Hydro-mechanical transmission (HMT) is one type of mechanical-hydraulic stepless transmission. There is a better tradeoff between the stepless speed regulation of hydraulic and efficient speed change of mechanical transmission. Clutch control is closely related to the appropriate timing of engagement and separation, due to the great influence of disturbance on the quality of the shifting process. It is necessary to clarify the shifting clutch for the higher quality of HMT during shifting. However, a strong nonlinear system is coupled with the HMT under modeling error and external load disturbance. In this study, the shifting clutch pressure control was proposed using disturbance feedforward compensation. The dynamical model of shifting and the mathematical model of the clutch in the sliding were also established using the composition and working principle of HMT. The optimal linear-quadratic model was achieved, where the jerk, sliding power, and shifting time were taken as the evaluation indexes during shifting, while the performance index of the quadratic function was the state control variable. The total disturbance during shifting was also estimated to rapidly respond to the disturbance using the first-order disturbance observer. The compensation gain of disturbance was introduced into the feedforward term of the controller, in order to realize the disturbance feedforward compensation. After that, the feedforward compensation gain was obtained, according to the disturbance estimate $\hat{d}$ and compensation coefficient k_d . Then, the optimal controller was designed to suppress the disturbance of the shifting process for the optimization of the quadratic index. The functional weight coefficients were set as q =1, and r =0.1, the equivalent moment of the inertia of the HMT input shaft, clutch C2 driven disc, quantitative motor output shaft, and HMT output shaft were set as 0.02, 0.04, 0.05, and 1 kg·m², respectively, while the equivalent damping coefficients were set as 0.015, 0.2, 0.018, and 0.016 N·m·rad/s, respectively. The co-simulation of HMT during shifting with disturbance was carried out in the AMEsim and Simulink software. The coefficients, k_x , k_h , and k_d of the optimal control variables were calculated by the simulation model in real time. The simulation indicated that the improved control system reduced the maximum disturbance by 48.9%, the jerk by 27.8%, the sliding friction work by 29.6%, and the shifting time by 15.3%, compared with the control without disturbance feedforward compensation. Better control was achieved in the time-varying disturbance of the shifting process. The test of the hydraulic mechanical transmission was also carried out on the test bench, in order to verify the effectiveness of the control system for the better quality of HMT during shifting. Among them, the output load torque and input speed were set as 1 000 N·m, and 1 500 r/min, respectively. Test results show that there was a consistent trend of experiment and simulation, although some error was under control. Consequently, the disturbance feedforward compensation greatly reduced the maximum jerk and shifting time, while suppressing the time-varying disturbance during shifting. The disturbance of the shifting was effectively estimated to better improve the shift quality of HMT under the disturbance working condition. The findings can provide a strong reference for the engineering application of hydraulic mechanical transmission. transmission.

Tractors have been widely used as agricultural machinery in the field. This study aims to improve the overall economy of tractors using hydro mechanical continuously variable transmission (HMCVT). An economic control strategy was also developed to consider the transmission of the tractor. The engine and multi-stage HMCVT efficiency model were established using polynomial fitting and meshing power. The optimal economic control was also provided after optimization. A control strategy was established to balance the significant differences in the transmission efficiency among multiple stages of HMCVT with different gear ratios, taking the ratio of engine fuel consumption rate to HMCVT efficiency as the evaluation index. Simulated annealing (SA) and genetic algorithm (GA) were combined to utilize the natural evolution of GA, gradually improving the quality of economic parameter optimization; At the same time, the SA algorithm was used to avoid premature convergence with the increasing iteration times. Arithmetic crossover and non-uniform mutation were used to accurately obtain the most economical engine speed, torque, and transmission ratio. The new population G' was generated, when the GA globally optimized the initial population G. SA algorithm was then used to locally optimize the population G'. The Metropolis criterion was used to calculate the individual acceptance probability under isothermal conditions. Once the fitness function of the offspring population G' was better than G, G' was accepted as the optimal solution. A cooling operation was performed until the global optimal solution was obtained. The best overall economy of the machine was achieved by storing the optimal speed ratio, engine speed, and torque of the load in the control unit. The engine operating point and transmission speed ratio were regulated, according to the requirements of tractors. The combinatorial optimization was verified to compare the iterative performance of the SA algorithm and GA. Two algorithms fell into the local optima after 53 iterations, indicating their high accuracy of the combinatorial optimization. Finally, the control strategy of optimization was also validated to improve the overall fuel economy of the tractors. A vehicle model was constructed to simulate using the Simulink platform, compared with the traditional control strategy. The HMCVT speed ratio of the control strategy was verified using a test bench. The simulation results show that the control strategy was achieved in an average transmission efficiency of 0.93 for the tractor under plowing, which increased by 0.06 and 6.8%. The average fuel consumption rate was 279 g/(kW·h), which was reduced by 8 g/(kW·h) and 2.7%. The transmission efficiency of the tractor was also improved to save the fuel consumption. The HMCVT speed ratio was relatively low at the low speed and high loading. The tractor was output the sufficient torque after optimization. There was great consistency in the simulation and experiment. The control strategy effectively improved the overall economy of the tractor, while reasonably matching the working states of the engine and transmission. The findings can provide a theoretical basis for the engineering application and economic control strategy of HMCVT tractors.