Abstract

This paper deals with the thermal modeling and validation of temperature rise in a prismatic lithium-ion battery with LiFePO4 (also known as LFP) cathode material. The developed model represents the main thermal phenomena in the cell in terms of temperature distribution. A neural network approach is used for the model development. The proposed model is validated with the experimental data collected in terms of temperature and voltage profiles. In addition to this, the surface temperature distributions on the principal surface of the battery are studied under various discharge/charge profiles with varying boundary conditions (BCs) and average surface temperature distributions. For this, the different discharge rates of 2C and 4C and different boundary conditions (cooling/operating/bath temperature of 5 °C, 15 °C, 25 °C, and 35 °C) are selected. The results of this study show that the increased discharge rates result in increased surface temperature distributions on the principal surface of the battery. Furthermore, it is observed that changing the operating or boundary conditions considerably affect the surface temperature distributions.

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