Thesis in Development of a Learning Based Compositional Electrical Drive Model

Robert Bosch Group; Renningen; Vor Ort; EUR 40.000 - 60.000; Vollzeit

Zusammenfassung

A leading technology company in Germany is offering a full-time thesis position focusing on the development of a learning-based electric drive model. Candidates should have a background in Electrical Engineering or related fields, with knowledge in Machine Learning and Python. This opportunity provides hands-on experience in modeling dynamical systems and applying research in a collaborative environment.

Qualifikationen

• Good knowledge in German and English.
• Flexibility and enthusiasm in work practice.

Aufgaben

• Familiarize with physical models of electric drives.
• Conduct literature research on existing (ML-based) approaches.
• Develop the dynamical physical electrical drive model.
• Implement proof of concept for gradient-based optimization.

Kenntnisse

Machine Learning

Python

Modelling of dynamical Systems

Ausbildung

Studies in Electrical Engineering, Cybernetics, Physics, Computer Science or comparable

Jobbeschreibung

Thesis in Development of a Learning Based Compositional Electrical Drive Model

• Full-time

At Bosch, we shape the future by inventing high-quality technologies and services that spark enthusiasm and enrich people’s lives. Our promise to our associates is rock-solid: we grow together, we enjoy our work, and we inspire each other.
Join in and feel the difference.

The Robert Bosch GmbH is looking forward to your application!

The identification of accurate simulation models of electric drive systems, comprising the inverter, an electric driver, and further components, is a crucial step for the design of high-performing controllers, fault diagnosis, and many other tasks. The goal of the thesis is to develop a compositional model for electric drives that allows for simulation, identification and control using automatic differentiation techniques. The main idea is to implement differentiable models for components of an electric drive that can be freely combined to an overall system model.

Responsibilities

• You will familiarize yourself with physical models of electric drives (electric machines, inverters, …).
• You will do literature research on existing (ML-based) approaches for the identification of electric drives.
• Furthermore, you will develop the dynamical physical electrical drive model combined with data-based models.
• Last but not least, you will implement the proof of concept to demonstrate the gradient-based optimization of the overall model for a given example system under using dynamical data with ODE solvers.

Qualifications

• Education: studies in the field of Electrical Engineering, Cybernetics, Physics, Computer Science or comparable.
• Experience and Knowledge: in Machine Learning and Python; modelling of dynamical Systems.
• Personality and Working Practice: you are flexible, enthusiastic and responsible.
• Languages: good in German and English.

Start: according to prior agreement
Duration: 6 months

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.

Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore, we welcome all applications, regardless of gender, age, disability, religion, ethnic origin or sexual identity.

Need further information about the job?
David Gänzle (Functional Department)
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