Our Fo­cus Are­as

Pow­er Elec­tro­nics

• Fast-switching inverters
• Converter optimization
• Control and modulation
techniques
• Application fields:
• Automotive
• Industry
• Datacenters

Mehr erfahren

Ma­gne­tic Com­ponents

• Measurement and modelling of
soft-magnetic materials
• Investigation of innovative
design concepts
• Implementation & testing of
prototypes

Mehr erfahren

In­ver­ter-Do­mi­na­ted Grids

• Future grid forming inverters
• Model predictive control
• Reinforcement learning control

Mehr erfahren

Drive Con­trol

• Data and model based optimal
control
• Systemidentification
• Real-time implementation and
validation

Mehr erfahren

Pow­er Elec­tro­nics

Ne­Mo.bil

• Developing a conductive inter-vehicle charging systems for moving platoons of autonomous electric vehicles used in public transportation.
• Analysing bidirectional energy sharing among vehicles based on a decentralized state-of-charge dependent droop control system for conductive AC charging.

Mehr erfahren

Cas­ca­ded Con­ver­ters for Hy­dro­gen Elec­tro­ly­sis

Advantages of Cascaded
Converters
• Interchangeable identical modules
• No 50 Hz transformer
• Reduction in size and cost
Research Focus Areas
• Design a 22 kW LLC converter
• Efficiency optimization
• Variable output power
• Real-time control

Mehr erfahren

Ga­Ni­us – Low EMI Three-Pha­se PFC

• Characterization of unidirectional and bidirectional GaN switches
• Design and simulation of novel PFC rectifier topologies
• Development and implementation of embedded digital control
• Implementation, testing, and performance evaluation of two 11 kW prototypes

Mehr erfahren

Ca­pa­ci­ti­ve LLC

• Development and optimization of
an IGBT-based LLC converter
• Optimized synchronous rectification
• Mathematical modeling of the transfer characteristics
• Bidirectional ZCS LLC converter

Mehr erfahren

Open­Au­to­Mo­LE

Open-source software toolkit for automated,
modular modeling, simulation, and design of
power electronic converters
• Modeling of individual power electronic
components
• Efficient multi-objective optimization of the
overall converter system to achieve high
efficiency and power

Mehr erfahren

Ma­g­ne­tic Com­­ponents

Ma­gne­tic Com­ponents in MHz Ran­ge

• Measurement methods in
the MHz range
• Modeling of inductance
and core losses
• Loss-optimized magnetic
component designs

So­lid-State Trans­for­mers

What are Solid-State Transformers?
• Advanced transformer technology for modern medium-voltage systems
• Flexible integration of renewable energy and smart-grid applications
• Compact and resource-efficient power
• Multi-objective transformer optimization
• Geometry-agnostic core loss models
• Measurements in medium-voltage
test bench

Pla­nar Ma­gne­tics

Why PCB Planar Magnetic Components?
• Planar magnetics are especially suited for
GaN-based converters with high power density
• Matrix configurations allows flux cancellation
• PCB windings allow automated fabrication

• Optimization of winding
and via arrangement
• Designs with reduced
parasitic capacitance
• 3D modelling conce

In­­­ver­­ter-Do­­mi­na­ted Grids

Mi­cro­grid La­bo­ra­to­ry

• Control and management of
electrical power grids
• Hybrid grids
• AC–DC systems
• Solid-state transformers
• Grid standards
• Inverter control
• Optimal control
• Artificial intelligence
• Grid stability
• Energy management
• Hardware testing
• Hardware fault handling and
mitigation

Mehr erfahren

Drive Con­trol

LEA-AI

• Implementing real-time reinforcement-learning controllers
• Designing reward functions
• Enabling safe, data-efficient learning
• Transferring agents to new systems
• Controlling partially observable systems
• Applying RL to electric drives and microgrids
• Funded by BMBF through the VIP+ program

Mehr erfahren

Pu­bli­ka­ti­o­nen

Optimal Control of Voltage-Forming Grid Inverters by Model Predictive Control and Reinforcement Learning

D. Weber, D. Schmies, J.H. Lange, M. Schenke, O. Wallscheid, IEEE Access 14 (2026) 38517–38535.

DOI

Reinforcement Learning-Based Control of Voltage-Forming Grid Inverters With Arbitrary Loads

D. Weber, J. Lange, O. Wallscheid, IEEE Journal of Emerging and Selected Topics in Industrial Electronics (2026) 1–12.

DOI

Reinforcement Learning: A Comprehensive Open-Source Course

A.H.A. Abdelwanis, B. Haucke-Korber, D. Jakobeit, W. Kirchgässner, M. Meyer, M. Schenke, H. Vater, O. Wallscheid, D. Weber, Journal of Open Source Education 9 (2026).

DOI

Safe Reinforcement Learning Direct Torque Control for Continuous Control Set Permanent Magnet Synchronous Motor Drives

M. Schenke, B. Haucke-Korber, O. Wallscheid, IEEE Access (2026) 1–1.

DOI

Pareto Optimal DC-Link Capacitor Selection

N. Förster, S. Schachten, O. Wallscheid, J. Kucka, in: 2026 International Power Electronics Conference (IPEC-Nagasaki 2026 - ECCE Asia), IEEE, 2026.

DOI

Alle Publikationen anzeigen

Leistungselektronik und Elektrische Antriebssysteme (LEA)

Lesen Sie mehr über uns:

Laborausstattung