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Laboratory for Smart Energy Systems

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Become part of the “Smart Energy Systems” research group!

In the “Smart Energy Systems” research group, we are always looking for motivated and interested people! Are you interested in working as an assistant scientist (m/f/d) or writing your Bachelor's or Master's thesis with us? Please use the form below or send us a non-binding e-mail - we look forward to hearing from you! 

 

Thesis / Part-Time Master's: Development of a Machine Learning-Based Prognostic Model for Aging Prediction of Lithium-Ion Battery Systems Based on Field Data

This thesis aims to improve an existing data-driven model for predicting the remaining useful life of battery systems using statistical methods and machine learning. Ideal for students with a strong interest in data science and energy systems.

Thesis / Part-Time Master's: Transfer Learning for Battery Aging Prediction

Battery aging varies with cell chemistry. This thesis focuses on transferring existing aging models to different battery types using transfer learning and hybrid modeling approaches.

Bachelor's or Master's theses

In the Smart Energy Systems team, we continuously supervise student projects both in-house and at the interface with industry. Do you have a specific topic suggestion or an idea? Then please contact us directly via email

 

Contact

Professor Holger Hesse

Tel. +49 (0)831 2523-9309
holger.hesse(at)hs-kempten.de

Location

Bahnhofstrasse 61
87435 Kempten, Germany

Room:
S.1.13