Work

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

Year: 2026

Type: dataset

Abstract: 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.

Source: TUGraz OPEN Library (Graz University of Technology)

DOI: 10.3217/ken76-vfy64

Authors: Wagner, Markus, Baumann, Georg, Feist, Florian, Schmid, Alexander, Schneider, Alexander, Bliem, Peter, Pinkl, Stefan

Institutions: Graz University of Technology, Battery4Life GmbH, BOKU University

Language: English

Topic: Battery Modeling and Management

Subfield: Automotive Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W7225824334

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