Open-Source contributions

Open Source Power Electronic Tools
https://github.com/upb-lea/awesome-open-source-power-electronics
Lists open source power electronic tools

FEM Magnetics Toolbox (FEMMT)
https://github.com/upb-lea/FEM_Magnetics_Toolbox
An Open-Source FEM Magnetics Toolbox for Power Electronic Magnetic Components

Transistordatabase (TDB)
https://github.com/upb-lea/transistordatabase
Download Transistordatabase
A unified software engineering tool for managing and evaluating power transistors.

Inkscape Electric Symbols
https://github.com/upb-lea/Inkscape_electric_Symbols
Contains block diagrams and symbols. For usage with Inkscape (open source vector drawing program), runs on Linux, Mac, Windows.

Gym Electric Motor (GEM)
https://github.com/upb-lea/gym-electric-motor
A Python-based toolbox for the simulation of different electric motor incl. power electronic converters and mechanical loads. A highly flexible user interface allows to simulate a wide variety of operation scenarios such as in automation or traction applications. The toolbox is built upon the OpenAI Gym interface definitions and, therefore, allows flexible coupling with arbitrary control techniques. In particular, the investigation of data-driven reinforcement learning approaches is highlighted.

OpenModelica Microgrid Gym (OMG)
https://github.com/upb-lea/openmodelica-microgrid-gym
A Python-based package for the simulation and control optimization of microgrids based on energy conversion by power electronic converters.
The main characteristics of the toolbox are the plug-and-play grid design and simulation in OpenModelica as well as the ready-to-go approach of intuitive reinforcement learning (RL) approaches through a Python interface. Moreover, the toolbox allows testing and validation of other arbitrary approaches such as linear feedback or model predictive control.

Deep Motor Temperature Estimation
https://github.com/upb-lea/deep-pmsm
Supervised machine learning pipeline based on Keras/Tensorflow to estimate important motor temperatures of a permanent magnet synchronous motors using only standard motor control measurement signals under real-time conditions. In particular, deep recurrent and convolutional networks are considered for the investigation. Based upon real laboratory test bench measurements.

LaTeX Thesis template
https://github.com/upb-lea/thesis_latex_template
This is a latex document template for LEA students, writing a project report or a thesis.