Research on Torque Allocation Control of Multi-Articulated Vehicle

2026-99-1123

9/11/2026

Authors
Abstract
Content
The multi-articulated vehicle uses distributed drive mode. Due to its large degree of freedom of movement and the large number of driving shafts, different torque distribution methods affect the operational stability of the vehicle, how to coordinate and distribute the torque of each driving motor has become an urgent problem to be solved. To improve drive stability of the multi-articulated vehicles, propose a layered torque allocation control strategy. The upper-layer sliding mode controller determines the required additional yaw moments of each car body based on the linear reference model, the controller is characterized by swift response and a strong ability to resist interference. The lower-level allocation module comprehensively considers the torque output limitations of the electric hub motors, the prevailing road adhesion state, and the corrective yaw moment constraints given by the upper layer, and constructs an optimization objective function centered on the uniformity and stability of tire load. The optimal distribution of driving forces for each wheel is completed by solving this function dynamically. To validate the strategy's effectiveness, a vehicle dynamics model is built in the multi-body dynamics software ADAMS/View. Using a joint simulation framework integrating ADAMS/View and MATLAB®/Simulink, the effect of the layered control strategy is evaluated in comparative simulation with uncontrolled situation under U-turn and single lane change conditions. The simulation outcomes demonstrate that, compared to uncontrolled situation, the yaw rate deviation of each car body under the torque layered control are significantly reduced, and the adhesion utilization rate of tire is also effectively controlled, thereby the driving stability is improved.
Meta TagsDetails
DOI
https://doi.org/10.4271/2026-99-1123
Citation
An, G. and Zhang, L., "Research on Torque Allocation Control of Multi-Articulated Vehicle," 2025 International Conference on Intelligent Equipment, Vehicle Engineering and Automation Control, Shenyang, China, December 5, 2025, https://doi.org/10.4271/2026-99-1123.
Additional Details
Publisher
Published
Sep 11
Product Code
2026-99-1123
Content Type
Technical Paper
Language
English