Optimization Matching of Powertrain System for Self-Dumping Truck Based on Grey Relational Analysis 2015-01-0501
In this paper, the performance simulation model of a domestic self-dumping truck was established using AVL-Cruise software. Then its accuracy was checked by the power performance and fuel economy tests which were conducted on the proving ground. The power performance of the self-dumping truck was evaluated through standing start acceleration time from 0 to 70km/h, overtaking acceleration time from 60 to 70km/h, maximum speed and maximum gradeability, while the composite fuel consumption per hundred kilometers was taken as an evaluation index of fuel economy. A L9 orthogonal array was applied to investigate the effect of three matching factors including engine, transmission and final drive, which were considered at three levels, on the power performance and fuel economy of the self-dumping truck. Furthermore, the grey relational grade was proposed to assess the multiple performance responses according to the grey relational analysis. In this process, the principal component analysis was employed to determine the corresponding weights of the five indicators. Then the optimal combination of the engine, transmission and final drive was determined according to the Taguchi methodology. Finally, a confirmation test was conducted to verify the optimal matching factors obtained by the proposed approach. The results indicated that the fuel economy of the improved self-dumping truck has been improved prominently, whilst its power performance completely satisfies the engineering design requirement. Hence, the optimization method based on the Taguchi method and grey relational analysis is an effective approach for the optimization matching of the powertrain system.