Trajectory Tracking and Driving Torque Distribution Strategy for Four-Steering-Wheel Heavy-Duty Automated Guided Vehicles

A four-steering-wheel heavy-duty Automated Guided Vehicle (AGV) is prone to lateral instability and wheel slippage during acceleration, climbing, and small-radius turns. To address this issue, a trajectory tracking strategy considering lateral stability and an optimal driving torque distribution strategy considering load transfer and tire adhesion coefficient are proposed. Firstly, a three-degree-of-freedom AGV trajectory tracking model is established, tracking error and sideslip angle are incorporated into the cost function, and an improved model predictive trajectory tracking controller is proposed. Secondly, the longitudinal and yaw dynamic model of AGV is established, and vertical load transfer is analyzed. With the goal of minimizing tire adhesion utilization rate, quadratic programming is used for the optimal distribution of driving torque. Finally, through co-simulation using ADAMS and MATLAB on a narrow “climbing straight+ S-curve” road, the maximum tracking error is 0.0443 m. Compared to the unimproved model predictive control and average driving torque distribution strategy, the sideslip angle is reduced by 58.18%, the maximum tire adhesion utilization rate is reduced by 6.62%, and climbing gradeability on wet roads is enhanced.

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Publication Details

Journal
Machines
Published
2025-05-01
DOI
https://doi.org/10.3390/machines13050383
Primary Topic
Vehicle Dynamics and Control Systems
Type
article
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article

Trajectory Tracking and Driving Torque Distribution Strategy for Four-Steering-Wheel Heavy-Duty Automated Guided Vehicles

Sanxing Chen, Xia Li, Xiaojie Chen, Chengming Wang et al.
Machines
Vehicle Dynamics and Control Systems
article

Trajectory Tracking and Driving Torque Distribution Strategy for Four-Steering-Wheel Heavy-Duty Automated Guided Vehicles

Sanxing Chen, Xia Li, Xiaojie Chen, Chengming Wang, Benxue Liu
article en

Abstract

A four-steering-wheel heavy-duty Automated Guided Vehicle (AGV) is prone to lateral instability and wheel slippage during acceleration, climbing, and small-radius turns. To address this issue, a trajectory tracking strategy considering lateral stability and an optimal driving torque distribution strategy considering load transfer and tire adhesion coefficient are proposed. Firstly, a three-degree-of-freedom AGV trajectory tracking model is established, tracking error and sideslip angle are incorporated into the cost function, and an improved model predictive trajectory tracking controller is proposed. Secondly, the longitudinal and yaw dynamic model of AGV is established, and vertical load transfer is analyzed. With the goal of minimizing tire adhesion utilization rate, quadratic programming is used for the optimal distribution of driving torque. Finally, through co-simulation using ADAMS and MATLAB on a narrow “climbing straight+ S-curve” road, the maximum tracking error is 0.0443 m. Compared to the unimproved model predictive control and average driving torque distribution strategy, the sideslip angle is reduced by 58.18%, the maximum tire adhesion utilization rate is reduced by 6.62%, and climbing gradeability on wet roads is enhanced.

MachinesVol. 13(5)
Zhengzhou University (CN)
Openalex Percentile: Top 91%
Vehicle Dynamics and Control Systems
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