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Active steering technology can effectively solve the contradiction between the running stability and curving performance of traditional bogies. However, the execution deviations between the actual and theoretical steering actions, which expressed in this paper as equivalent curvature differences, would occur when mileage error or other abnormal operating conditions happens. In this study, the influence of equivalent curvature differences on running safety was studied, and a steering efficiency evaluation method was proposed. First, the equivalence between the wheel–rail relationship in the under- and over-steering states and that in the passive state was demonstrated by combining analytical and numerical simulation methods. It was concluded that under- and over-steering states do not worsen the running safety of rail vehicles. Then, the formula for wear number with the equivalent curvature difference as the independent variable was derived based on the linear model of the rail vehicle, and the accuracy of the formula was verified using the nonlinear model. Finally, a steering efficiency evaluation method was established, and a steering efficiency evaluation under different equivalent curvature differences and steering rates was conducted. The results of this study can provide a reference for engineering active steering systems. [ABSTRACT FROM AUTHOR]

Among other variables, smart tyre systems are capable of determining tyre contact forces. Combining this information with the signals obtained from conventional vehicle sensors, e.g. inertial measurement units, wheel speed sensors and steering wheel angle sensors, improves the estimation accuracy of the states used by the vehicle dynamics controllers of production cars. This study assesses the performance improvement brought by the vertical and longitudinal tyre contact force signals, obtained through smart tyres, to an unscented Kalman filter (UKF) for vehicle speed and sideslip angle estimation, based on a nonlinear vehicle dynamics model. Two UKF designs, excluding and including smart tyre information, are compared by using experimental data from a purposely sensorised high-performance passenger car, along a comprehensive set of manoeuvres. The results show average ∼60% and ∼37% reductions of the root mean square values of the normalised vehicle speed and sideslip angle estimation errors for the filter design receiving the smart tyre information. In comparison with the more conventional UKF design without tyre force inputs, the smart tyre based estimator is also characterised by significantly enhanced robustness and adaptability to typical variations of vehicle and tyre parameters, such as the tyre-road friction coefficient. [ABSTRACT FROM AUTHOR]

A control strategy based on H ∞ -type static output feedback combined with dynamic feed-forward is proposed to improve the high-speed lateral performance of an A-double combination vehicle(tractor–semitrailer–dolly–semitrailer) using active steering of the front axle of the dolly. Both feedback and feed-forward syntheses are performed via Linear Matrix Inequality (LMI) optimisation. From a practical point of view, the proposed controller is simple and easy to implement, despite its theoretical complexity. In fact, the measurement of the driver steering angle and only one articulation angle are required for the feed-forward and the feedback controllers, respectively. The results are verified using a high-fidelity vehicle model and confirm a significant reduction in yaw rate and lateral acceleration rearward amplification and also high-speed transient off-tracking, and subsequently improving the lateral stability and performance of the A-double combination vehicle during sudden lane change manoeuvres. [ABSTRACT FROM AUTHOR]

Future vehicle localisation technologies enable major enhancements of vehicle dynamics control. This study proposes a novel vehicle stability control paradigm, based on pre-emptive control that considers the curvature profile of the expected path ahead in the computation of the reference direct yaw moment and braking control action. The additional information allows pre-emptive trail braking control, which slows down the vehicle if the predicted speed profile based on the current torque demand is deemed incompatible with the reference trajectory ahead. Nonlinear model predictive control is used to implement the approach, in which also the steering angle and reference yaw rate provided to the internal model are varied along the prediction horizon, to account for the expected vehicle path. Two pre-emptive stability control configurations with different levels of complexity are proposed and compared with the passive vehicle, and two state-of-the-art nonlinear model predictive stability controllers, one with and one without non-pre-emptive trail braking control. The performance is assessed along obstacle avoidance tests, simulated with a high-fidelity model of an electric vehicle with in-wheel motors. Results show that the pre-emptive controllers achieve higher maximum entry speeds – up to ∼34% and ∼60% in high and low tyre-road friction conditions – than the formulations without preview. [ABSTRACT FROM AUTHOR]

Automobiles are becoming more and more complex as multiple control systems are integrated into the vehicle platform. This paper investigates the coordination of active rear steering (RWS) and torque vectoring (TV) – which is enabled by independent electric motors at the rear axle – in controlling vehicle lateral dynamics. The proposed controller aims at enhancing vehicle handling performance and stability while cornering. The coordination of the two actuators is achieved by weighting their contribution based on their impact on vehicle dynamics according to the working condition. The impact of each control system is assessed by means of phase portraits. These plots are a very powerful tool for analysing vehicle nonlinear dynamics as they readily display vehicle stability properties and map equilibrium point locations and movement to changing parameters and control inputs. Based on phase portrait analysis, a performance index is thus proposed, which weights more the control action (TV or RWS) capable of leading the vehicle at the nearest equilibrium point with the fastest rate. The controller performance is assessed through numerical simulations carried out using a nonlinear 14 dofs vehicle model. Results are compared with ones of the two controllers alone (RWS and TV) in different manoeuvers and adherence conditions. [ABSTRACT FROM AUTHOR]

