Veröffentlicht 11. November 2026 | Version v1
Modell Offen

Machine Learning Surrogate for Data-Driven Design of Cork-based Composites for Thermal Management of EV Battery Cells

Autor*innen/Ersteller*innen

  • 1. ROR icon Graz University of Technology
  • 2. Battery4Life GmbH
  • 3. Wood K plus
  • 4. ROR icon University of Natural Resources and Life Sciences

Beschreibung

This repository contains a Python-based machine learning framework for estimating the temperature evolution of lithium-ion battery modules under fast-charging conditions and various external operating conditions. The framework combines a rank-reduced autoencoder with a feed-forward neural network to predict battery temperature curves.

In addition to the model implementation, the repository includes the required input files and a Python script for  testing the proposed approach.

Dateien

ML_Surrogate_for_Cork_Composite_BTMS.zip

Dateien (4.1 MB)

Weitere Details

Verknüpfte Arbeiten

Ergänzt
Preprint: 10.22541/authorea.15004926/v1 (DOI)

Förderung

Austrian Research Promotion Agency
921894