Abstract:An automatic control strategy for forward speed in the planting process is proposed to improve the fuel economy and reduce the labor intensity of drivers. Models of tractors with power-shift transmission (PST) and a precise pneumatic planter with an electric-driven seed metering device are built as research objects and simulated using Matlab with Simulink. The economic comprehensive control strategies for forward speed, including gear-shift schedule and cruise control strategy, are developed. Four levels contr… Show more
“…As can be seen from equation ( 5), disturbance is added as an extended state and it is a real time status variable. What's more, the disturbance is estimated according to equation (7) and the estimated disturbance play a role during the controlling process as part of the controller output which can be referenced as equation (11).…”
Section: Active Disturbance Rejection Controller Designmentioning
A modified sliding mode active disturbance rejection control (MSMADRC) position system is designed for small-sized tractors to solve the longer shift time and reduced shifting quality because of the inaccurately motor control used for the automatic mechanical transmission (AMT) gear shift actuator. Firstly, the control model of the motor with total disturbance is established. Then an extended observer is presented to monitor the unmodeled dynamics and various disturbances of the system in real time, at the same time the extended state and the system feedback variables are constructed as the system variables of the sliding mode control (SMC) algorithm. Secondly, a sliding mode surface instead of the nonlinear control law in the active disturbance rejection control (ADRC) algorithm is designed, which realizes the fast and accurate tracking of the position. What's more, the stability of the control system is proved by Lyapunov theory. Lastly, the simulation results demonstrate that the position control precision by MSMADRC is higher 37% than by SMC and higher 75% than by ADRC. Furthermore, the response speed of MSMADRC is the fastest, it only takes about 0.7s.
“…As can be seen from equation ( 5), disturbance is added as an extended state and it is a real time status variable. What's more, the disturbance is estimated according to equation (7) and the estimated disturbance play a role during the controlling process as part of the controller output which can be referenced as equation (11).…”
Section: Active Disturbance Rejection Controller Designmentioning
A modified sliding mode active disturbance rejection control (MSMADRC) position system is designed for small-sized tractors to solve the longer shift time and reduced shifting quality because of the inaccurately motor control used for the automatic mechanical transmission (AMT) gear shift actuator. Firstly, the control model of the motor with total disturbance is established. Then an extended observer is presented to monitor the unmodeled dynamics and various disturbances of the system in real time, at the same time the extended state and the system feedback variables are constructed as the system variables of the sliding mode control (SMC) algorithm. Secondly, a sliding mode surface instead of the nonlinear control law in the active disturbance rejection control (ADRC) algorithm is designed, which realizes the fast and accurate tracking of the position. What's more, the stability of the control system is proved by Lyapunov theory. Lastly, the simulation results demonstrate that the position control precision by MSMADRC is higher 37% than by SMC and higher 75% than by ADRC. Furthermore, the response speed of MSMADRC is the fastest, it only takes about 0.7s.
“…The engine static torque is a function of engine speed and throttle level [10,29]. The mathematical model of engine torque is in Equation ( 7) for a 95 kW engine.…”
This study is focused on the estimation of fuel consumption of the power-shift transmission (PST) tractor based on PTO (power take-off) dynamometer test. The simulation model of PST tractor was developed using the configurations and powertrain of the real PST tractor. The PTO dynamometer was installed to measure the engine load and fuel consumption at various engine load levels (40, 50, 60, 70, 80, and 90%), and verify the simulation model. The axle load was also predicted using tractor’s specifications as an input parameter of the simulation model. The simulation and measured results were analyzed and compared statistically. It was observed that the engine load, as well as fuel consumption, were directly proportional to the engine load levels. However, it was statistically proved that there was no significant difference between the simulation and measured engine torque and fuel consumption at each load level. The regression equations show that there was an exponential relationship between the fuel consumption and engine load levels. However, the specific fuel consumptions (SFC) for both simulation and measured were linear relationships and had no significant difference between them at each engine load level. The results were statistically proved that the simulation and measured SFCs were similar trends. The plow tillage operation could be performed at the gear stage of 7.65 km/h with higher working efficiency at low fuel consumption. The drawback of this study is to use a constant axle load instead of dynamic load. This study can provide useful information for both researchers and manufacturers related to the automated transmission of an agricultural tractor, especially PST tractor for digital farming solutions. Finally, it could contribute to the manufacturers developing a new agricultural tractor with higher fuel efficiency.
“…In modern agriculture, mechanization, automation, and precision are the development trends [1]. As the main power source of farm operation, the automation level of the agricultural tractor is crucial to precision agriculture [2,3]. Carrying different implements and tools, general purpose agricultural tractors are often used in ploughing, harrowing, sowing, material movement, etc.…”
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