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There is not much research carried out on factors such as temperature differences in different regions of battery pack, which is highly important and poses a great challenge. Temperature changes across batteries affect the battery pack performance and its life span largely. Thus, the present work proposes the Integrated Finite Element‐Meta‐Optimization Framework for solving this problem. The integrated framework includes the formulation of Finite Element Model of a battery pack and Meta‐Optimization Framework for multi‐objective minimization of three objectives such as the inter‐cell temperature differences, temperature standard deviation and the total volume of the cell. In this framework, firstly Support Vector Regression (SVR) model is formulated based on the data and the SVR parameters are optimized using a genetic algorithm. It can conclude that the resulting model has a coefficient of correlation metric of 99%. The simulated annealing algorithm is then applied to find the optimal values of inter‐cell and cell‐enclosure distances for minimization of inter‐cell temperature differences and the total volume of the cell. Optimization analysis concluded that the volume of the battery pack was decreased by 29%, temperature difference (K) by 42% and SD of the temperature over the entire pack decreased by 55%. [ABSTRACT FROM AUTHOR]