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

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 operation...

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Bibliographic Details
Main Authors: Xiaoting Deng, Zheng Wang, Zhixiong Lu, Kai Zhang, Xiaoxu Sun, Xuekai Huang
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Agriculture
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Online Access:https://www.mdpi.com/2077-0472/15/13/1398
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Summary: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.
ISSN:2077-0472