For a vehicle equipped with DCT, the vehicle model is established according to the existing experimental data. The traditional method is used to solve the law of economic and dynamic shift, respectively. Then, the dynamic objective function and economic objective function are designed. After normalization of the two functions, the weighted combination is carried out to get the comprehensive objective function. The traditional shift law obtained in the previous paper is regarded as the limit value of variable optimization by particle swarm optimization algorithm, and the comprehensive objective function designed in this paper is solved. The shift law obtained by the three methods is integrated into Simulink model, and the dynamic and economic verification are carried out, respectively. By comparing the acceleration time of 0–100, 0–70, and 70–120 km/h, the dynamic performance of the shift point is obtained by three methods. The final test results show that the economy of the optimized shift point is improved by 1.37% and 3.17%, respectively. The power performance increased by 4.087%, 15.28%, and −10.70%, hence, achieving the desired results.
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