Optimizing the Control of the Hydraulic Driving System for the Power Shift Gearbox of a Cotton Picker Based on Dual Working Conditions

Abstract

In response to the issues of slow dynamic response, uneven shifting, and strong jolting during the starting and shifting operations of the cotton picker, we established a model for automatic power shifting control. We proposed optimization strategies using the Statechart logic control method and BP neural network control method. Different control effects were analyzed concerning pressure, flow rate, motor speed, vehicle speed, impact degree, and slip-grinding work. The results showed that the Statechart logic control method increased the response time of the flow rate by 46.67% during the starting process, with a good linear characteristic during the variation. It reduced the impact during starting and shifting by 38.57% and 67%, and the sliding friction power during starting and shifting by 51.95% and 33.33% respectively. The BP neural network control method reduced the pressure overshoot during starting and shifting by 25% and 30.77%, respectively, demonstrating better robustness. The pump, motor speed, and vehicle speed showed smooth growth after starting and shifting, with faster vehicle speed response during the starting process. Additionally, the vehicle speed overshoot during shifting significantly decreased, ensuring overall performance that meets the operational requirements of the cotton picker. This finding holds practical significance for the advancement of control strategy optimization and the development of the control system for the powershift gearbox in cotton pickers.