gym-electric-motor (GEM)

gym-electric-motor (GEM): A Python toolbox for the simulation of electric drive systems - Published in JOSS (2021)

https://github.com/upb-lea/gym-electric-motor

Science Score: 98.0%

This score indicates how likely this project is to be science-related based on various indicators:

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CITATION.cff file
✓
codemeta.json file
Found codemeta.json file
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.zenodo.json file
Found .zenodo.json file
✓
DOI references
Found 14 DOI reference(s) in README and JOSS metadata
✓
Academic publication links
Links to: arxiv.org, ieee.org, joss.theoj.org, zenodo.org
✓
Committers with academic emails
4 of 21 committers (19.0%) from academic institutions
✓
Institutional organization owner
Organization upb-lea has institutional domain (ei.uni-paderborn.de)
✓
JOSS paper metadata
Published in Journal of Open Source Software

Keywords

benchmark converters electric-drive electrical-engineering gym-environment machinelearning motor-models openai openai-gym openai-gym-environments pmsm reinforcement-learning

Scientific Fields

Mathematics Computer Science - 84% confidence

Last synced: 6 months ago · JSON representation

Repository

Gym Electric Motor (GEM): An OpenAI Gym Environment for Electric Motors

Basic Info

Host: GitHub
Owner: upb-lea
License: mit
Language: Python
Default Branch: master
Homepage: https://upb-lea.github.io/gym-electric-motor/
Size: 33.1 MB

Statistics

Stars: 364
Watchers: 22
Forks: 73
Open Issues: 34
Releases: 10

Topics

benchmark converters electric-drive electrical-engineering gym-environment machinelearning motor-models openai openai-gym openai-gym-environments pmsm reinforcement-learning

Created over 6 years ago · Last pushed 6 months ago

Metadata Files

Readme Changelog Contributing License Code of conduct

Gym Electric Motor

Overview

The gym-electric-motor (GEM) package is a Python toolbox for the simulation and control of various electric motors. It is built upon Faram Gymnasium Environments, and, therefore, can be used for both, classical control simulation and reinforcement learning experiments. It allows you to construct a typical drive train with the usual building blocks, i.e., supply voltages, converters, electric motors and load models, and obtain not only a closed-loop simulation of this physical structure, but also a rich interface for plugging in any decision making algorithm, from linear feedback control to Deep Deterministic Policy Gradient agents. In addition, an automated framework for classical control structures based on PI controllers is provided.

Getting Started

An easy way to get started with GEM is by playing around with the following interactive notebooks in Google Colaboratory. Most important features of GEM as well as application demonstrations are showcased, and give a kickstart for engineers in industry and academia.

There is a list of standalone example scripts as well for minimalistic demonstrations.

A basic routine is as simple as: ```py import gymelectricmotor as gem

if name == 'main': env = gem.make("Finite-CC-PMSM-v0") # instantiate a discretely controlled PMSM env.reset() for _ in range(10000): (states, references), rewards, done, _ =\ env.step(env.action_space.sample()) # pick random control actions if done: (states, references), _ = env.reset() env.close() ```

Installation

Install gym-electric-motor from PyPI (recommended):

pip install gym-electric-motor

Install from Github source:

``` git clone git@github.com:upb-lea/gym-electric-motor.git cd gym-electric-motor

Then either

python setup.py install

or alternatively

pip install -e . ```

Building Blocks

A GEM environment consists of following building blocks: - Physical structure: - Voltage supply - Converter - Electric motor - Load model - Utility functions for reference generation, reward calculation and visualization

Information Flow in a GEM Environment

Among various DC-motor models, the following AC motors - together with their power electronic counterparts - are available: - Permanent magnet synchronous motor (PMSM) - Synchronous reluctance motor (SynRM) - Externally exited synchronous motor (EESM) - Squirrel cage induction motor (SCIM) - Doubly-fed induction motor (DFIM)

The converters can be driven by means of a duty cycle (continuous control set) or switching commands (finite control set).

Citation

A white paper for the general toolbox in the context of drive simulation and control prototyping can be found in the Journal of Open Sorce Software (JOSS). Please use the following BibTeX entry for citing it: ``` @article{Balakrishna2021, doi = {10.21105/joss.02498}, url = {https://doi.org/10.21105/joss.02498}, year = {2021}, publisher = {The Open Journal}, volume = {6}, number = {58}, pages = {2498}, author = {Praneeth {Balakrishna} and Gerrit {Book} and Wilhelm {Kirchgässner} and Maximilian {Schenke} and Arne {Traue} and Oliver {Wallscheid}}, title = {gym-electric-motor (GEM): A Python toolbox for the simulation of electric drive systems}, journal = {Journal of Open Source Software} }

