The reliability of engine and chassis system is the key factor affecting the performance of commercial vehicles.Accurate and comprehensive evaluation of its reliability is of great significance to guide the improvement of commercial vehicle reliability.Based on big data of faults

a reliability evaluation was conducted for the engine and chassis of four commercial vehicles within a specific manufacturing enterprise.All the fault data of the four commercial vehicles in 2021 were collected for preliminary statistical analysis

and a random sample was drawn to form an analysis sample.Based on the U-test to test the difference between the sample and the overall data distribution

the probability density distribution function of the engine and chassis system fault interval was fitted

and it was inferred that the distribution law satisfied the Weibull distribution.The traditional median rank method and kernel density estimation method were used to mutually verify and calculate the distribution parameters of the system.The Kolmogorov-Smirnov(K-S)hypothesis test was used to verify that the sample data of the fault interval time followed the Weibull distribution.The reliability evaluation indexes such as reliability

failure rate and mean time between failures were calculated.After 500 days of driving

the reliability of the four commercial vehicles were 0.002

0.003

0.007 and 3×10-9.The fault rates were 0.021

0.016

0.015 and 0.063.The average time between fault were 146.088

129.492

149.755 and 70.897 days.Based on the reliability evaluation results and fault contents of engine and chassis system

the optimization scheme was proposed to provide reference for the reliability improvement of the commercial vehicle system.