Dry-state single-atom Pt engineering on crystalline carbon nitride for integrated hydrogen evolution and neuromorphic computing

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.