Bachelor's or Master's thesis - EIS-based diagnosis of lithium-ion cells in automated disassembly

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City:  Darmstadt

Date:  Oct 10, 2025

Bachelor's or Master's thesis - EIS-based diagnosis of lithium-ion cells in automated disassembly

**WHAT COUNTS FOR US IS THE IDEA -
AND THE PEOPLE BEHIND IT.** 
CHANGE STARTS WITH US.

Bachelor's or Master's thesis – EIS-based diagnosis of lithium-ion cells in automated disassembly (all genders)

Darmstadt

Here you create change

With the increasing use of electric vehicles, the need for sustainable and efficient recycling processes for traction batteries is also growing. A key step is the automated, safe, and non-destructive separation of individual cells from used battery modules – particularly to reuse them either as second-life cells or to recover high-quality materials.

As part of an ongoing research project, Fraunhofer LBF is developing an automated disassembly system. This system will now be expanded to include a module for integrating real-time battery cell health diagnostics. The goal is to apply electrochemical impedance spectroscopy (EIS) directly during the disassembly process to classify the cells for their reusability.

A pre-trained machine learning model for assessing cell condition based on EIS data is available and will be integrated into the system.

Your Tasks

• Literature research on the condition diagnosis of lithium-ion cells with a focus on EIS
• Design and simulate a probe system (potentially integrated with a robotic head) for cell contact and impedance measurement
• Analysis and preprocessing of EIS data
• Integration and deployment of an existing ML model (e.g., as a Python module, API, or embedded system)
• Evaluation of real-time capability and measurement quality
• Validation of the solution in a prototype test environment
• Documentation and presentation of the results

This is your contribution

• Electrical Engineering / Mechatronics / Automation Engineering / Computer Science or related fields
• Interest in battery technologies and electromobility
• Basic knowledge of electrochemistry or willingness to learn
• Experience in working with Python, MATLAB or comparable tools for signal analysis
• Knowledge of machine learning (especially model deployment) is an advantage
• Structured, independent, and solution-oriented working style
• Good communication skills (German & English)

What we have in store for you

• An individually tailored task with plenty of creative freedom
• A highly topical and practically relevant research topic with direct relevance to the circular economy
• The opportunity to actively participate in an innovative and interdisciplinary project
• Access to state-of-the-art laboratory equipment and professional support
• Prospects for a further scientific or industrial career
• Insight into current developments in battery cell disassembly and diagnostics

Home office option by arrangement (not 100%).

Ready for a change? Then apply now and make a difference! Once we have received your online application, you will receive an automatic confirmation of receipt. We will then get back to you as soon as possible and let you know what happens next.

We value and promote the diversity of our employees' skills and therefore welcome all applications - regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation and identity. Severely disabled people are given preference if they are equally suitable.

Our tasks are varied and adaptable - we work together with applicants with disabilities to find solutions that best promote their abilities. The same applies if they do not meet all the profile requirements due to a disability.

Do you have questions about the position? Our colleague Savan Dihora is there for you: Phone +49 6151 705-573

Fraunhofer Institute for Structural Durability and System Reliability LBF 

www.lbf.fraunhofer.de&nbsp

Requisition Number: 80490                Application Deadline:

Job Segment: Computer Science, Laboratory, Engineer, Electrical, Research, Technology, Science, Engineering

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