Dynamic Control Of Tractor Power-shifting And Power-reversing Process

PST?power-shifting transmission?is one of the important directions in the research of agricultural machinery intelligentization.The principle of PST is controlling the wet clutch switching to realize power shifting.It can effectively reduce the driver's operational complexity and reduce the burden on the driver.The main problem in the development of the transmission is the shifting process control strategy,which is the hot research direction of agricultural machinery in recent years.This paper takes Dongfanghong part power-shift transmission as the research object.First,the PST principle and transmission characteristics is analyzed,the power shifting and reversing control strategy formulation is proposed,and finally the shifting quality is optimized.The main research contents are as followings:?1?The PST shifting commutation principle is introduced and the PST transmission characteristics is analyzed.The main component model of the tractor transmission system is established.According to the bench test data,the engine numerical model is determined.According to the torque transmission characteristics of the wet clutch under different working conditions,the clutch dynamics model is established.Finally,considering the complexity of soil resistance,based on the experimental data and empirical values,the resistance model under the working conditions and transportation conditions of the tractor is established.?2?The power-shifting process is divided into a single pair of clutch shifting and two pairs of clutch shifting.Firstly,for the shifting process of the single pair of clutches to switch,the torque transfer dynamics equation between clutch switching is analyzed in depth,and the shifting process is divided into five stages,the shifting process Matlab/simulink simulation platform is built.The torque phase and inertia phase clutch and engine control strategy are designed.For the characteristics of diesel engine torque variation range during the speed change process,the oil pressure control strategy of the on-coming clutch on synchronization phase is designed to reduce the sudden change of torque during the engagement.Secondly,for the problem of shifting process of the two pair of clutches switching,it is determined that the shifting process is divided into two single-pair clutch switching control processes,and the optimal clutch switching timing is obtained according to the engine speed change requirements.Based on the simulation platform,the single-pair clutch switching and two pair clutch switching control strategies are simulated and verified.The results show that the control strategy can better fulfill the requirements.?3?The torque transmission characteristics of the clutch switching process in the motion inverter process are analyzed in depth.The process is also divided into five stages.The dynamics model of the motion inverter process is established,and the Matlab/simulink simulation platform of the motion inverter is built.The clutch hydraulic pressure and engine torque control strategy of torque phase,inertia phase and clutch synchronization phase are designed.The motion inverter process control strategy is verified on the simulation platform.The results show the effectiveness of the control strategy.?4?According to the tractor working conditions and transportation conditions,the shifting and motion inverting quality evaluation system under working conditions and transportation conditions was established.For the control strategy,the inertia phase?upshift?,inertial phase?downshift?engine PID control parameters,synchronization phase custom parameters are optimized,and the shift quality evaluation index is used as the objective function,and NSGA-II optimization algorithm is used to establish the shift quality optimization method.The condition of the heavy-duty full throttle 1^st upshift to2^nd gears,4^th downshift to 3^rd gears is selected to verify the optimization method.The simulation results show that the optimized shifting quality is significantly improved before optimization.