In order to solve the problem of the single objective optimization can't meet the actual demand in the optimization process of the torque converter, the one-dimensional flow theory was adopted to calculate the characteristics of the torque converter. The comparison against experimental data showed a good agreement. On this basis, efficiency, stall torque ratio and max pump torque coefficient were taken as optimization goals, and the multi-objective optimization model was built. The optimization platform was built by integrating Matlab and ISIGHT, in which the one-dimensional beam theory was employed as the core solver. The angle of the blades was taken as design parameters, and the archive-based micro genetic algorithm (AMGA) was utilized to optimize the torque converter performance with change stator and no change stator. The results show that method is effective, and the performance of optimized torque converter has increased compared with the original model. The optimization results obtained by change stator and no change stator method are all improved in the performance indexes of the torque converter, which solves the shortcomings of the single target optimization can't meet the different performance requirements of hydraulic torque converter. © 2017, Editorial Board of Journal of Huazhong University of Science and Technology. All right reserved.
