# Optimization of Mode-Switching Quality of Hybrid Tractor Equipped with HMCVT
## 1 Introduction  
According to the International Energy Agency (IEA), global energy-related CO2 emissions reached a record high of 37.4 billion tons in 2023, up 1.1% from 2022. With the intensification of global climate change and the increasingly serious problem of global warming caused by greenhouse gas emissions, countries around the world have implemented more stringent emissions regulations for non-road mobile machinery, such as the European Union Stage V standard and the United States Tier 4 standard. Therefore, the development of tractors that meet low emissions standards has become an urgent need [1]. Tractors use mechanical power instead of human and animal power for farming. They are used to improve agricultural production efficiency and can be used to pull and drive operational machinery to complete various agricultural work. Tractors play an important role in agricultural road transportation and field operations. Conventional tractors usually use the engine to drive the mechanical transmission mechanism directly. As a result, the engine is in a state of low load and high emissions for a long time, the fuel economy is poor, and a tractor with a mechanical transmission structure cannot achieve stepless transmission. The shortcomings of pure electric tractors, such as high purchase cost and fast battery decay,have led to the arrival of the era of hybrid power tractors. Therefore, hybrid power as a tractor power source is the best choice at present [2]. Hybrid tractors have a variety of working modes to adapt to different working conditions. In the process of mode switching, the impact load, vibration phenomenon, and power transmission interruption have a negative impact on the smooth operation of the tractor and can even cause damage to the transmission system. In recent years, many researchers have conducted research on dynamic coordination control, clutch control, and other aspects during the mode-switching process. [PERSON] and others from the University of Technology Sydney proposed a closed-loop control strategy based on lqr. The simulation results show that this strategy can ensure maneuverability during vehicle mode switching [3]. [PERSON] and others from Purdue University proposed a unified control strategy based on torque, which can improve the driving experience [4]. [PERSON] and others from the University of Bejaia proposed two intelligent torque distribution strategies based on particle swarm optimization (PSO) and fuzzy logic control (FLC), which can reduce the transient torque during mode switching [5]. [PERSON] from Beijing Institute of Technology and others proposed a hybrid dual-flow coupled power system configuration and used the Haar wavelet decomposition method to propose a torque distribution strategy based on power prediction. The hardware-in-the-loop test verified that this control strategy can be effective, reducing torque ripple by 35% [6]. [PERSON] and others from Chongqing University proposed a neural network model based on genetic algorithms to improve the accuracy of engine torque estimation [7]. In terms of HMCVT research, [PERSON] from Ruhr University Bochum in Germany conducted in-depth research on the structure, performance, and control methods of HMCVT [8]. Scholars such as [PERSON] from Turkey's Tobu University of Economics and Technology, and [PERSON] and [PERSON] from Italy's University of Padua, analyzed the engine fuel consumption and discussed the advantages of tractors and city buses equipped with HMCVT under various working conditions [9]. [PERSON] et al. from Linkoping University in Sweden analyzed the dynamic response performance and power distribution rule of the hydraulic-mechanical continuously variable transmission system. A static decoupling multi-input to multi-output control strategy is proposed. The cross-coupling phenomenon existing in the transmission mode switching process is reduced, and the steady-state error caused by cross-coupling is eliminated by replacing the integral element with the feedforward method [10].