In this paper, a computational fluid dynamics (CFD) model to predict the transient temperature distributions of a prismatic lithium-ion polymer battery (LiPo) cooled by natural convection at various discharge cycles is developed. The thermal behavior of a lithium-ion (Li-ion) battery cell is important for its safety, performance and degradation, and it requires both measurement and modeling. However, most existing thermal models for Li-ion battery cells only account for steady-state temperature fields, while the exercise of a Li-ion battery cell is usually transitory. The Newman’s pseudo-2D approach was used to perform an electrochemical CFD analysis. This approach treats the porous electrode as a collection of equal-sized, isotropic, homogeneous spherical particles. This simplifies the electrode microstructure and assumes a smooth and uniform lithium insertion/extraction in the electrode. The model has been validated through variable discharge rate experimental tests in a controlled chamber. Additionally, infrared images of the battery cell during discharging are taken and the experimental numerical gradient temperature was compared. We have validated the CFD simulations by comparing the temperature, state of charge and voltage curves with experimental data. The model predictions match the experimental data very well. The difficulty in CFD battery simulations with an electrochemical approach lies in the setting of many physical parameters that are difficult to find. In this work, the parameters’ characteristics of the simulated battery are assumed and validated; these can be useful for modeling batteries of the same type. Consequently, the model developed in this work can be applied to predict the temperature distribution of the LiPo prismatic battery and can be used by the battery designers and by the designers of all systems that include batteries.

The increment of battery temperature during the operation caused by internal heat generation is one of the main issues to face in the management of storage systems for automotive and power generation applications. The temperature strongly affects the battery efficiency, granting the best performance in a limited range. The investigation and testing of materials for the improvement of heat dissipation are crucial for modern battery systems that must provide high power and energy density. This study presents an analysis of the thermal behavior of a lithium-polymer cell, which can be stacked in a battery pack for electric vehicles. The cell is sheltered with layers of two different materials: carbon and graphene, used in turn, to dissipate the heat generated during the operation in natural convection. Optical diagnostics in the infrared band is used to evaluate the battery surface temperature and the effect of the coatings. Experiments are performed in two operating conditions varying the current demand. Moreover, two theoretical correlations are used to estimate the thermal parameters of the battery with a reverse-logic approach. The convective heat transfer coefficient h and the specific heat capacity c_p of the battery are evaluated and provided for the Li-ion battery under investigation for different coatings’ conductivity. The results highlight the advantage of using a coating and the effect of the coating properties to reduce the battery temperature under operation. In particular, graphene is preferable because it provides the lowest battery temperature in the most intense operating condition.

Thermal management is an important research area for the automotive sector in order to make high-efficiency and low-impact future vehicles. The transition from internal combustion engines to battery systems in the automotive field requires new skills to be achieved in the shortest possible time. The well-consolidated knowledge of thermal management of engine systems can be rearranged to face new challenges regarding the thermal control of batteries. The present work aims to show the analogies between the thermal behavior of an engine component, such as the piston, and of a battery. The thermodynamic processes involved during the operation are described, experimentally investigated, and modeled. The external temperature of the piston window is measured once per cycle with a K-type sheathed thermocouple, while the surface temperature of the battery is detected via infrared imaging. An almost-fixed stabilization time of 500 s is observed for the engine while it varies with the current load for the battery ranging from 1800 s to 3000 s, for the tested cases. Different temperature increments are also observed. Two mono-dimensional (1D) models of heat transfer are built using the finite-difference method. Good agreement with the experimental data is quantitatively demonstrated by a Normalize Root Mean Square Error lower than 0.07 for all the test cases and systems, except for the battery charging phase. The analysis of the temperature provides an estimation of the heat losses for the two systems, spanning from 15% to 27% for the engine and from 6% to 10% for the battery. The analysis carried out in this work can provide a methodology to understand and improve the thermal management of the new mobility system.