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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]

This paper investigates the handling control and stability of an all-wheel-drive vehicle whose axles are individually equipped with an electric motor connected to an open differential. This could offer a potential configuration for the mass production of electric all-wheel-drive vehicles because of reduced cost and complexity. Although there is no torque vectoring or direct yaw moment control in this configuration, considerable handling improvement can be achieved by optimised front/rear torque distribution due to the longitudinal and lateral tire force coupling. In this study, a model predictive control design is presented with a coupled force prediction model for vehicle handling dynamics. The controller optimises the front/rear torque allocation to track the desired handling response and ensure vehicle stability. This study also compensates for actuator delay by incorporating the actuator dynamics into the control design. The performance of the proposed controller is evaluated through software simulations and experimental tests conducted on an electric all-wheel-drive Chevrolet Equinox. [ABSTRACT FROM AUTHOR]

Active safety systems contribute significantly to the safe driving of autonomous vehicles in hazardous circumstances. However, conventional active safety systems that mainly depend on braking intervention may not yield the desired vehicle behaviour in critical situations where the tyre forces tend to saturate. Over-actuation through individually cambering the wheels provides a possibility of overcoming this difficulty, as extra lateral tyre forces can potentially be produced. This paper presents active camber for improving the path following and yaw stability performance of over-actuated autonomous electric vehicles (AEVs). With a modified Dugoff tyre model, the camber effect on the lateral tyre force is modelled as an effective linear component. The modified tyre model, together with a double-track vehicle model, is utilised for active camber of the AEVs. The camber controller is developed in the framework of model predictive control (MPC), including both actuator- and safety-related constraints. The camber controller is investigated at different camber rates and road friction levels, in terms of path following, yaw stability and vehicle velocity gain. [ABSTRACT FROM AUTHOR]

This paper presents an in-depth analysis of the application of different techniques for vehicle state and tyre force estimation using the same experimental data and vehicle models, except for the tyre models. Four schemes are demonstrated: (i) an Extended Kalman Filter (EKF) scheme using a linear tyre model with stochastically adapted cornering stiffness, (ii) an EKF scheme using a Neural Network (NN) data-driven linear tyre model, (iii) a tyre model-less Suboptimal-Second Order Sliding Mode (S-SOSM) scheme, and (iv) a Kinematic Model (KM) scheme integrated in an EKF. The estimation accuracy of each method is discussed. Moreover, guidelines for each method provide potential users with valuable insight into key properties and points of attention. [ABSTRACT FROM AUTHOR]

For performance improvement of modern vehicle dynamic control systems, exact knowledge of the vehicle motion state and the road conditions is essential. Addressing this problem, the development and validation of a state observer for a four-wheel drive electric vehicle is examined in this article. In particular, a reliable and accurate estimation of the tire slip in longitudinal and lateral direction at each wheel is desired. For this, an Unscented Filter is used to estimate the vehicle chassis and wheel dynamics. At the same time, the estimator is able to adapt the tire model according to the current road conditions by using wheel-individual tire-road friction coefficients. In the beginning, details on the used vehicle model as well as the estimator tuning and implementation procedure are given. The validation takes place first in a vehicle simulation environment to point out the performance of the observer especially in severe driving situations, like a sudden change of road friction conditions during a slalom manoeuver. Afterwards, driving tests with an electric four-wheel drive vehicle are carried out to proof the presented observer concept under real-world conditions. All performed driving manoeuvers are described and the test results are presented and evaluated. [ABSTRACT FROM AUTHOR]

