Machine Learning for Battery Lifetime Predictions

  • Apply state-of-the-art machine learning methodologies on an extensive battery ageing dataset
  • Make use of a dataset covering over 3 years of calendar and cyclic ageing data for a commercial state-of-the art Li-ion pouch cell
  • Building up on a previous Masters’ thesis at ITS by Andreas Dyve
  • What are the advantages and disadvantages of using ML models vs standard state-of-the-art empirical models?
  • Is it more time and/or resource efficient to develop ML model compared to ESF models?
Published Nov. 17, 2024 10:03 PM - Last modified Nov. 17, 2024 10:17 PM

Supervisor(s)

Scope (credits)

30