} 💻 🤔 💡 🧑‍🏫	_silundbe 💻 💡	_{JoonaKukkonen} 💻 🚇	_jarno-k 🤔 👀 🧑‍🏫	_{angelicaiaderosa} 💻 💡
_{Luca Peretti} 🤔 📣	_{GianmarioPellegrinoPolito} 🔣	_{Simone Ferrari} 🔣	_Jialed0303 🤔	_murgui 🐛	_{Nithin Valiyaveettil Sadanandan} 🐛	_saarela 🐛
_Ushnish 🐛	_{Francesco-Lelli} 💻 💡 🤔	_{Mikko Sarén} 💻 💡 🤔	_{Juho Määttä} 💻 💡 🤔	_rayanmour 💻 💡 🤔 👀 🧑‍🏫	_{Cosimo Bassi} 🚇	_{Junyi Li} 💻 💡 🤔
_{Tim Foißner} 🔣 🤔

This project follows the all-contributors specification. Contributions of any kind welcome!

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.

Metadata

Release files for motulator 0.11.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for motulator 0.11.0
File	Size	Uploaded
motulator-0.11.0.tar.gz	31.2 MB	Oct 13, 2026	Details

Built distribution (wheel)

Table of built distributions (wheels) for motulator 0.11.0
File	Interpreter	ABI	Platform	Reset
motulator-0.11.0-py3-none-any.whl 151.1 kB Oct 13, 2026	Python 3	none	any	Details

Total release size: 31.4 MB

Release files / motulator-0.11.0.tar.gz

Download URL	motulator-0.11.0.tar.gz
Size	31.2 MB
Tags	Source
SHA-256 checksum How to use checksums	`6a206154fd61ea75e2f502c7f7094322ac6fbc8a8ffd1b2c1894f0035f4afb81`
BLAKE2b-256 checksum How to use checksums	`b8d7bdffee8909dfb5269539cc851762bb20364855b3bcd383835f604372adbe`
Upload date	Oct 13, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/7.0.0 CPython/3.12.15`

Release files / motulator-0.11.0-py3-none-any.whl

Download URL	motulator-0.11.0-py3-none-any.whl
Size	151.1 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`06213c308c664ffeac84b2ef6c02e052215dd635c1c0ca6d3232b2d9ba85ecdc`
BLAKE2b-256 checksum How to use checksums	`7a881cd67a7e5a17065d6e24385ebae4124a6fbc812c7b05e817179e73d8dc69`
Upload date	Oct 13, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/7.0.0 CPython/3.12.15`