Master Thesis Robust Identification of Compositional Electrical Drive Models - Identifiability, Sensitivity & Excitation Analysis

Master Thesis Robust Identification of Compositional Electrical Drive Models - Identifiability, Sensitivity & Excitation Analysis Requirement for this thesis is the enrollment at university. Please attach your CV, transcript of records, examination regulations and if indicated a valid work and residence permit.

• During your thesis, you delve into physics-based models of electric drives and our Python component library while simultaneously reviewing current literature on robust system identification and the design of experiments.
• Furthermore, you develop innovative robustness diagnostics for our existing identification pipeline - considering parameter identifiability, sensitivity, and convergence behavior - and implement as well as quantify appropriate countermeasures.
• In Addition, you analyze the excitation content of given datasets, evaluate relevant criteria, and link these insights to the achievable identification quality.
• You comprehensively evaluate the approach you have developed using a practical benchmark use case.
• Moreover, you document as well as present your research findings clearly and understandably.
• Lastly, you extend the approach to address partially observable effects resulting from states that cannot be measured directly, such as temperatures.

• Education: Master studies in the field of in Cybernetics, Engineering, Mathematics, Computer Science, or comparable
• Experience and Knowledge: basic knowledge of dynamic systems and differential equations; proficiency in Python programming; understanding of the physics of electrical machines; optional: experience with MATLAB/Simulink for interacting with legacy simulation models; optional: knowledge of machine learning and automatic differentiation frameworks (JAX or PyTorch)
• Personality and Working Practice: you work independently and systematically on complex issues and possess strong analytical skills, enabling you to accurately grasp and solve problems
• Work Routine: office attendance required
• Languages: very good in English