Design method of dual-motor electric tractor drive system based on mass constraint algorithm under uncertainty using mass

The tractor using mass is uncertain at the beginning of design, which results in the inability to accurately obtain the driving index constraints for the tractor. To solve the above problems, this paper proposes a parameter design method of dual-motor electric tractor drive system under uncertainty using mass. First, to solve the problem of unable to obtain the driving index constraints for the tractor due to uncertainty using mass, a tractor mass constraint algorithm is proposed and then the algorithm convergence is proved by numerical derivation. Next, to optimize the operating efficiency of the power source, an instantaneous optimization algorithm is adopted to optimize the torque distribution of the dual-motor and the power coupling device gear ratio. Finally, a parameter design method is formed by fusing the tractor mass constraint algorithm, the instantaneous optimization algorithm and the genetic algorithm. To verify the effectiveness of the method, the rule design method is used as a comparison method with the simulation and the HIL test are carried out under plowing conditions. The using mass and energy consumption resulting from the parameter design method are reduced by 8.54% and 4.15%, respectively, comparing with the rule design method. • A tractor mass constraint algorithm is proposed to solve the driving index constraints problem. • The tractor mass constraint algorithm convergence is proved by numerical derivation. • A new design method of drive system is proposed under uncertainty using mass. • The drive system parameters and using mass are collaboratively optimized.