Master Thesis on Data-Based Modelling of Electric Drives for Reinforcement Learning-Based Controller Design
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Job description
Vollzeit
- Typ k.A.
Gewünschte Fähigkeiten & Kenntnisse
Network Machine Learning Data Processing Simulink YouTube CAN Simulation Mobile App Spirit Python Solid Neuronale Netze MS Excel Matlab Engineering Analytisches Denken, Masterarbeit eDrive elektrische Maschine Regelung feedback control Prüfstand test bench neuronale Netze neural networks
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Your tasks The performance and efficiency of electric drives are fundamentally determined by their control methods and modulation schemes. While conventional approaches rely on simplified models and control structures, these limitations often restrict optimal performance in real-world applications. Reinforcement Learning (RL) has emerged as a promising solution, offering the potential to enhance performance through more sophisticated models and control structures, e.g. direct switching control which directly manipulates the switching time instants of the inverter terminals. However, RL agents trained in simulation environments using simplified models frequently experience performance gaps when deployed in real-world scenarios. The main objective of this thesis is the development of an innovative electric drive model suitable for a direct switching controller design using reinforcement learning.
- During your thesis you will conduct a comprehensive literature review on data-based modelling and control of electric drives.
- You will develop a concept for electric drive system excitation for generating training data capturing the switching behavior.
- Furthermore, you will elaborate an electric drive model that captures the switching behavior using physics-based and data-based modelling techniques.
- Optionally, you will train and evaluate a direct switching controller using reinforcement learning and the developed models.
- Finally, the documentation of your work also falls within your area of responsibility., Our Research Campus in Renningen, Germany, is the international hub of our Corporate Sector Research and Advance Engineering, the Cross-Domain Computing Solutions division, and the Bosch Center for Artificial Intelligence. Here, associates from all over the world are dedicated to finding answers to tomorrow's questions. To ensure our researchers' ideas can develop and flow freely, the campus has been set up to encourage direct, easy communication and nurture inspiration - an environment where creativity knows no bounds. Are you ready to join us in shaping the future? Your innovative spirit and curiosity are just what we're looking for.
Requirements
- Education: Master studies in the field of Cybernetics, Computer Science, Engineering, Mathematics or comparable
- Experience and Knowledge: profound knowledge of machine learning and control theory; experience in Matlab/Simulink and Python, ideally in DL frameworks; knowledge of electrical machines is a plus
- Personality and Working Practice: you excel at working autonomously, systematically organizing your tasks, and applying analytical thinking to solve complex problems
- Languages: very good in English
Benefits & conditions
Supported employee car park on site, free bicycle parking in the courtyard, secure bicycle parking space for rent, e-bike charging stations
Company doctor on site Occupational health care and counselling by internal medical staff, free vaccinations, attractive health insurance, psychosocial and therapeutic counselling, personal health care, workshops and lectures on the subject of health, company pension scheme from the 3rd year at Bosch
Discounts for employees Discounted purchasing conditions with us and our partner companies, subsidised cultural and leisure events