Research on constant speed cruise control of 4WID high ground clearance self-propelled electric sprayer

doi:10.12398/j.issn.2096-7217.2024.02.003

Abstract

Abstract:

In response to the problems of poor speed stability and degraded spraying quality of 4WID high-clearance self-propelled electric sprayers caused by changes in external road gradients and lowered payloads resulted from internal liquid spraying under complex operating conditions， a fixed-speed cruise control algorithm with a layered control approach is proposed based on an analysis of the structure and longitudinal dynamic characteristics of 4WID high-clearance self-propelled electric sprayers. The control algorithm model receives the user-specified desired speed and inputs acceleration control signals to the longitudinal dynamic system model through algorithmic calculation to realize the tracking of the sprayer to the desired speed. The structure of the longitudinal dynamic system mainly includes five parts： the inverse longitudinal kinematic model， the acceleration-braking switching model， the torque allocation model， the motor model， and the longitudinal kinematic model. The inverse longitudinal kinematic and longitudinal kinematic models of the sprayer can be obtained by analyzing the force on the body of the sprayer under the condition of driving on a slope. Meanwhile， in order to establish a reasonable four-wheel torque allocation strategy， the analysis is conducted under the condition that the sprayer has both pitching and tilting motions of the body， and the slip rate of each driving wheel is used as the basis for allocation， ensuring the optimal torque moment of each wheel under different operating conditions and ensuring the balanced power of the sprayer. The speed cruise control adopts a layered control approach， which realizes the effective tracking of the speed of the spraying machine through the establishment of the upper PID control and the lower fuzzy PID control. By defining fuzzy control rules， the PID parameters of the lower layer controller are automatically adjusted to ensure the good adaptability of the speed cruise control system to various complex operating conditions. A control model is established using Matlab/Simulink， and the control system is simulated and analyzed. The experimental results show that the designed speed cruise control system can effectively control the speed of the sprayer under typical operating conditions. Specifically， the performance of the system is excellent under conditions of external disturbance and self-weight variation， with overshoot less than 2%， response time less than 0.2 s， and steady-state error approaching 0， verifying the accuracy of the control algorithm used.

Key words: self-propelled electric sprayer, cruise control system, four-wheel independent drive, longitudinal dynamics model, fuzzy PID control

CLC Number:

S224.3

HU Chenwei, CHEN Yu, CAO Jiayu, CHEN Yuxiang, ZHANG Shuo, CHEN Jun. Research on constant speed cruise control of 4WID high ground clearance self-propelled electric sprayer[J]. Journal of Intelligent Agricultural Mechanization, 2024, 5(2): 19-32.

Figures/Tables 25

Figure 1 Force diagram of the sprayer in spatial coordinate system

Figure 2 Longitudinal dynamics simulation system of the sprayer

Figure 3 Inverse longitudinal dynamics module

Figure 4 Drive and brake switching relationship module

Figure 5 Two-wheel model of the sprayer from a pitch angle view

Figure 6 Two-wheel model of the sprayer from a roll angle view

Figure 7 Four-wheel torque distribution strategy

Figure 8 Wheel hub motor control model

Figure 9 Overall motor module

Table 1 Motor control model regulator parameters

参数	转速调节器ASR	电流调节器ACR
比例调节系数k_p	2.5	3.8
积分调节系数k_i	0.01	0.007

Figure 10 Longitudinal dynamics model of the sprayer

Figure 11 Simulation block diagram of the longitudinal dynamics system for the sprayer's cruise control

Figure 12 Standard cruise control structure

Figure 13 Overall scheme of the cruise control system for the sprayer

Figure 14 Upper-level controller model

Figure 15 Fuzzy PID control structure

Figure 16 Membership functions of input and output variables for fuzzy PID control of cruise control

Table 2 Adjustment table for control rules of parameters Kp， Ki， and Kd

e	e_c
e	NB	NM	NS	ZO	PS	PM	PB
NB	PB/NB/PS	PB/NB/NS	PM/NM/NB	PM/NM/NB	PS/NS/NB	ZO/ZO/NM	ZO/ZO/PS
NM	PB/NB/PS	PB/NB/NS	PM/NM/NB	PS/NS/NM	PS/NS/NM	ZO/ZO/NS	NS/ZO/ZO
NS	PM/NB/ZO	PM/NM/NS	PM/NS/NM	PS/NS/NM	ZO/ZO/NM	NS/PS/NS	NS/PS/ZO
ZO	PM/NM/ZO	PM/NM/NS	PS/NS/NS	ZO/ZO/NS	NS/PS/NS	NM/PM/NS	NM/PM/ZO
PS	PS/NM/ZO	PS/NS/ZO	ZO/ZO/ZO	NS/PS/ZO	NS/PS/ZO	NM/PM/ZO	NM/PB/ZO
PM	PS/ZO/PB	ZO/ZO/NS	NS/PS/NS	NM/PS/PS	NM/PM/PS	NM/PB/PS	NB/PB/PB
PB	ZO/ZO/PB	ZO/ZO/PM	NM/PS/PM	NM/PM/PM	NM/PM/PS	NB/PB/PS	NB/PB/PB

Figure 17 Corresponding characteristic curves of input and output variables

Figure 18 Simulation of the fuzzy PID control system for constant speed cruising of a sprayer

Figure 19 Torque distribution of individual wheel hub motors under different operating conditions

Figure 20 Speed tracking curve

Figure 21 Acceleration output curve

Figure 22 Speed tracking curve

Figure 23 Acceleration output curve

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