Driving torque management model for electric tractor in field cruise condition

Researchers have developed various design methods for driving systems and control strategies for electric tractors, as well as performance analysis of key components. However, little attention has been paid to the precise management of torque requests in the top layer in consideration of factors such as the power output restrictions at motor operating temperature limits, battery state-of-charge limits, time-based torque ramp limits, and the speed-dependent torque capability of the motor. In this paper, we developed a driving torque management model on the upper layer of driving systems for electric tractors based on the common functional blocks related to the decision of target torque in electric tractor control. In order to meet the field operation requirements and improve the quality of work, the input signals were calibrated to the desired cruise speed and further converted to the motor target revolving speed. According to the deviation between the actual revolving speed and the target revolving speed, the motor target output torque was calculated to balance the required motor power with the work load. Further considering the impacts on the electric tractor caused by the torque fluctuations during the cruise operation, the motor maximum torque available at the current revolving speed, the influence of the over-temperature of the driving system and the over-discharge of the battery, models of time-based ramp limitation of target torque, motor's speed-based maximum torque limitation and load reduction protection under extreme conditions were constructed in turn. The electric tractor model consisting of tractor dynamic model, battery model, and electric motor model was also built. A tractor control unit to support the torque demand management model was designed, and a hardware-in-the-loop real-time test platform was built with dSPACE. The parameters in the torque management model were calibrated separately, and the output characteristics of the drive system under traction conditions were tested. The results showed that the actual vehicle speed tracked the expected cruising speed steadily during the traction operation. The tracking error mainly depended on the degree of slip of the driving wheels. When the expected speed changed, the actual vehicle speed smoothly transited to the expected value according to the calibrated climbing rate. During the operation, the model output torque always stayed within the motor torque capacity, and kept a small change rate of not more than 35 N·m/s, which led to more gentle variations of motor torque compared with the original without ramp limitations. When the battery voltage dropped below the over-discharge threshold, the management model scaled down the target torque in time by 10%-27% according to the degree of undervoltage, which therefore kept the battery voltage always above the safe level. The driving torque demand management model built in this paper can provide a technical reference for tractor control unit designs of electric tractors.