```

A white paper for the utilization of this framework within reinforcement learning is available at IEEE-Xplore (preprint: arxiv.org/abs/1910.09434). Please use the following BibTeX entry for citing it: @article{9241851, author={Traue, Arne and Book, Gerrit and Kirchgässner, Wilhelm and Wallscheid, Oliver}, journal={IEEE Transactions on Neural Networks and Learning Systems}, title={Toward a Reinforcement Learning Environment Toolbox for Intelligent Electric Motor Control}, year={2022}, volume={33}, number={3}, pages={919-928}, doi={10.1109/TNNLS.2020.3029573}}

A white paper for the classical control approaches of gym-electric-motor control is available at IEEE-Xplore. Please use the following BibTeX entry for citing it: @INPROCEEDINGS{10239044, author={Book, Felix and Traue, Arne and Schenke, Maximilian and Haucke-Korber, Barnabas and Wallscheid, Oliver}, booktitle={2023 IEEE International Electric Machines & Drives Conference (IEMDC)}, title={Gym-Electric-Motor (GEM) Control: An Automated Open-Source Controller Design Suite for Drives}, year={2023}, volume={}, number={}, pages={1-7}, doi={10.1109/IEMDC55163.2023.10239044}}

Running Unit Tests with Pytest

To run the unit tests ''pytest'' is required. All tests can be found in the ''tests'' folder. Execute pytest in the project's root folder: ```

pytest or with test coverage: pytest --cov=./ ``` All tests shall pass.

Owner

Name: Paderborn University - LEA
Login: upb-lea
Kind: organization
Location: Paderborn, Germany

Website: https://ei.uni-paderborn.de/en/lea/
Repositories: 29
Profile: https://github.com/upb-lea

Department of power electronics and electrical drives

JOSS Publication

gym-electric-motor (GEM): A Python toolbox for the simulation of electric drive systems

Published

February 07, 2021

DOI

10.21105/joss.02498

Volume 6, Issue 58, Page 2498

Authors

Praneeth Balakrishna
Department of Power Electronics and Electrical Drives, Paderborn University, Germany

Gerrit Book
Department of Power Electronics and Electrical Drives, Paderborn University, Germany

Wilhelm Kirchgässner

Department of Power Electronics and Electrical Drives, Paderborn University, Germany

Maximilian Schenke

Department of Power Electronics and Electrical Drives, Paderborn University, Germany

Arne Traue
Department of Power Electronics and Electrical Drives, Paderborn University, Germany

Oliver Wallscheid

Department of Power Electronics and Electrical Drives, Paderborn University, Germany

Editor

Kevin M. Moerman

GitHub Events

Total

Create event: 15
Release event: 1
Issues event: 21
Watch event: 60
Delete event: 6
Member event: 3
Issue comment event: 11
Push event: 121
Pull request review comment event: 20
Pull request review event: 23
Pull request event: 26
Fork event: 13

Last Year

Create event: 15
Release event: 1
Issues event: 21
Watch event: 60
Delete event: 6
Member event: 3
Issue comment event: 11
Push event: 125
Pull request review comment event: 20
Pull request review event: 23
Pull request event: 26
Fork event: 13

Committers

Last synced: 7 months ago

All Time

Total Commits: 890
Total Committers: 21
Avg Commits per committer: 42.381
Development Distribution Score (DDS): 0.707

Past Year

Commits: 76
Committers: 6
Avg Commits per committer: 12.667
Development Distribution Score (DDS): 0.553

Top Committers

Name	Email	Commits
Arne	a**e@g**e	261
wkirgsn	w**r@g**e	109
Felix Book	6****8	96
Maximilian Schenke	m**e@m**e	75
GitPascalP	p**6@g**m	74
Darius	d**t@w**e	65
Stefan Arndt	s**t@m**e	38
S.A	8****t	34
wallscheid	5****d	34
RohithCharanD	r**0@o**m	28
Praneeth Balakrishna	b**h@g**m	24
KoehlerM173	k**s@o**e	22
HauckeBa	b**r@i**g	15
Maximilian Schenke	m****e	6
Marvin Meyer	2****r	2
Stefan Heid	s**d@w**e	2
Deployment Bot (from Travis CI)	d**y@t**g	1
Joni Airaksinen	a**o@g**m	1
Pramod_Mahajan	p**m@m**e	1
Gerrit Book	g**k@m**e	1
unknown	r**5@g**m	1

