Real-Time Energy-Efficient Control Strategy for Distributed Drive Electric Tractor Based on Operational Speed Prediction

作者：Xiaoting Deng, Zheng Wang, Zhixiong Lu, Kai Zhang, Xiaoxu Sun, Xuekai Huang · 发表于：Agriculture · 年份：2025 · DOI：10.3390/agriculture15131398 · 被引用次数：4 · 研究领域：Electric and Hybrid Vehicle Technologies、Sensorless Control of Electric Motors、Control Systems in Engineering

This study develops a real-time energy-efficient control strategy for distributed-drive electric tractors (DDETs) to minimize electrical energy consumption during traction operations. Taking a four-wheel independently driven DDET as the research object, we conduct dynamic analysis of draft operations and establish dynamic models of individual components in the tractor’s drive and transmission system. A backpropagation (BP) neural network-based operational speed prediction model is constructed to forecast operational speed within a finite prediction horizon. Within the model predictive control (MPC) framework, a real-time energy-efficient control strategy is formulated, employing a dynamic programming algorithm for receding horizon optimization of energy consumption minimization. Through plowing operation simulation with comparative analysis against a conventional equal torque distribution strategy, the results indicate that the proposed real-time energy-efficient control strategy exhibits superior performance across all evaluation metrics, providing valuable technical guidance for future research on energy-efficient control strategies in agricultural electric vehicles.