In this study, a dual-input coupling powertrain system (DICPS) was proposed to improve the energy utilization efficiency of pure electric tractors (PETs). The working principles of the DICPS under different modes were analyzed and dynamic models were established. To study the influence of changing key parameters in the DICPS on the economic performance of PETs, a parameter-matching design method was proposed and the feasible region of the design parameters was determined according to the tractor’s dynamic performance. In addition, we put forward an energy management strategy (EMS) based on the optimal system efficiency and a dual-motor-driven electric tractor (DMET) model was built in MATLAB/Simulink. The simulation results revealed that different parameter configurations of DICPS will lead to significant changes in overall efficiency, with a maximum difference of 6.6% (under a rotary tillage cycle). We found that the optimal parameter configuration for the DMET under two typical working conditions was PDR = 0.5, k = 1.6. Compared with the single-motor powertrain system (SMPS), the DICPS with the optimal configuration of key parameters can significantly improve overall efficiency by about 9.8% (under a plowing cycle).

Powertrain parameter matching and optimal design of dual-motor driven electric tractor

The tractor is the primary power device of the agricultural production process. For the problem that the traditional electro-hydraulic hitch control method for tractors cannot simultaneously meet the requirements of maintaining a constant ploughing depth and improving traction performance and electric tractor overall efficiency, this paper proposes a hydraulic cylinder pressure control method of the electro-hydraulic hitch system for electric tractors. We establish a tractor-implement system dynamic model, calculate the rear axle load of the tractor in real-time according to the actual working parameters under the premise of ensuring the constant ploughing depth, construct a traction performance objective optimization function, and use the genetic algorithm to solve the optimal hydraulic cylinder pressure value of the electro-hydraulic hitch system. Hardware-in-the-loop (HIL) simulation results show that the electric tractor under the traditional position control method and the hydraulic cylinder pressure control method has an average wheel slip of 18.50% and 16.93%, an average traction efficiency of 71.35% and 73.08%, and an average overall efficiency of 50.81% and 52.40%. The hydraulic cylinder pressure control method proposed in this paper reduces the wheel slip by 9.27%, increases the traction efficiency by 2.42%, improves the electric tractor overall efficiency by 3.13%, and reduces the electric tractor overall energy loss by 7.67% compared with the traditional position-control method. Therefore, the hydraulic cylinder pressure control method of the electro-hydraulic hitch system proposed in this paper can achieve the purpose of effectively improving tractor traction performance and reducing tractor energy loss while maintaining a constant ploughing depth. This study offers technological references for electric tractors to improve traction performance and reduce the overall energy loss of electric tractors.

The driving tasks of a maize harvester are exhausting because of the varying soil, maize conditions, and the long working time. Operators must adjust and optimize the internal settings of the harvester to modify the working parameters and reduce the harvest loss. In this paper, an intelligent control system for maize picking harvest was investigated for automatic adjustment and minimization of maize picking losses. A prediction model based on experimental data was used to predict the maize picking loss rate, and the rotational speed of the pulling rollers, operating speed, and header height were optimized to minimize the maize picking loss. The intelligent control system allows use of manual or automatic controls; the controller adjusts the rotational speed of pulling rollers, the operating speed, and header height based on the measured picking losses in automatic mode. The designed automatic control system comprises faster and slower loops. The fuzzy proportional–integral–derivative (PID) method is used to optimize the rotational speed of pulling rollers and the operating speed in the faster loop, and the PID method is used to regulate the header height in the slower loop. Field experiments were conducted to evaluate the effectiveness and stability of the system. The system test results showed that all working parts respond quickly, and the overshoot and steady-state errors of each working part were relatively small. Regardless of the load condition, the established control strategy could optimize each working parameter of the maize harvester. In experiments, maize picking loss rates of 1.676% and 1.386% were obtained, which meet the requirements of maize harvesting.