Optimization of DCT Power-On Upshift Control Strategy Based on PSO Algorithm

This investigation presents a methodology to develop and optimize shift process control strategy to improve shift quality as perceived by drivers during power-on upshift events for Dual Cultch Transmission (DCT) vehicles. As part of the first study, the main factors affecting shift quality during shifting process under typical working conditions are analyzed. And taking the power-on upshift as example, dynamic model of DCT shifting process is build. An Integrated control strategy is proposed for power-on upshift, which during torque phase slipping revolving speed controller is adapted to harmonically control two clutches power switching process, and during Inertial phase engine torque is regulated to synchronize with the value of target gear while holding the oncoming clutch pressure. Oncoming clutch oil pressure gradient in torque phase and engine torque reducing target decrement in inertial phase are chosen as controlled quantity. The proximity between actual and ideal shift process is taken as fitness function. Power transmission system simulation model, shift quality evaluation model and Particle Swarm Optimization (PSO) algorithm are integrated based on Maltab/Simulink platform. The proposed integrated control strategy is optimized by PSO algorithm. Through comparison of evaluation indexes before and after optimization, the optimized control strategy could reduce the frictional loss and improve the power performance with no sacrifice of shifting comfort. So the optimized control strategy can improve the shift quality which verifies the feasibility.