The lifetime of a battery pack consisting of many cells in series is determined by the weakest cell. Heterogeneous degradation of the battery cell, as a result of inherent discrepancy between cells, accelerates the aging of the weakest cell, which cannot be overcome by conventional passive and active balancing techniques. Therefore, this paper presents a methodology for charging series-reconfigurable Lithium-ion battery packs. To mitigate the negative effects of unregulated temperature increases, thermal gradients, state-of-charge imbalances, and other cell-tocell variations, we formulate and evaluate a charging strategy that addresses temperature and charge homogenization and temperature tracking. Model Predictive Control (MPC) was used to optimally homogenize the charge and temperature in the reconfigurable battery. Comparative simulations were carried out on the passive and the proposed reconfigurable battery, showing the superior perormance of reconfigurable battery dealing with battery cells with different aging conditions. Moreover, the scalability of the proposed method is verified on a string of 100 serial cells with low computational time. Finally experiments were conducted for four different case studies to verify the proposed MPC-based charge and temperature homogenization and control.