Nanofluid-based cooling of prismatic lithium-ion battery packs: an integrated numerical and statistical approach

Recently, the need for thermal management of lithium-ion batteries in electrical transportation engineering has received increased attention. To get maximum performance from lithium-ion batteries, battery thermal management systems are required. This paper quantitatively presents the effects of several factors on both maximum battery temperature and temperature gradient. These factors include ambient temperature (288 K, 293 K, 298 K, 303 K, 308 K), C-rate (1C, 2C, 3C, 4C, 5C), mixing ratio (1%, 2%, 3%, 4%, 5%), and inlet velocity (0.01 m s-1, 0.02 m s-1, 0.03 m s-1, 0.04 m s-1, 0.05 m s-1). Five levels for each parameter were considered to develop the orthogonal array. The significance of the variables was orderly shown through the L25 experiment. Results indicated that for maximal battery temperature, C-rate and ambient temperature are the most significant factors while for temperature gradient, C-rate and inlet velocity play an important role. For maximum battery temperature ambient temperature, C-rate, mixing ratio, and inlet velocity of 288 K, 1C, 4%, and 0.05 m s-1, respectively, were obtained at the optimal setting. An ambient temperature of 308 K, a C-rate of 1, a mixing ratio of 5%, and an inlet velocity of 0.05 m s-1 was the optimal setting for the temperature gradient. The results showed that the confirmatory test validates the optimization process for maximum battery temperature and temperature gradient. This study may provide a pathway for manufacturers and researchers interested in minimizing battery temperature and improving temperature gradient in electric vehicle applications.