Master Thesis AI-based Sensorless Edrive Control
Core
Researching AI-based sensorless control architectures for electric drives using neural networks to estimate rotor positions without physical sensors.
Role type
Master Thesis Researcher (AI/Control Engineering)
Builds
Novel AI-based control and estimation algorithms for electric drive systems
Domain
Automotive/Electromobility, Control Engineering, Machine Learning
Deliverable
research
Required skills
control engineering, machine learning, neural networks, Python, MATLAB, electric drive modeling
Preferred skills
autonomous working style, systematic task structuring
Technologies
Python, MATLAB, high-fidelity simulation models
Responsibilities
Analyze state-of-the-art ML approaches for sensorless control, develop novel neural network designs, implement and validate algorithms in simulation, document methodology and present findings
Seniority
Master Thesis (6 months)