Vehicle Lateral Stability Research Articles

Semi-active lateral control simulation of straddle-type monorail dynamic model with single-axle bogies

Lateral stability of straddle-type monorail vehicle (STMV) with single-axle bogies, as a new type of bogies, has been paid more and more attention. To solve it the lateral control method of a semi-active suspension system for STMV dynamic model with single-axle bogies based on magnetorheological fluid damper is proposed. The full-scale dynamics model of 34 freedom and magneto-rheological (MR) damper is established. An adaptive fuzzy hybrid strategy for STMV dynamic model based on vehicle body acceleration and velocity feedback is designed. The inverse mechanical model of MR damper is established to predict the control current. The dynamic characteristics of a semi-active suspension system based on MR damper model are studied by numerical method. The dynamic response of a STMV model with a semi-active suspension system is analysed. The simulation results show that the proposed adaptive control strategy can improve the comfort of the vehicle and improve the stability of the operation.

Vehicle Lateral Stability Regions for Control Applications

This article presents an improved method of obtaining lateral stability regions for road vehicles, considering the influence of steering angle, center of gravity, longitudinal speed, and tire-road friction coefficient on the vehicle dynamics. Comprehensive stability regions are obtained for a wide range of such parameters. Moreover, conservative stability regions are proposed, in the case of control applications that demand robust or safety-critical control actions. Next, a steering-angle-dependent region is used to implement a safety-critical electronic stability control system with active front steering as actuation. The resulting control system extends safety-critical control based on control-dependent barrier functions, introducing a control-dependent Lyapunov function to improve its steady-state behavior. Finally, we identify and propose workarounds for problems that arise from the number of inputs being less than the dimension of the desired safe set. The conservative stability regions and the extended safety-critical control system are validated by means of simulation results based on a nonlinear lateral stability model.

Safety-Guaranteed Control of Coupled Longitudinal and Lateral Vehicle Dynamics by Considering Tire Stability via CDBFs

In high-speed emergent driving scenarios of automated ground vehicles (AGVs), a lateral lane changing maneuver is often accompanied by longitudinal deceleration and/or acceleration. Such emergency scenarios not only couple vehicle longitudinal and lateral dynamics but also involve nonlinear, unstable, and coupled longitudinal and lateral tire forces. Therefore, a safety-guaranteed control design considering coupled longitudinal and lateral vehicle dynamics and tire stability is desired. Control Lyapunov function (CLF) and control barrier function (CBF) were integrated to find a safety-guaranteed controller while tracking a reference path. However, CBF cannot describe the control-dependent invariant sets that characterize vehicle lateral stability regions with stable tire forces. Thus, an integrated CLF and control-dependent barrier function (CDBF) control is designed for coupled longitudinal and lateral vehicle dynamics by considering tire stability to ensure vehicle driving safety in emergent driving scenarios. Simulation results are shown to verify the effectiveness of the proposed control design.

Conflict and Sensitivity Analysis of Articulated Vehicle Lateral Stability Based on Single-Track Model

Lateral stability is quite essential for the vehicle. For the vehicle with an articulated steering system, the vehicle load and steering system performance is quite different from the passenger car with the Ackman steering system. To investigate the influence of the tire characteristics and vehicle parameters on lateral stability, a single-track dynamic model is established based on the vehicle dynamic theory. The accuracy of the built model is validated by the field test result. The investigated parameters include the tire cornering stiffness, vehicle load, wheelbase, and speed. Based on the snaking steering maneuver, the lateral stability criteria including the yaw rate, vehicle sideslip angle, tire sideslip angle, and lateral force are calculated and compared. The sensitivity analysis of the tire and vehicle parameters on the lateral stability indicators is initiated. The results demonstrated that the parameters that affect the lateral vehicle stability the most are the load on the rear part and the tire cornering stiffness. The findings also lay a foundation for the optimization of the vehicle’s lateral stability.

Fractional Calculus Control of Road Vehicle Lateral Stability after a Tire Blowout

The lateral stability control of the vehicle can avoid serious traffic accidents when it had a tire blowout during the operation. This article proposes a robust nonlinear control method for controlling vehicle lateral stability after a tire blowout. To be exact, a seven degree of freedom dynamic model of vehicle with modified Dugoff tire model is established. The yaw moment of vehicle is performed by differential braking once the tire blowout occurring. As for control strategy, taking the linear two degree of freedom vehicle model as the reference, using the deviation of yaw rate and the vehicle side angle between the actual value and the reference value as the controller input parameters, the fractional calculus theory is utilized for yaw moment controller which was investigated by regulating the brake moment of blowout vehicle for improving its stability. The results of computer simulation show that the design controller of fractional PID can more effectively enhance the blowout vehicle performance stability compared with the vehicle with the non control, PID control, no matter in straight road or curve road.