Autonomous driving at at-limit handling represents a big challenge due to the nonlinear behaviour of a vehicle. In this paper, a hierarchical control scheme composed of two Nonlinear Model Predictive Controls (NMPCs) for path following is proposed. This structure allows for real-time feasibility without having to simplify excessively the vehicle model. The higher level NMPC operates on a long prediction horizon with a point-mass model which constraints are given by a tyre dependant 'g–g diagram'. The output of the higher level is a velocity profile which is used as terminal constraint by the lower level NMPC. This operates on a short horizon and is based on a seven degrees of freedom vehicle model with full Pacejka Magic Formula tyre formulation on all tyres, load transfers and Limited Slip Differential. Because of the terminal set computed by the higher level, it is possible to use a short horizon and exploit the vehicle performance in real-time. For both controllers, the full Nonlinear Optimisation Problem is solved at each step. The algorithm is tested in a Model-in-the-Loop environment where a validated Vi-Grade vehicle model is controlled in co-simulation. The results show the effectiveness and feasibility of real-time control with complex vehicle models. [ABSTRACT FROM AUTHOR]

This paper proposes a linear predictive lateral control method to stabilise a highly automated vehicle (HAV) at the tire-road friction limits when tracking a (tight) desired path. Two approaches are adopted to linearise the vehicle model around the tire saturation region: (1) the lateral force of the front tire is selected as the control input instead of the steer angle and (2) the rear tire dynamics is locally linearised at the current operating point within the predictive horizon. The friction limits of both the front and rear tires are utilised to define an enveloped stable zone, which serves as the safety constraints for the predictive controller. Simulation results show that the proposed controller is able to stabilise a vehicle when tracking a tight desired path at a high speed even on a low-adhesion road. Moreover, the robustness of the proposed controller is also verified as it tolerates small estimation errors in the road friction coefficient. [ABSTRACT FROM AUTHOR]

Hybrid Electric Vehicles (HEV) offer improved fuel efficiency compared to conventional vehicles at the expense of adding complexity and at times, reduced total power. As a result, HEV generally lack the dynamic performance that customers enjoy. To address this issue, the paper presents a HEV with electric All-Wheel-Drive capabilities via the use of torque vectoring electric rear axle drive (TVeRAD) to power the rear axle. The addition of TVeRAD to a front wheel drive HEV improves the total power output. To improve the handling characteristics of the vehicle, the TVeRAD provides torque vectoring at the rear axle. A bond graph model of the drivetrain is developed and used in co-simulation with CarSim. The paper proposes a control system which utilises control allocation to optimise tyre forces. The proposed control system is tested in the simulation environment with a high fidelity CarSim vehicle model. Simulation results show the control system is able to maximise vehicle longitudinal performance while avoiding tyre saturation on low mu surfaces. More importantly, the control system is able to track the desired yaw moment request on a high speed double lane change manoeuvre through the use of the TVeRAD to improve the handling characteristic of the vehicle. [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]

This paper proposes a novel 2-step global sensitivity analysis algorithm to provide an in-depth sensitivity analysis of the vehicle parameters on the system responses. A 9 degree-of-freedom nonlinear vertical–lateral coupled vehicle model is developed, and 12 parameters along with 7 system responses are selected for the sensitivity analysis. In order to reduce the computational effort, the proposed 2-step algorithm calculates the elementary effects and selects 7 influential parameters from these 12, and then uses the Sobol' method to obtain the global sensitivity indexes of these influential parameters. An unscented Kalman filter is finally designed to show the effect and importance of the selected sensitive parameters on the observation accuracy. Simulations with different vehicle types, velocities and tyre models have verified that the proposed algorithm can accurately describe the relationship between the vehicle parameters and system responses, which is of directive significance to improve vehicle controller and observer performances. [ABSTRACT FROM AUTHOR]

Simulations of closed-loop manoeuvres where the driver is modelled in a vehicle-road environment axe of increasing importance in car development. To be able to investigate manoeuvres with large local deviations from a desired road trajectory the 2-level standard driver model, which is based on previewed steering, is extended by a 3rd level which initiates a smooth transition to the road trajectory. The corresponding control design is based on the two-wheel vehicle model and the sliding control technique, and more over it can be adapted to different steering intensities and driving situations. The simulation results are based on a complex 3D vehicle model and consider different tyre-road friction conditions. An obstacle avoidance manoeuvre and the entering of a curve (with clothoide) with a μ-low section in the circular part prove the quality of this 3-level approach. [ABSTRACT FROM AUTHOR]