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Thesis Supervision

You are interested in studies or thesis in the field of powertrain technology, in particular mechatronic systems? Don't hesitate to contact us!

Bachelor or Master

Our scientific research assistants are continuously supervising Bachelor's and Master's thesis. Focus of these theses is the examination of mechatronic components and control strategies in the areas of mobile propulsion technology and modern powertrains. Also project thesis might be supervised in cases of high scientific relevance.

English or German

Theses can be written in German or English language after clarification with the supervising research assistant. If you are interested, please contact us directly to arrange an initial interview appointment with the respective supervisor.

Apply

If you want to apply for an open position or perhaps even have your own specific idea for a research topic, we appreciate if you register with a CV and an overview of your current grades. Then we will initiate a face-to-face meeting to discuss the next steps with you and answer any questions you may have.

Showing 1 - 17 of 17 Results

  • Paper Title
    Type of Paper
    Subject Area
    WEB
    PDF
  • A Novel Framework for Drivable Area Classification with Enhanced Environmental Sensing in Critical Driving Scenarios
    Contact:
    Bachelor Thesis Master Thesis
    F6;F1;F4
    [422320]
     
    Link to PDF
  • Literature Review on Hydrogen Combustion Engine Control Strategies
    Bachelor Thesis
    F4
    [422320]
     
    Link to PDF
  • Evaluation of production costs and recyclability of automotive traction electric motors
    Bachelor Thesis Master Thesis Project Work
    F6;F8;F1;F4;F5.1
    [422320]
     
    Link to PDF
  • Untersuchung der Produktionskosten und der Wiederverwertbarkeit von Elektromotoren im Automobilbereich
    Bachelor Thesis Master Thesis Project Work
    F6;F8;F1;F4;F5.1
    [422320]
     
    Link to PDF
  • AI Function Development in Model-Based Systems Engineering
    Bachelor Thesis Master Thesis
    F6;F4
    [422320]
     
    Link to PDF
  • Automated Machine Learning for Control Oriented Model Identification
    Bachelor Thesis Master Thesis
    F6;F1;F4
    [422320]
     
    Link to PDF
  • Hochfrequenzmodellierung elektrischer Traktionsantriebe zur Simulation parasitärer Gleichtaktströme
    Bachelor Thesis
    F6;F4
    [422320]
    Link to Webpage
    Link to PDF
  • Konzeptstudie für einen fremderregten Synchronantrieb mit induktiver Übertragung des Erregerstroms
    Bachelor Thesis Master Thesis
    F6;F4
    [422320]
    Link to Webpage
    Link to PDF
  • Reinforcement Learning basierte Betriebsstrategien mobiler Schnellladeroboter
    Bachelor Thesis Master Thesis
    F6;F1;F4
    [422320]
    Link to Webpage
    Link to PDF
  • Reinforcement Learning based operating strategy of mobile fast charging robot
    Bachelor Thesis Master Thesis
    F6;F1;F4
    [422320]
    Link to Webpage
    Link to PDF
  • Automatisierte Hyperparameter-Identifikation eines nichtlinearen modellprädiktiven Reglers
    Bachelor Thesis Master Thesis
    F4
    [422320]
    Link to Webpage
    Link to PDF
  • Modellierung mit maschinellem Lernen unter Verwendung synthetischer Wasserstoffmotordaten
    Bachelor Thesis Master Thesis
    F4
    [422320]
    Link to Webpage
    Link to PDF
  • Automated Hyperparameter Identification of a Nonlinear Model Predictive Controller
    Bachelor Thesis Master Thesis
    F4
    [422320]
    Link to Webpage
    Link to PDF
  • Experimentally Applied Reinforcement Learning for Low-Temperature Combustion Control
    Bachelor Thesis Master Thesis
    F4
    [422320]
    Link to Webpage
    Link to PDF
  • Stator Phase Voltage Estimation for a Dual Three-Phase Machine Drive System
    Bachelor Thesis Master Thesis
    F6;F1;F4
    [422320]
    Link to Webpage
    Link to PDF
  • Optimization of Field Weakening Control and Overmodulation Techniques for Dual Three-Phase PMSMs
    Bachelor Thesis Master Thesis
    F6;F1;F4
    [422320]
    Link to Webpage
    Link to PDF
  • Development of a machine learning-based method for the detection of anomalies in test bench systems
    Bachelor Thesis Master Thesis
    F6;F1;F4
    [422320]
    Link to Webpage
    Link to PDF