Quality and Efficiency of a Brain-Smart Electric Tractor Unit Operation Control Mechanism: Instant Information Interaction and Collaborative Task Management

Abstract

Electric tractors (ETs) with mounted implements form operating units. There are significant differences in parameters such as shape, firmness, and moisture content of the soil in contact with the tractor and implements when working in complex terrains such as field stubble, waterlogged silt, and loose/firm terrain. These differentiated dynamics prevent cooperation between ETs and operating implements under independent control, resulting in poor quality operations and low energy efficiency. We propose a control mechanism for ETs and implements to achieve full life cycle management of collaborative control tasks, instantaneous intertask interaction, and a multitask synchronization mechanism. To address the internal redundant communication problems caused by traditional distributed microcontrol units, we break through the underlying technology of unit data processing and interaction and develop an integrated high-performance controller structure with high processing capacity and high- and low-speed communication interfaces. On the basis of hierarchical stepwise control theory, a hierarchical real-time operating system is designed. This system realizes a preemptive kernel response of computational tasks and competitive–collaborative synchronization among tasks; overcomes the low-latency response of collaborative control tasks, instantaneous information interaction, and multitask synchronization problems; and provides system-level support for deep collaborative operation control of units. To demonstrate and validate the proposed collaborative control mechanism, a plowing collaborative operation management strategy is designed and deployed. The experimental results show that the communication delay of collaborative tasks is as low as 83 μs, the solution time of complex collaborative equations is as low as 46 ms, the mechanical efficiency of the ET is increased by 9.07%, the efficiency of the drive motor is increased by 9.72%, the stability of the operation speed is increased by 106.25%, and the stability of the plowing depth reaches 94.98%. Our work meets the hardware and software requirements for realizing complex collaborative control of ET units and improves the operational quality and operational energy efficiency in real vehicle demonstrations.