Aiming at the objective evaluation of shift quality of DCT (dual clutch transmission) vehicles

10 parameters are selected as the evaluation indexes of shifting quality from two evaluation dimensions of smoothness and power performance. In order to solve the problems of redundancy between indicators and the lack of rationality of the existing weighting methods

based on the primary evaluation indicators

the evaluation indicators are reduced by using the rough set knowledge reduction method optimized by genetic algorithm

and the effectiveness of the reduction is verified by using the classification model of support vector machine. Then

based on the concept of attribute importance

the reduced evaluation index is weighted. The test results show that the method can effectively delete redundant indicators

and reasonably weight the evaluation indexes

which provides a basis for objective evaluation of shift quality of DCT vehicles.