SinoXivEstimating the Impact of Temperature on the Thermal Resistance of a Lithium-ion Battery Using a Combination of the Finite Difference Method and Neural Networks
Abstract
This article focuses on the sustainable development of electric vehicle equipment to ensure the safety of people and property. It contributes to improving the thermal management of lithium-ion batteries in order to slow down wear and tear, increase battery life, range, and performance. The objective of this work is to evaluate the impact of temperature increase on the thermal resistance of lithium-ion battery cells during charging. To this end, an experimental study was conducted to determine the thermal power generated during battery charging using a methodology based on Joule's law. The combination of the finite difference method and neural networks was used to estimate the temperature increase and thermal resistance. The correlation coefficient, with a value of approximately 0.72 and the mean square error, with a value of approximately 0.41 across all test data, are performance indicators that demonstrate the high accuracy of the combined finite difference-neural network model. The thermal power generated and the initial temperature were used as input data for the model. The results showed that an increase in initial temperature has an influence on the thermal resistance of lithium-ion battery cells.
Citation Information
@article{achilleclovicegoune2026,
title={Estimating the Impact of Temperature on the Thermal Resistance of a Lithium-ion Battery Using a Combination of the Finite Difference Method and Neural Networks},
author={Achille Clovice GOUNE and Essombo Bathelemy Essombo and Jean Calvin Seutche and Ghislain Junior Bangoup Ntegmi and Jean Luc Nsouandele and Germain Hubert Ben-Bolie},
journal={Research Square},
year={2026},
doi={https://doi.org/10.21203/rs.3.rs-8998975/v1}
}
