ETI 09-2023 Master thesis Data driven State-of-Health monitoring of Lithium Ion battery used for micro-grid optimization
Elektrotechnisches Institut (ETI)
Lithium Ion Batteries (LIB) are recently the preferable energy storage technologies for multiple applications due to its reducing investment costs. Based on the application where the storage is used, the ageing of the battery differs strongly. And at the same time to be able to optimally use the storage systems, tracking the health of the battery is important.
Ageing of LIB happens through different mechanisms, which is briefly accumulated in the image above. Some prominent mechanisms includes growth of the SEI layer, structural damages due to repetitive charging and discharging, lithium platting due to High C-rate, high SOC and or extremely high and low temperature.
As a part of Project BiFlow at Battery Technology Center, ETI, a 60kWh Commercial LiFePO4 battery is used for self-sufficiency improvement of the micro-grid / building. Thus, this LIB is completely charged and discharged at dynamic profiles regularly every day. Since June 2022, high resolution data (250msec resolution) of the individual packs of this battery have been collected. Based on this data ageing due to individual ageing mechanism of the LIB could be tracked, based on which an overall State-of-Health of each battery pack and thus the whole storage system could be defined. Based on the SOH estimation the microgrid optimization strategy would be enhanced further.
as soon as possible
Courses of Study: Electrical Engineering, Mechanical Engineering, Mathematics, Process Engineering or Informatics
Focus: Theory, Literature, Simulation and Programming
Skills recommended: JAVA, basic understanding of battery, Cell Modelling, machine learning
Contact person in line-management
For further information, please contact Mr. Palaniswamy, email: firstname.lastname@example.org.
Bitte bewerben Sie sich online über den unten stehenden Button für die Ausschreibungsnummer ETI 09-2023.
Ausschreibungsnummer: ETI 09-2023
Bei gleicher Eignung werden anerkannt schwerbehinderte Menschen bevorzugt berücksichtigt.
Bei allgemeinen Fragen zur Bewerbung:
Personalservice (PSE) - Personalbetreuung
Frau Carrasco Sanchez
Telefon: +49 721 608-42016,
Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen