Optimization for Driveline Parameters of Self-Dumping Truck Based on Particle Swarm Algorithm

In this study, with the aim of reducing fuel consumption and improving power performance, the optimization for the driveline parameters of a self-dumping truck was performed by using a vehicle performance simulation model. The accuracy of this model was checked by the power performance and fuel economy tests. Then the transmission ratios and final drive ratio were taken as design variables. Meanwhile, the power performance of the self-dumping truck was evaluated through standing start acceleration time from 0 to 70km/h, maximum speed and maximum gradeability, while the combined fuel consumption of C-WTVC drive cycle was taken as an evaluation index of fuel economy. The multi-objective optimization for the power performance and fuel economy was then performed based on particle swarm optimization algorithm, and the Pareto optimal set was obtained. Furthermore, the entropy method was proposed to determine the weight of fuel consumption and acceleration time. The optimal solution was chosen based on the entropy weighted performance coefficient. In addition, confirmation simulations of fuel economy and power performance were conducted by using the optimal combination of the driveline parameters, to demonstrate the effectiveness of PSO algorithm and entropy method for dealing with multi-objective optimization problems.