Studies on semitrailer stability and control development

About this project

Project description

The dynamics of articulated vehicles entail safety-critical conditions and are more complicated than those of rigid vehicles. For example, inexperienced drivers may find it difficult to control situations like caravan munching, jack-knifing, and rollover, which can result in serious accidents. The trailer’s dimensions, mass, yaw mass moment of inertia, and other characteristics, as well as the way it is attached to the tractor, all affect how stable the entire vehicle is. The project has multiple objectives. Initially, the trailer’s stability would be studied using hitch point angle, vertical force distribution, and vehicle states. Driver models for articulated vehicles (especially HMVs) differ from normal vehicles due to different trailer control requirements. How the driver can affect stability will also be explored. Further analysis of system behaviour in low-speed manoeuvres like reversing and docking would be done. A symbolic toolbox can be used to develop the mathematical model of the system for analysis. Any incipient instability can be predicted based on the trailer states (roll, sideslip, and articulation angle) or the hitch point force. Next, control strategies for stabilizing the vehicle will be developed. Due to the diverse configurations available for articulated vehicles, a reconfigurable and universal control strategy will be developed. Data-driven control methods like learning-based MPC is one such method. The method learns an approximate Gaussian model of the system through data using Koopman operators. Another method could be modeling individual trailers as independent systems and then modeling the connection as articulation constraints. Usually, decoupled yaw and roll-based controllers are used, but both motions are coupled due to weight redistribution, resulting in low control performance of one variable over another. Optimal control strategies based on coupled states will be designed to simultaneously control yaw and roll motions through active steering and braking. Torque vectoring-based control is also one area to explore, especially with the advent of electric trucks. Individual control authorities can be allocated to each tire to minimize the control effort by formulating an optimization problem based on vehicle slip and tire slip. Initial validation of these control strategies will be done using commercial simulation packages like CARSIM and final deployment on scaled articulated vehicle prototype like [1]. Further experiments will be conducted in NATRAX [2] on full-scale vehicle to validate the controller and scaled prototype results.

[1] Chen, L. K., and Y. A. Shieh. “Jackknife Prevention for Articulated Vehicles Using Model Reference Adaptive Control.” Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, vol. 225, no. 1, SAGE Publications, Sept. 2010, pp. 28–42.

[2] National Automotive Test Tracks,


Study of semitrailer stability with driver in loop.

A scaled articulated vehicle platform for testing and validation of various control strategies.

Novel stability control strategies for articulated vehicles coupling yaw and roll motion.

Information for applicants

Essential capabilities

Mathematical modeling, knowledge of vehicle systems, coding skills, good academic record and analytical skills.

Desireable capabilities

Hands-on experience in student competitions (BAJA, Formula SAE, etc.), Good technical writing skills, Knowledge of commercial software packages, Embedded system design.

Expected qualifications (Course/Degrees etc.)

Bachelor’s degree in Mechanical Engineering/Mechatronics/Automobile engineering and allied areas or a Master’s degree with application to vehicle systems/embedded systems and algorithms.

Project supervisors

Principal supervisors

UQ Supervisor

Professor Ross McAree

School of Mechanical and Mining Engineering
IITD Supervisor

Assistant professor Husain Kanchwala

Center of Automotive Research and Tribology