Battery thermal management system (BTMS) is critical to battery packs in electric vehicles, which significantly influences the service life of the battery packs and the performance of the electric vehicles. In this paper, the structure optimization of the parallel air-cooled BTMS is investigated to improve the cooling performance of the system. The flow resistance network model is introduced to calculate the velocities in the cooling channels of the system. The numerical results show that the velocities in the cooling channels calculated by the flow resistance network model are in good agreement with the ones calculated by CFD method, validating the effectiveness of the model. Furthermore, the model can save much calculation time, which is applicable to combine with the optimization approaches for structure optimization of BTMS. Subsequently, the structure of the BTMS is optimized through arranging the widths of the inlet divergence plenum and the outlet convergence plenum without changing the layout of the battery cells. Newton method is introduced to combine with the flow resistance network model to obtain the optimal plenum widths, with the target of minimizing the standard deviation of airflow velocities in the cooling channels. The optimization with fixed inlet flow rate and the one with fixed power consumption are both conducted. Three-dimensional CFD calculations for both the original BTMS and the optimized BTMS are performed, respectively. The results show that the cooling performance of the BTMS can be improved significantly after optimization using the proposed method. For the situation with fixed inlet flow rate and constant heat generation of the battery pack, the maximum temperature difference of the battery pack is reduced by 45% after optimization. For the situation with fixed power consumption and constant heat generation of the battery pack, the maximum temperature difference of the battery pack is reduced by 41%.after optimization. Moreover, the maximum temperature of the battery pack is also reduced slightly after optimization. For the situation with fixed power consumption and unsteady heat generation of the battery pack, the maximum temperature differences of the battery pack are still reduced by 35% and 32% respectively for 4C and 5C discharge processes after optimization. It can be concluded that Newton method combined with the flow resistance network model is an effective method to optimize the structure of the parallel air-cooled BTMS and to improve the cooling performance of the system. (C) 2017 Elsevier Ltd. All rights reserved.