Master Thesis Application of Physics-Informed Machine Learning for Grid-Tied Inverter Control

Bosch Group

Renningen

Vor Ort

EUR 9.000 - 13.000

Teilzeit

14 Tage+
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Zusammenfassung

Robert Bosch GmbH in Renningen seeks a Master thesis candidate to develop a physics-informed current controller for grid-tied inverter control. You will compare linear regulators and predictive controllers, investigate AI-based implementations, and design a concept to improve AI-based black-box approaches, mitigating their drawbacks.

You will select an AI-based concept, possibly involving machine learning, RNNs, or reinforcement learning, and, if needed, model the system alongside the

Qualifikationen

  • Master studies in Engineering, Mathematics, IT, or comparable.
  • Experience with AI methods, system modelling and control engineering; power electronics is advantageous.
  • Team player with good communication, able to work independently and meticulously.
  • Office and laboratory work required, partially mobile working possible.

Aufgaben

  • Develop a physics-informed current controller for grid-tied inverter control.
  • Evaluate linear regulator and predictive controller as reference points.
  • Research AI-based implementations in literature.
  • Develop a concept to improve AI-based black-box implementations and mitigate drawbacks.
  • Select an AI-based concept (e.g., ML, RNN, RL) and model the system if needed.

Kenntnisse

AI methods
System modelling
Control engineering
Power electronics

Ausbildung

Master's degree in Engineering/Math/IT

Jobbeschreibung

Company Description

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!

Job Description
  • As a part of your Master thesis, you will develop a physics-informed current controller for grid-tied inverter control.
  • You will evaluate the linear regulator and the predictive controller as reference points, as well as establish their boundaries.
  • In addition, you will research current AI-based implementations in the literature.
  • Furthermore, you will be responsible for developing a concept to improve the implementation of AI-based black boxes and mitigate their drawbacks in grid-tied inverter applications.
  • Last but not least, you will select an AI-based concept, which may include machine learning, recurrent neural networks or reinforcement learning. If necessary, you will model the system alongside the implemented controller.
Qualifications
  • Education: Master studies in the field of Engineering, Mathematics, Information Technology or comparable
  • Experience and Knowledge: in the application of AI methods, system modelling and control engineering; in power electronics advantageous
  • Personality and Working Practice: you are a team player with good communication skills who is able to work independently, proactively and meticulously
  • Work Routine: office and laboratory work required, partially mobile working possible
  • Languages: good in English
Additional Information

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?

Paul Kießling (Functional Department)

+49 152 04696974

Tobias Beck (Functional Department)

+49 152 58813496

Legal Entity: Robert Bosch GmbH

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