Michael Theiler

Development and validation of data-driven methods for fault detection, diagnosis, anomaly detection, and condition monitoring using PCA, Autoencoders, and XAI. Signal processing and analysis of multivariate sensor data with MATLAB and Python. Design and execution of battery safety test campaigns and test benches. Collaborative R&D projects with industry partners, acquisition of third-party funding, scientific publications, and supervision of student theses.

Optimization of state and parameter estimation algorithms for lithium-ion batteries based on Kalman filters

• Research on state-of-charge estimation and fault detection using LSTM-based methods • Development and evaluation of machine-learning methods using experimental battery data • Teaching Assistant: Signal and Systems

• Design and setup of experimental aging tests for lithium-ion batteries • Analysis and interpretation of measurement data • Execution, monitoring, and evaluation of battery aging experiments

Modeling of permanent-magnet DC motors in MATLAB/Simulink, including armature reaction and commutation effects Setup, wiring, commissioning, and maintenance of an electric motor test bench, including component calibration and hardware/software improvements Testing and validation of power-window motors against technical specifications Development and maintenance of Python-based evaluation and automation tools

Fahrwerkvormontage

Fahrwerkvormontage

Fachrichtung: Kommunikationstechnik Zusatzqualifikationen: • Sachkundenachweis Kältemittelkreislauf • Sachkundenachweis Airbagsysteme • Elektrofachkraft für Hochvoltfahrzeugtechnik (EFK) • Sensibilisierung Hochvoltfahrzeuge

Semester Abroad in Lakeland, FL, USA

Forschung im Bereich Lebensdauerprognosen und Zustandsschätzung für Lithium-Ionen Batterien