Write a PREreview

Neural Operator-Based Prediction of Temperature Dynamics in Lithium Iron Phosphate Batteries for Electric Vehicles

by Abhishek Baer

Posted: October 6, 2025
Server: Preprints.org
DOI: 10.20944/preprints202510.0462.v1

This paper presents a novel approach for modeling temperature evolution in Lithium Iron Phosphate (LiFePO4) electric vehicle batteries using Neural Operators. The method overcomes limitations of traditional heat transfer models by learning a data-driven surrogate that accurately predicts battery temperature as a function of driving diagnostics and environmental conditions. The study explores regularization techniques and a time stability loss function to enhance the model’s robustness and accuracy. Results demonstrate the efficacy of the proposed Neural Operator framework for estimating battery temperature dynamics.

You can write a PREreview of Neural Operator-Based Prediction of Temperature Dynamics in Lithium Iron Phosphate Batteries for Electric Vehicles. A PREreview is a review of a preprint and can vary from a few sentences to a lengthy report, similar to a journal-organized peer-review report.

Before you start

We will ask you to log in with your ORCID iD. If you don’t have an iD, you can create one.