Conjugate heat transfer analysis of a battery pack using finite volume method

Abstract

Lithium-ion (Li-ion) batteries are an excellent energy source for electric vehicles due to their extraordinary features, such as lower mass density, high energy density and long service life. The use of Li-ion batteries in electric vehicles is becoming extensive in the modern world. During battery charging and usage, internal heat is continuously generated due to increased thermal resistance. If the heat produced is not removed correctly, it will get stored and increase the cell temperature. Such an extreme temperature directly affects the life cycle, effectiveness, dependability, and battery safety problems. Hence cooling mechanism is necessary to have a good life and reliability on the battery system. The main objective of this analysis is to perform the thermal analysis of the Li-ion battery pack considering conjugate conduction-convection boundary conditions at the pack and coolant interface. This analysis is performed numerically by solving the relevant governing equations using the finite volume method. The conduction, Navier-Stokes, and energy equations are solved iteratively. The numerical study is carried for the battery pack cooled with five categories of coolants. Five categories of coolants are passed over the heat-generating battery packs to extract the heat and keep the temperature within the limit. Different kinds of gases, conventional oils, thermal oils, nanofluids, and liquid metals, are adopted as coolants. In each category of coolant, five types of fluids are selected to obtain the lowest maximum temperature. The flow Reynolds number (Re), heat generation (Qgen), and conductivity ratio (Cr) are the parameters considered for each fluid to analyze the temperature distribution in the battery pack and its maximum temperature in detail. The average Nusselt number (Nuavg) analysis indicates the heat removal from the battery pack cooled by flowing fluid is carried out considering coupled heat transfer conditions at the pack and coolant interface. The Pr of the coolants varies in the range of 0.0208 to 511.5 (25 coolants), and Cr for each coolant category has its own upper and lower limit are used. The major findings of the conjugate analysis conducted reveals that the temperature distribution is non-uniform at the top and bottom of the battery. The maximum temperature of the battery pack is located at the top portion of the battery where the electrodes are placed. The temperature of the pack is low at the bottom surface due to direct contact with the coolant which comes in contact as fresh. The regions with high and low temperatures at the top and bottom of the battery pack produce uneven thermal stress, which later can cause the failure of the battery. Hence, choosing an appropriate range of thermal conductivity ratios that balances the solid and the fluid field to get better battery system performance results is required. The maximum temperature of the pack is significantly reduced by the Re and Cr of the coolants. While Qgen in the battery causes an increase in temperature above critical limits. For temperature reduction below the critical threshold requires use of nanofluids at moderate Re and any Cr is suitable. The flow of gas coolants over the battery pack causes a less decrease in maximum temperature due to their lower thermal conductivity. The Cr of all coolants except gases causes a higher difference in maximum temperature at all Re. Thermal oils, nanofluids, and liquid metals provide maximum temperature in the same range of 0.62 to 0.54. In contrast, gases have nearly the same effect at different values of Re and Cr. Pr of oils and liquid metals show more influence than the gases and nanofluids. However, the Pr of coolants shows lower effects at different heat generations inside the battery pack. Conversely, by increasing the Cr of coolants, the Pr shows a promising variation in maximum temperature. The Nuavg is found to be unaffected by Qgen due to the velocity profile remaining the same at any heat generation term. Whereas the flow Re changes the velocity distribution significantly which impacts Nuavg severely for different coolants. The analysis also revealed that Cr and Qgen have no role in improving Nuavg while Pr and Re vary significantly in each step. Moreover, Nuavg is found to increase with Re continuously irrespective of any Cr and Qgen. While, for oils with an increase in Pr and Re, Nuavg was found to reduce significantly. Nanofluids are found to be more effective in improving heat transfer from the battery pack when cooled by flowing nano-coolants over it.