Abstract
The spacing in a lithium-ion battery pack is crucial in various aspects; including mechanical stability, heat dissipation, temperature distribution, thermal coupling, and cooling effectiveness. This research aims to enhance the cooling efficiency of a 24 V, 10Ah, 4P7S aligned battery pack by optimizing the distribution of spacing among the battery cells. The parameters examined in this study are the longitudinal pitch (Dx), transverse pitch (Dy), and distance of first row with the side walls (Dw). The Computational Fluid Dynamics (CFD) approach is utilized to compute the flow and temperature fields of the battery thermal management system (BTMS). Thereafter, CFD simulations, in conjunction with the Taguchi approach of Design of Experiments (DOE), is used to determine the optimal parameters. Additionally, an experimental set-up is developed to validate the numerical results with experimental outcomes. Thermal performance evaluation includes examining temperature changes both along and across the airflow direction, temperature variation around the circumference of the cells. The key parameters such as maximum temperature (Tmax), average temperature (Tavg.), maximum temperature differential (∆Tmax), and temperature standard deviation (σT) are also determined. Furthermore, it is assessed that how different distances affect the necessary power (P) and space utilization factor (α) for the airflow. Enlargement of the cooling air vortices within the backflow zone with an increase in Dx is observed to cause a drop in Tmax, Tavg., ∆Tmax, and σT. In addition, as Dy is increased, the values of these parameters fall to a minimum and then begin to rise. Dw also shows a similar impact. Changing Dx from 20.00 mm to 36.00 mm raises inlet pressure, which causes P to increase by 0.57 W. It is determined that the optimal dimensions to maximize the thermal performance of the battery pack in question are (Dy = 24.00, Dx = 36.00, and Dw = 12.00, mm). The numerical results closely matched with the experimental results, with a maximum absolute relative error of 1.48%.
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