Shift quality optimization control of power shift transmission based on particle swarm optimization–genetic algorithm
Guang Xia, Jiangshan Chen, Xiwen Tang, Linfeng Zhao, Baoqun Sun
Abstract
A clutch control strategy is proposed to improve the shift quality of power shift transmission and solve the power cycle phenomenon in the shifting process. The strategy effectively avoids the power cycle phenomenon by analyzing the change in the transmission torque and the relationship between the rotating speed of the driving and driven disks of a shifting clutch. The evaluation indexes of the shift quality of power shift transmission are sliding friction power loss, impact degree, and torque oscillation amplitude. Particle swarm optimization (PSO), combined with a genetic algorithm, is used to optimize the shift quality of power shift transmission, solving the problem in which basic PSO frequently converges to the local optimal solution. Simulations and experiments are performed on the optimization results. The simulation and test results show that the proposed control strategy can ensure that the rotating speed of the driving disk is always higher than that of the driven disk when the clutch is insliding and wearing states. Thus, this control strategy effectively avoids power cycle when shifting and improves shift quality.