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.

Simulating the electrochemical-thermal behavior of a prismatic lithium-ion battery on the market under various discharge cycles

Luca Magri;Luigi Sequino;Cristian Ferrari
2023

Abstract

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.
2023
Istituto di Scienze e Tecnologie per l'Energia e la Mobilità Sostenibili - STEMS
CFD
lithium battery
Newman's model
simulation
temperature distribution
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/429940
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