Committer Domains (Top 20 + Academic)

mail.uni-paderborn.de: 3 gmx.de: 2 mail.upb.de: 1 travis-ci.org: 1 ieee.org: 1 outlook.de: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time

Total issues: 144
Total pull requests: 150
Average time to close issues: 3 months
Average time to close pull requests: 10 days
Total issue authors: 32
Total pull request authors: 21
Average comments per issue: 2.27
Average comments per pull request: 0.96
Merged pull requests: 107
Bot issues: 0
Bot pull requests: 0

Past Year

Issues: 16
Pull requests: 28
Average time to close issues: 3 months
Average time to close pull requests: 11 days
Issue authors: 4
Pull request authors: 6
Average comments per issue: 0.19
Average comments per pull request: 0.11
Merged pull requests: 13
Bot issues: 0
Bot pull requests: 0

View more stats

Top Authors

Issue Authors

wallscheid (21)
wkirgsn (18)
atra94 (17)
XyDrKRulof (16)
bhk11 (16)
max-schenke (13)
GitPascalP (10)
stheid (3)
vapemaster-kz (2)
jmailloux (2)
soumava11 (2)
Priyadharshan2001 (2)
fbook98 (2)
KoehlerM173 (2)
jose-otero-rodriguez (1)

Pull Request Authors

atra94 (42)
max-schenke (19)
XyDrKRulof (16)
fbook98 (13)
bhk11 (9)
devandt (9)
wkirgsn (8)
ranil345 (6)
annava1 (6)
manjeetjha070 (4)
RohithCharanD (3)
praneeth-b (2)
MarvinMeyer (2)
stheid (2)
wallscheid (2)

Top Labels

Issue Labels

enhancement (27) bug (13) documentation (3) agenda/meeting (3)

Pull Request Labels

Packages

Total packages: 1
Total downloads:
- pypi 177 last-month

Total dependent packages: 0
Total dependent repositories: 1
Total versions: 15
Total maintainers: 2

pypi.org: gym-electric-motor

A Farama Gymnasium environment for electric motor control.

Homepage: https://github.com/upb-lea/gym-electric-motor
Documentation: https://gym-electric-motor.readthedocs.io/
License: MIT License
Latest release: 3.0.2
published over 1 year ago

Versions: 15
Dependent Packages: 0
Dependent Repositories: 1
Downloads: 177 Last month

Rankings

Stargazers count: 4.2%

Forks count: 5.5%

Dependent packages count: 7.3%

Average: 12.2%

Downloads: 21.7%

Dependent repos count: 22.1%

Maintainers (2)

wkirgsn bhk

Last synced: 6 months ago

Dependencies

.github/workflows/build_and_test.yml actions

actions/checkout v3 composite
actions/setup-python v4 composite
ad-m/github-push-action master composite
ammaraskar/sphinx-action master composite

.github/workflows/pypi-publish.yml actions

actions/checkout v2 composite
actions/setup-python v2 composite
pypa/gh-action-pypi-publish 27b31702a0e7fc50959f5ad993c78deac1bdfc29 composite

requirements.txt pypi

gym <0.24.0,>=0.15.4
matplotlib >=3.1.2
numpy >=1.16.4
pytest >=5.2.2
pytest-cov *
scipy >=1.4.1

setup.py pypi

gym-electric-motor (GEM)

Science Score: 98.0%

Keywords

Scientific Fields

Repository

Basic Info

Statistics

Topics

Metadata Files

README.md

Gym Electric Motor

Overview

Getting Started

Installation

Then either

or alternatively

Building Blocks

Information Flow in a GEM Environment

Citation

Running Unit Tests with Pytest

Owner

JOSS Publication

gym-electric-motor (GEM): A Python toolbox for the simulation of electric drive systems

Authors

Editor

Tags

GitHub Events

Total

Last Year

Committers

All Time

Past Year

Top Committers

Committer Domains (Top 20 + Academic)

Issues and Pull Requests

All Time

Past Year

Top Authors

Issue Authors

Pull Request Authors

Top Labels

Issue Labels

Pull Request Labels

Packages

pypi.org: gym-electric-motor

Rankings

Maintainers (2)

Dependencies