Master Thesis AI-based Power Electronics Control
Core
Design and implement next-generation closed-loop control algorithms for non-linear AC/DC and DC/DC converters to optimize efficiency and performance in E-Mobility, Robotics, and Data Centers.
Role type
Master Thesis Researcher (Power Electronics Control)
Builds
Simulation models and control strategies for next-generation charger/converter topologies
Domain
Power Electronics / Control Theory / Machine Learning
Deliverable
production ML models | research
Required skills
Control systems (state-space, non-linear, predictive), Simulation tools (MATLAB/Simulink, Python), Power electronics fundamentals
Preferred skills
Model Predictive Control (MPC), Neural Network-based control, Reinforcement Learning (RL)
Technologies
MATLAB/Simulink, Python, PyTorch, PLECS
Responsibilities
Select control concepts, design tailor-made strategies, implement algorithms in simulation, validate and benchmark performance, analyze robustness and real-time suitability, document and present findings
Seniority
Master's level research project