Abstract: Abstract: China is a large agricultural country, and the tractor is the main agricultural machinery; therefore, its automation degree can represent the level of agricultural mechanization in a country to a large extent. As the core driving part of the tractor, clutch is directly connected with the engine, transfers power by the friction torque of master-slave movable sheets, and realizes the working state of the vehicle powertrain system through the clutch engaging and disengaging. Clutch reliability is worth attention due to that the quality of its separation and bonding directly affects the quality and safety of vehicle shift, however, current study on the clutch is mainly in terms of engagement and gear shifting impact, more emphasis is on the research of the individual parts, and there are few attentions in the analysis of the assembly characteristics for the clutch. The reliability of the clutch assembly cannot be separated from the interaction between the components. Gray relational theory is used to explore the actual movement laws, and mainly according to the known information, it uses the sequence operator to further extract valuable information to realize the correct description and effective monitoring of system behavior and evolution law. After the investigation of the actual working conditions of the clutch, the structural failure of the clutch is mainly attributed to 20 factors. Among the verified factors, strength, stiffness, damping, and heat resistance of key parts of clutch are selected as the research targets. In order to analyze the influence of the components on the clutch, the three-dimensional model of the clutch is established in UG (Epigraphics NX, UG)according to the specific structure of the clutch. Considering the failure form, production process, test engineering and customer feedback of clutch, the performance index of the clutch is treated according to the mathematical model of the subjective comprehensive evaluation, the clutch grey correlation model is established, and the reliability of the clutch is determined. Then, the reliability of the clutch is evaluated. Firstly, 12 sets of virtual prototype sequences are selected as the sample data in the ANSYS-workbench simulation environment, and the approximation degree of each sampling sequence and the characteristic behavior sequence are compared through the data line diagram drawn in Matlab, in order to obtain the optimal prototype sequence. When the traditional grey correlation method is used to evaluate the overall reliability of clutch, the No. 10 sample is better, including the disc spring deformation characteristics, master-slave wheel hub strength, and mechanical efficiency of spline, which 3 indicators are below the set of behavior feature sequence. But this method is not suitable for indicators dispersed distribution, object sequence characteristics cannot be fully reflected, and it is prone to generate miscarriage of justice due to that the sequence of local data value is too large. When the generalized grey incidence analysis method is adopted, the correlation degree between the sampling sequence and the characteristic sequence is analyzed from the angle of the curve by using the absolute grey correlation method; and the correlation between curves is described by the relative grey correlation method from the angle of relative change rate of curve. The similarity and proximity between the 2 curves are analyzed according to the gray correlation method, and the No. 7 sample is determined as the optimal virtual prototype sequence. Compared with the No. 10 sample sequence analysis results, in the No. 7 sample series, the temperature characteristics of the master-slave disk and the seismic characteristic of shock absorber spring are below the characteristic behavior sequence. Comparing the analysis results of the 2 methods with the statistics of the clutch production site, the optimal solution of generalized grey relational analysis method is more close to the practical engineering, and this analysis method can provide a reference for the research of similar products' reliability.