Masterarbeit: KI-basierte Regelung der Leistungselektronik (w/m/div.)

Role Summary

Modern power electronic systems, in particular AC/DC and DC/DC converters, form the indispensable backbone of tomorrow's technology landscape: In e-mobility, they enable ultra-fast, highly efficient onboard charging systems and robust power delivery. In robotics, they drive highly dynamic, precise actuators and electric drives required for collaborative and autonomous systems. In data centers, they ensure maximum energy efficiency, high power density and uninterrupted operation. In order to meet the strict efficiency and installation space requirements of these applications, modern power electronics are increasingly relying on advanced soft switching topologies. Although these topologies significantly reduce switching losses and maximize power density, they exhibit highly nonlinear dynamics. At the same time, cost and space optimization require smaller energy storage components (capacitors and inductors), which further increases system instability and complex dynamic behavior. Traditional linear control methods (such as standard PI controllers) struggle to maintain optimal performance under these demanding conditions.

This master's thesis aims to investigate, compare and implement next-generation closed-loop control algorithms to master these nonlinearities and further push the performance limits of converters. As part of your work, you will select the most promising control concept and develop a tailor-made control strategy based on an existing simulation model of our next-generation charger converter topologies. You will investigate advanced closed-loop control methods suitable for highly nonlinear power electronic systems, with a focus on model predictive control (MPC), neural network-based control architectures, and reinforcement learning (RL) approaches for power converters. In addition, you implement the developed control algorithm in a simulation environment (e.g. MATLAB/Simulink, Python or PLECS). You will also validate and benchmark the control concept under realistic operating conditions and evaluate the transient behavior, efficiency and stability in comparison to established reference controllers. You analyze and compare the identified control strategies in terms of computational effort, dynamics, robustness to parameter changes and suitability for real-time implementation. Finally, you create the documentation and present the results.

Requirements

Education: Master's degree in electrical engineering, control engineering, mechatronics, cybernetics, computer science or a comparable qualification

Experience and knowledge: Sound knowledge of control systems (state space, non-linear control or predictive modern control methods); confident use of simulation tools such as MATLAB/Simulink and/or Python with machine learning frameworks such as PyTorch; Knowledge of power electronics (AC/DC and DC/DC converters) is an advantage

• Personality and way of working: You are a goal-oriented and motivated person with a solution-oriented mindset
• Working model: We offer you the opportunity to work in a hybrid working model
• Enthusiasm: High motivation to work on pioneering research at the interface of power electronics and intelligent control systems (machine learning, reinforcement learning).
• Languages: Business fluent English or German

Benefits

Start: by prior arrangement

Duration: 6 months

• The prerequisite for this thesis is enrollment at a college/university. Please attach your CV, your transcript of records, the examination regulations and - if necessary - a valid work and residence permit.
• For us, diversity and inclusion are not just trends, they are firmly anchored in our corporate culture. We therefore welcome all applications – regardless of gender, age, disability, religion, ethnic origin or sexual identity.
• Error 500 (Server Error)!!1500.That’s an error.There was an error. Please try again later.That’s all we know.

About the Company

At Bosch, we shape the future by developing high-quality technologies and services that inspire and enrich people's lives. Our promise to our employees is rock solid: We grow together, we enjoy our work and we inspire each other. Join us and feel the difference. Robert Bosch GmbH looks forward to your application!