A numerical investigation of a two-phase nanofluid flow with phase change materials in the thermal management of lithium batteries and use of machine learning in the optimization of the horizontal and vertical distances between batteries

In this article, a battery pack cooling system having multiple lithium-ion (LIB) battery cells with a laminar nanofluid (NFD) flow and phase change materials (PCMs) was simulated using the finite element method (FEM). The cooling system's walls were curved, and the NFD flow was simulated using the two-phase method. PCMs were positioned inside the elliptical enclosure and encompassed all the battery cells. The temperature of the battery cells, heat transfer coefficient (HTC), and phase change by PCMs were transiently investigated by the alteration of the vertical distance between batteries from 0.7 to 1.1, the horizontal distance between batteries from 0.5 to 1, and the NFD input size from 0.5 to 1.5. The data were optimized using the artificial intelligence (AI) technique to achieve the best results. The results showed that the maximum pressure drop occurs at the biggest NFD input, the highest horizontal distance, and the lowest vertical distance between batteries (583% difference). Similarly, the lowest maximum temperature (MXT) of batteries (TLIB) occurred at the lowest horizontal and vertical distances between batteries and the smallest NFD input dimensions (7.15 degrees difference). The highest HTC (794.26 W/m2K) between the NFD and batteries occurred at the highest horizontal distance and the lowest vertical distance between batteries and the highest NFD input dimensions.

Automated summary

In this study, a battery pack cooling system with laminar nanofluid flow and phase change materials was simulated using finite element method. The effects of vertical and horizontal distance between battery cells and nanofluid input size on temperature, heat transfer coefficient, and phase change were investigated. The results were optimized using artificial intelligence technique. The findings showed that the maximum pressure drop occurred at the highest nanofluid input, highest horizontal distance, and lowest vertical distance between battery cells (583% difference). The lowest maximum temperature of batteries occurred at the lowest horizontal and vertical distances and smallest nanofluid input dimensions (7.15 degrees difference). The highest heat transfer coefficient between nanofluid and batteries was observed at the highest horizontal distance, lowest vertical distance, and highest nanofluid input dimensions.