As agricultural modernization advances and environmental awareness grows, enhancing the energy efficiency and environmental performance of tractors, a core component of agricultural machinery, becomes a crucial research focus. This study centers on the series-parallel hybrid electric tractor (SPHET), analyzing its drive system structural characteristics and operational modes. The research involves developing a dynamic model for the hybrid electric tractor (HET) traction operations and proposing a real-time energy management strategy based on fuzzy logic rules (FLR). To precisely evaluate the superiority for real-time control strategies, an Energy Management Strategy based on final state-constrained dynamic programming (FSCDP) is introduced. To validate the feasibility and continuous power output capability of the proposed real-time control strategies, a hardware-in-the-loop (HIL) simulation platform for the SPHET energy management control strategy is established. Simulation results under plowing conditions show that, with the initial state of charge (SOC) of the battery set at 50%, the FLR control strategy reduces fuel consumption by 6.05% compared to the deterministic rule (DR) control strategy, resulting in a 0.57% increase in SOC. When compared with the FSCDP control strategy, both control strategies achieve the same final SOC value, and the fuel consumption of the FLR control strategy reaches 96.6% of the FSCDP level. This indicates that the energy management strategy based on FLR can effectively reduce energy consumption and is suitable for real-time application. For initial SOC values set at 30% or 80%, the FLR control strategy demonstrates lower energy consumption compared to DR. Both strategies ensure the power battery pack stays within the set upper and lower limits, ensuring the safe operation of the power battery pack while meeting continuous power demands under plowing conditions. The study results provide valuable insights and guidance for energy management in SPHET, contributing positively to the advancement of sustainable mechanized agriculture.

Electric tractors driven by dual motors have become a critical research topic in the field of pure electric tractor research. As a key component of the transmission system, the optimization of the internal parameters of the power-coupled transmission gearbox has a crucial impact on the power transmission of the whole machine. This work combines the characteristics of low speed and high torque during tractor operation, and adopts the transmission form of double motor input and double planetary group coupling output to design the transmission structure of the gearbox. Then, this paper proposes a dynamic optimization method of the transmission system based on the Improved Deep Deterministic Policy Gradient (IDDPG) algorithm, which realizes the optimization of the gear ratio of the transmission system by constructing a virtual prototype and hardware-in-the-loop simulation environment. In transport mode, the optimized gear ratios shorten the acceleration time of the tractor from 0-20 km/h by 13.6% and increase the motor efficiency by 10%; in rotary mode, the acceleration performance is improved by 28.5% and the motor efficiency is increased by 5%. The study shows that the proposed method is significantly better than the traditional static design and provides a new technical path for the intelligent optimization of the electric tractor drive train, while promoting the efficient and sustainable development of agricultural machinery.

Agricultural machinery and equipment are indispensable to realize resource utilization for high efficiency in sustainable production. It is also required for the efficient, intelligent, and environmentally friendly agricultural power machinery, due to the greenhouse gas emissions and the drastic reduction in the extraction of non-renewable resources. Fuel cell distributed drive electric tractors (FCDET) can provide a new approach to developing green agricultural machinery. However, the great challenge has posed on the traction efficiency, short range, and high hydrogen consumption. A reasonable and effective power allocation can be expected to reduce energy consumption for the high efficiency of the fuel cell system. In this study, an allocation strategy of plowing drive power was proposed for FCDET using adaptive multi-resolution analysis (AMRA). The effective decoupling between the various energy sources was also realized to reduce the frequent start-stop and the large power fluctuations of the hydrogen fuel cell. Firstly, two models were established for the fuel cell system and the total efficiency solver. The first-time reconstruction was to obtain the subsequence that effectively responded to the oscillation characteristics of the power signal using the tunable Q-factor wavelet transform (TQWT). The second reconstruction was to decompose the low-frequency subseries into several discrete sub-signals with special sparse properties using variational mode decomposition (VMD). Then, the sparrow search algorithm (SSA) was used to obtain the optimal combination of modal decomposition layers and quadratic penalty factors for VMD in real time. Finally, the second-time decomposed subsequence and sub-signals were reconstructed, according to the frequency characteristics. The reconstructed power signal was redistributed among the various energy sources. A test was carried out to verify the power allocation. The power demand information of the drive motor was acquired for FCDET plowing conditions at the China YTO Mengjin test base, taking the ET504-H prototype as the object. The plowing condition included a 0-8.7 s starting stage and an 8.7-18.0 s stable plowing stage. The demand power signal shared a large rate of change in the starting stage and a large high-frequency characteristic in the stable plowing stage. In addition, another experiment was carried out on the transmission bench in the New Energy Key Laboratory of Henan Province, in order to test the cooperative operation of permanent magnet synchronous motors (PMSM) under three power allocations. The results showed that the FCDET drive power allocation using AMRA effectively improved the energy utilization of the fuel cell system and the economy of the whole vehicle in plowing condition. The fuel cell system efficiency was improved by 8.30% and 1.82%, respectively, compared with the power-following and the first-time reconstruction. The equivalent hydrogen consumption was reduced by 35.60% and 11.86%, respectively. Meanwhile, the drive motor efficiency was improved by 2.06% and 1.27% on average; the energy consumption was reduced by 3.73% and 2.60%, respectively. This finding can provide a novel theoretical and technical approach for the development of the FCDET control system.