Equivalent consumption minimization strategy based on global optimization of equivalent factor for hybrid tractor

Area of Science:

• Agricultural Engineering
• Automotive Engineering
• Control Systems

Background:

• Increasing emission standards and labor shortages drive demand for high-horsepower, electrified tractors.
• Hybrid tractors require advanced transmissions like the hydromechanical continuously variable transmission (HMCVT) to meet operational demands.

Purpose of the Study:

• To design and optimize a control strategy for HMCVT in hybrid tractors.
• To improve fuel economy and motor auxiliary capability by optimizing battery energy usage.

Main Methods:

• Developed an equivalent factor global optimization model for HMCVT.
• Utilized a genetic algorithm to optimize the equivalent factor (S) offline based on operating mileage and initial battery state of charge (SOC).
• Verified the control strategy using MATLAB/Simulink and hardware-in-the-loop (HIL) tests.

Main Results:

• The optimized control strategy allows for extended operation in charge-depleting (CD) mode.
• Maximized the utilization of battery energy throughout the entire operation cycle.
• Achieved fuel economy improvements of 2.939% (Simulink) and 3.909% (HIL).

Conclusions:

• The proposed control strategy effectively enhances the auxiliary role of the electric motor in hybrid tractors.
• Optimizing the equivalent factor of HMCVT significantly reduces tractor fuel consumption.
• The strategy is validated for practical application in agricultural machinery.