Published November 11, 2026 | Version v1
Model Open

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

Authors/Creators

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

Description

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.

Files

ML_Surrogate_for_Cork_Composite_BTMS.zip

Files (4.1 MB)

Name Size Download all
md5:5f2267954145dee4ff49eb2c808adf82
4.1 MB Preview Download

Additional details

Related works

Is supplement to
Preprint: 10.22541/authorea.15004926/v1 (DOI)

Funding

Austrian Research Promotion Agency
921894