This paper presents the design of a central feedforward control for the two chassis control systems rear-wheel steering (RWS) and torque vectoring (TV) which have related areas of intervention in lateral dynamics. A control strategy is presented in order to follow desired target values consisting of yaw acceleration and sideslip angle velocity. Central attention is given to the use of additional tyre information with the aim of enhancing vehicle handling and stability. With the knowledge of the mounted tyre type, an adaption law for the desired target values is derived. Although the focus is based on the usage of new tyre information, this modelling approach basically has the potential to reduce the need for coordination among the two systems RWS and TV, exploiting the synergies between both of them. Starting from an extended single-track model an exact Input–output linearisation method is used to design the feedforward control. This is followed by a proof of stability for the external and the internal dynamics of the controller. For the subsequent investigation, in a preliminary step, real-world in vehicle tests are carried out under varying tyre types with a wide spreading of characteristics. This serves as a basis to identify the most important tyre parameters for the controller and to derive the target goals. Finally, the controller is implemented in a 14-DOF non-linear entire vehicle model in Matlab/Simulink, that serves for simulations with a virtual vehicle plant. The performance of the presented feedforward control is assessed by specified objective criteria for steady-state and transient open-loop manoeuvres in lateral dynamics. These criteria are used to investigate the effectiveness of the control design with the aim to achieve the defined target motion. In addition to that, the manoeuvre results also serve to evaluate the control effort, involved in the coordinated cooperation of both systems. [ABSTRACT FROM AUTHOR]

A robust steering-based controller synthesis is presented for an A-double combination vehicle with a steerable dolly. The controller ensures robust stability and performance in the face of uncertainties in the cornering stiffness of the tyres and the moments of inertia of the semitrailers, which are treated as time-varying and time-invariant parameters respectively. A descriptor-type representation of the system is employed since a standard state-space model depends rationally on the moments of inertia. The controller synthesis is formulated as an -type static output feedback, which uses information from only one articulation angle. The driver steering input is also used by including a static feed-forward. The proposed synthesis method is based on linear matrix inequality (LMI) optimisation. The controller is verified based on the simulation results obtained from both (approximate) linear and (high-fidelity) nonlinear vehicle models. The results indicate significant improvement in the high-speed lateral performance of the A-double in the presence of parametric uncertainties. [ABSTRACT FROM AUTHOR]

In this paper, a coordinated control strategy is proposed to provide an effective improvement in handling stability of the vehicle, safety, and comfortable ride for passengers. This control strategy is based on the coordination among active steering, differential braking, and active suspension systems. Two families of controllers are used for this purpose, which are the high order sliding mode and the backstepping controllers. The control strategy was tested on a full nonlinear vehicle model in the environment of MATLAB/Simulink. Rollover avoidance and yaw stability control constraints have been considered. The control system mainly focuses on yaw stability control. When rollover risk is detected, the proposed strategy controls the roll dynamics to decrease rollover propensity. Simulation results for two different critical driving scenarios, the first one is a double lane change and the other one is a J-turn manoeuvre, show the effectiveness of the coordination strategy in stabilising the vehicle, enhancing handling and reducing rollover propensity. [ABSTRACT FROM AUTHOR]

This paper considers the problem of collision avoidance for road vehicles, operating at the limits of friction. A two-level modelling and control methodology is proposed, with the upper level using a friction-limited particle model for motion planning, and the lower level using a nonlinear 3DOF model for optimal control allocation. Motion planning adopts a two-phase approach: the first phase is to avoid the obstacle, the second is to recover lane keeping with minimal additional lateral deviation. This methodology differs from the more standard approach of path-planning/path-following, as there is no explicit path reference used; the control reference is a target acceleration vector which simultaneously induces changes in direction and speed. The lower level control distributes vehicle targets to the brake and steer actuators via a new and efficient method, the Modified Hamiltonian Algorithm (MHA). MHA balances CG acceleration targets with yaw moment tracking to preserve lateral stability. A nonlinear 7DOF two-track vehicle model confirms the overall validity of this novel methodology for collision avoidance. [ABSTRACT FROM AUTHOR]

The paper discusses some of the common speed and steering control strategies of drivers for negotiating curved roads under normal, obstacle-free driving conditions. An analysis is given of the dynamic behaviour of the driver-vehicle system for two typical strategies. A driver model is developed to take into account the application of steering and speed control before approaching a curve and during driving on curved roads. The driver's anticipatory speed-control is based on the desired lateral acceleration and estimated maximum curvature of the road ahead. The well-known two-level model is adapted for describing the steering activity of the driver. The primary control of steering is anticipatory tracking of the road-curvature previewed at a look-ahead distance. It is assumed that the driver's mental model for anticipatory steering is based on a simple, linear and non-adaptive vehicle model assuming a vehicle driving with constant forward speed. A non-linear model with variable forward speed represents the actual vehicle. When both steering input and speed control using brake/throttle are applied simultaneously the driver's anticipatory steering estimate leads to tracking errors. The driver's compensatory steering input for reducing tracking errors uses feedback of error in lateral displacement at a near-field viewpoint of the driver. The results of analysis of the driver-vehicle system demonstrate the significant influence of the driver's internal model and control strategies on the overall performance of the driver-vehicle system. [ABSTRACT FROM AUTHOR]