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This paper presents an integrated design method for active trailer steering (ATS) systems of articulated heavy vehicles (AHVs). Of all contradictory design goals of AHVs, two of them, i.e. path-following at low speeds and lateral stability at high speeds, may be the most fundamental and important, which have been bothering vehicle designers and researchers. To tackle this problem, a new design synthesis approach is proposed: with design optimization techniques, the active design variables of ATS systems and passive design variables of trailers can be optimized simultaneously; the ATS controller derived from this approach has two operational modes, one for improving lateral stability at high speeds and the other for enhancing path-following at low speeds. To demonstrate the effectiveness of the proposed approach, it is applied to the design of an ATS system for an AHV with a tractor and a full trailer.

This paper presents nonlinear bifurcation stability analysis of articulated vehicles with active trailer differential braking (ATDB) systems. ATDB systems have been proposed to improve stability of articulated vehicle systems to prevent unstable motion modes, e.g., jack-knifing, trailer sway and rollover. Generally, behaviors of a nonlinear dynamic system may change with varying parameters; a stable equilibrium can become unstable and a periodic oscillation may occur or a new equilibrium may appear making the previous equilibrium unstable once the parameters vary. The value of a parameter, at which these changes occur, is known as “bifurcation value” and the parameter is known as the “bifurcation parameter”. Conventionally, nonlinear bifurcation analysis approach is applied to examine the nonlinear dynamic characteristics of single-unit vehicles, e.g., cars, trucks, etc.

An optimal preview controller is designed for active trailer steering (ATS) systems to improve high-speed stability of articulated heavy vehicles (AHVs). AHVs' unstable motion modes, including jack-knifing and rollover, are the leading course of highway accidents. To prevent these unstable motion modes, the optimal controller, namely the compound lateral position deviation preview (CLPDP) controller, is proposed to control the steering of the front and rear axle wheels of the trailing unit of a truck/full-trailer combination. The corrective steering angle of the trailer front axle wheels is determined using the preview information of the lateral position deviation of the trajectory of the axle center from that of the truck front axle center. In turn, the steering angle of the trailer rear axle wheels is calculated considering the lateral position deviation of the trajectory of the axle center from that of the trailer front axle.

This paper examines the performance of different active control strategies for improving lateral stability of car-trailer systems using numerical simulations. For car-trailer systems, three typical unstable motion modes, including trailer swing, jack-knifing and roll-over, have been identified. These unstable motion modes represent potentially hazardous situations. The effects of passive mechanical vehicle parameters on the stability of car-trailer systems have been well addressed. For a given car-trailer system, some of these passive parameters, e.g., the center of gravity of the trailer, are greatly varied under different operating conditions. Thus, lateral stability cannot be guaranteed by selecting a specific passive parameter set. To address this problem, various active control techniques have been proposed to improve handling and stability of car-trailer systems. Feasible control methods involve active trailer steering control (ATSC) and active trailer braking (ATB).

Vehicle simulators are often used for vehicle system development and driver behaviour study. The target of this study is to design and evaluate an Active Trailer Steering (ATS) system for a Long Combination Vehicle (LCV) with mutiple trailers using a real-time vehicle simulator. A linear yaw-plane LCV model is generated to derive an optimal ATS controller. Then, the controller is reconstructed in LabVIEW and integrated with a vehicle model for a B-train double from TruckSim. The Driver-Software-in-the-Loop (DSIL) real-time simulations are conducted with the vehicle simulator. The DSIL real-time simulations indicate that the ATS controller can effectively improve the LCV's low-speed maneuverability and high-speed stability under the test maneuvers of a low-speed 90-degree turn and a high-speed single-lane change, respectively.

Ensuring the lateral stability and handling of a car-and-trailer combination remains one of the challenges in safety system design and development for articulated vehicles. This paper reviews the state-of-the-art approaches for car-trailer lateral stability control. A literature review covering the effects of external factors, such as aerodynamic forces, tire forces, and road & climatic conditions, is presented. To address the effects of these factors, researchers have previously investigated numerous passive and active safety control techniques. This paper intends to identify the inadequacies of the passive safety approaches and analyzes promising active-control schemes, such as active trailer steering control (ATSC), active trailer braking (ATB) and model reference adaptive controller (MRAC). A comparative study of these control strategies in terms of applicability and cost effectiveness is performed.

This paper presents a robust active trailer steering (ATS) controller for car-trailer combinations. ATS systems have been proposed and explored for improving the lateral stability and enhancing the path-following performance of car-trailer combinations. Most of the ATS controllers were designed using the linear quadratic regulator (LQR) technique. In the design of the LQR-based ATS controllers, it was assumed that all vehicle and operating parameters were constant. In reality, vehicle and operating parameters may vary, which may have an impact on the stability of the combination. For example, varied vehicle forward speed and trailer payload may impose negative impacts on the directional performance of the car-trailer combination. Thus, the robustness of the conventional LQR-based ATS controllers is questionable. To address this problem, we propose a gain-scheduling LQR-based ATS controller.

The phase-plane analysis technique has become a powerful tool for analyzing lateral stability of single-unit vehicles. Articulated vehicles, such as car-trailer combinations, consist of multiple vehicle units. Multi-unit vehicles exhibit unique dynamic features compared against single-unit vehicles. For example, a car-trailer may exhibit one of the three unstable motion modes, i.e., jack-knifing, trailer sway and rollover. Considering the distinguished configurations and dynamic features of articulated vehicles, it is questionable whether the phase-plane analysis method based on single-unit vehicles is applicable for analyzing the lateral stability of multi-unit vehicles. In order to address the problem, case studies are conducted to test the effectiveness of the phase-plane method for analyzing the lateral stability of a car-trailer combination, which is represented by a nonlinear vehicle model generated using the CarSim software package.

This paper proposes a model reference adaptive control (MRAC) strategy for active trailer steering (ATS) in order to improve the lateral stability of articulated heavy vehicles (AHVs). Optimal controllers based on the Linear Quadratic Regulator (LQR) technique have been explored to enhance the lateral stability of AHVs; these controllers are designed under the assumption that the vehicle model parameters and operating conditions are given and they remain as constants. However, in reality, the vehicle system parameters and operating conditions may vary. To address the variable payloads of trailer(s), the controller based on MRAC technique is adopted. A three degrees of freedom (DOF) linear yaw-plane tractor-semitrailer model is generated to design the control law. The reference model is also developed using the linear yaw-plane model with the LQR technique. The effectiveness of the MRAC controller is demonstrated using numerical simulations under an emulated single lane-change maneuver.