Thesis "Optimization of a Sorptive Dry Air Supply for Battery Cell Production"

The Fraunhofer Institute for Solar Energy Systems ISE, based in Freiburg, plays a leading international role in the field of renewable energy systems and technologies with its research and development work. Securing the livelihoods of current and future generations as well as preserving our natural environment drive our efforts. With our currently around 1,400 employees, we are shaping the transformation of energy supply through outstanding research results, successful projects with industrial partners, spin-offs, and global collaborations – towards the exclusive use of renewable energies.

 

For our team “System Integration and Energy Concepts”, we are looking for a student assistant to start as soon as possible, with the opportunity to write a bachelor's, diploma, or master's thesis.

 

One of our projects, funded by the Federal Ministry of Education and Research, focuses on the energy-efficient production of battery cells. The goal of the project is to design a controlled production environment that surrounds the manufacturing processes with the smallest possible volume while meeting both cleanroom and dry room requirements. To meet these requirements, very low residual moisture levels are necessary in the controlled manufacturing environment, as higher levels would otherwise impair the future storage capacity of the battery cells. Therefore, sorption wheels are used for dehumidification, which require enormous amounts of energy for regeneration. To reduce this energy consumption and therefore the CO₂ footprint of the produced batteries, we are investigating the operation and interconnection of the sorption wheels using a numerical simulation model in Modelica/Dymola. We are optimizing the processes according to the given requirements. The aim is to develop a parametrizable universal model based on various created models that achieve the target dew points of up to -30 °C. Using discrete and continuous parameters, this model should find the optimal parameter set via a “Functional Mock-up Interface” (FMI) with an algorithm to be implemented in Python.

 

What you will do

• You will create a universal model based on documented, functioning Modelica models for Sorptive air drying, which can represent each of these models through parameter variation.
• You will implement at least one optimization algorithm in Python that controls the parameter optimization of the Modelica model via an FMI.
• Your tasks also include conducting a literature review on the algorithms. In particular, while the Genetic Algorithm can significantly reduce computation time, it does not reliably lead to a unique solution.
• During your work, you will document your learning process as well as your results so that you can ultimately use them for your thesis. Part of this work also includes maintaining and organizing a repository in GitLab.

 

What you bring to the table

• You are studying the programs engineering, mathematics, computer sciences or similar.
• Additionally, you possess foundational knowledge in object-oriented programming. Ideally, you are proficient in programming Python code or at least one of the closely related programming languages.
• You value contributing to your team and achieving common goals through interdisciplinary and international collaboration.
• You plan and complete tasks independently and with high quality.
• You can independently and proactively plan upcoming work steps, set priorities, and have appropriate time management skills.
• You enjoy sharing your work results and can present them convincingly.You have good German language skills (at least B1) and have successfully demonstrated your good English skills (at least B2).

 

What you can expect

• Exclusive insight: By working together with the scientists in our work unit, you will gain an insight into everyday research and development at a research institute.
• Laboratory infrastructure: At Fraunhofer ISE, we work with state-of-the-art facilities and equipment so that research projects can be carried out using the latest technology.
• Research mix: We give you the opportunity to combine experimental work with theory and thus apply and expand your knowledge from your studies.
• Supervision: You will be supervised in your work by scientists and receive feedback on your progress.
• Teamwork: You will gain experience of working in a team by interacting with academic and student staff and will be able to contribute the experience you have already gained.
• Working hours and location: We offer you the opportunity to flexibly adapt your working hours