The electrochemical storage of electrical energy presents a major challenge in the context of energy transition. The lithium-ion technology is going to become the most cost-efficient way to store energy and offers the best opportunity for the following applications: stationary storage and electrical vehicles, due to their high energy density. Moreover, battery energy storage promotes the implementation of renewable energies into the power grid while answering their intermittence. However, the lithium-ion battery is prone to degradations, that impact on the performances and lifespan, as far as consumers or investors are concerned, the use of rechargeable batteries is foremost a matter of lifespan and safety. The degradation mechanisms depend on thermal behavior of the battery. Management of the energy systems and optimization of battery performances, require to develop battery management systems (BMS). The temperature estimation allows improving the electrical response for the BMS, and thermal estimation allows to help this system to preserve the thermal limits of the battery and improves the energy management. It is for these reasons that it is necessary to further increase the current performance of lithium-ion batteries with a thorough understanding of thermal behavior.

This study presents a thermal model of the lithium-ion battery at cell scale using a localized constant approach to facilitate the implementation in the simulation platform of energetic systems. With this process, it is possible to anticipate the thermal behaviors and will allow to dimension a cooling system to optimize the battery energy management. The thermal model is coupled with an electrical model to estimate the cell voltage and the internal resistance with respect to the temperature. The electro-thermal model has been developed to estimate the temperature on the battery from dynamic current profile and ambient temperature. The parameters which characterize the thermal behavior in the cell takes into account the following items: the thermal capacity, the internal resistance, the reaction entropy and the thermal conductance between the core of the cell and casing. Thermal model allows having a good estimation of the surface temperature at the cell level from few data input such as current, voltage, state of charge (SOC), ambient temperature and good thermal parameters. It enables to reproduce the thermal behavior of the cell and given a critical temperature to predict the cell heating. The model was experimentally validated and simulation results are in very good agreement with temperature data measurement. The relative error between the temperature data and simulation is lower than two percent. It has been also shown that thermal distribution on the surface is uniform for periodical solicitations of current. In the end, this model could be implemented to estimate battery pack temperature and for the dimensioning of a cooling system, and it could be implemented in an energetics system simulation platform to improve the performances estimation of storage systems.