Switched model predictive controller for path tracking of autonomous vehicle considering rollover stability

Lateral stability and rollover stability are two most crucial concerns for path tracking of an autonomous vehicle under handling limit conditions. To improve path tracking accuracy and ensure vehicle stability under handling limit conditions, this paper proposes a force-driven switched MPC path tracking control strategy that coordinates active front-wheel steering with an external yaw moment. Firstly, a linear time-varying tire model is modelled using the affine approximate linearisation method to describe rear tire dymamics. And vehicle dynamics is modelled to predict vehicle states in the prediction horizon. Then, a force-driven switched MPC control strategy is proposed based on the system prediction model. The vehicle lateral stability and rollover stability are restricted using maximum tire lateral force and the zero-point moment method, respectively. Finally, according to the simulation results under normal speed and limiting speed conditions, a force-driven switched MPC control strategy can improve control accuracy and ensure vehicle stability.

Extension Coordinated Multi-Objective Adaptive Cruise Control Integrated with Direct Yaw Moment Control

An adaptive cruise control (ACC) system can reduce driver workload and improve safety by taking over the longitudinal control of vehicles. Nowadays, with the development of range sensors and V2X technology, the ACC system has been applied to curved conditions. Therefore, in the curving car-following process, it is necessary to simultaneously consider the car-following performance, longitudinal ride comfort, fuel economy and lateral stability of ACC vehicle. The direct yaw moment control (DYC) system can effectively improve the vehicle lateral stability by applying different longitudinal forces to different wheels. However, the various control objectives above will conflict with each other in some cases. To improve the overall performance of ACC vehicle and realize the coordination between these control objectives, the extension control is introduced to design the real-time weight matrix under a multi-objective model predictive control (MPC) framework. The driver-in-the-loop (DIL) tests on a driving simulator are conducted and the results show that the proposed method can effectively improve the overall performance of vehicle control system and realize the coordination of various control objectives.

A feedback-feed-forward steering control strategy for improving lateral dynamics stability of an A-double vehicle at high speeds

A control strategy based on -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.

Alternative Models for Calculation of Static Overturning Angle and Lateral Stability Analysis of Subcompact and Universal Tractors

Vehicle lateral stability is evaluated using the static overturning angle. The correct value of this parameter depends on the calculation method. The aim of this study was to compare the latest standard with previously published methodology, to propose two alternative methodologies (Models 1 and 2) and to analyze the influence of various levels of rear wheel ballast weights and overall tire widths on the stability of universal and subcompact tractors. The results showed a significant regression effect of the rear wheel ballast weight on static overturning angle. The influence of the rear wheel ballast weight was higher in the subcompact tractor than in the universal tractor due to a larger distance between the height of the center of gravity and the center of the rear axle. Comparing the latest standard with the previously published methodology, the highest difference values were 13.82% and 7.30%. Both models are based on the previously published methodology and differ from each other in rolling and slope lines. The methodology proposed in Model 2 differed from the standard similarly to the previously published methodology; therefore, it is irrelevant. Model 1 reached differences of only −1.81% and −1.63%, representing a minimal difference from the standard.

Adaptive event-based robust passive fault tolerant control for nonlinear lateral stability of autonomous electric vehicles with asynchronous constraints

This work solves the robust passive fault-tolerant control problem for autonomous electric vehicles based on an adaptive event triggered mechanism. Firstly, given the system uncertainties from the tire dynamics and the longitudinal speed, the T–S fuzzy model method is used to approximate the vehicle lateral dynamics. Secondly, taking the communication constraints caused by band-limited networks into account, an adaptive event-triggered scheme is introduced in the process of the control design. Moreover, the asynchronous constraint of the weight function between the controller and system is considered. Thirdly, considering that the actuator faults are inevitably encountered in the control system, a robust passive fault-tolerant control method is proposed to improve vehicle performances. Finally, simulations are carried out to illustrate the effectiveness and robustness of the proposed approach.

Cooperative-Game-Oriented Optimal Design in Vehicle Lateral Stability Control with Fuzzy Uncertainties

Cooperative-Game-Oriented Optimal Design in Vehicle Lateral Stability Control with Fuzzy Uncertainties

Real-Time nonlinear predictive controller design for drive-by-wire vehicle lateral stability with dynamic boundary conditions

Due to flexible drive-by-wire technology, vehicle stability control can improve handling and lateral stability under extreme conditions. However, this technology can also increase the probability of random transmission delay. This paper proposes a nonlinear model predictive control (NMPC) strategy to improve vehicle stability and compensate for the random time delay. First, by combining the nonlinear dynamic characteristics and driver behavior, we obtain a stable region of the yaw rate and the sideslip angle under complex driving conditions. Second, an NMPC controller is designed to track the reference values in the identified stable region to improve the handling and lateral stability. Finally, the actuator receives the optimized control sequence and compensates for the random time delay of the transmission channel. CarSim/Simulink simulation and hardware-in-the-loop experiment results show that the proposed controller with dynamic boundary conditions can better track the expected value of the yaw rate and suppress the sideslip angle under low adhesion road conditions.

Lateral Stability Control of Four-Wheel-Drive Electric Vehicle Based on Coordinated Control of Torque Distribution and ESP Differential Braking

This research focuses on four-wheel-drive electric vehicles. On the basis of the hierarchical coordinated control strategy, the coordinated control system of driving force distribution regulation and differential braking regulation was designed to increase the electric vehicles steering stability under special road working conditions. A seven-degree-of-freedom model of an electric vehicle was established in MATLAB/Simulink, and then a hierarchical coordination control model of the Electronic stability program and dynamic torque distribution control system was established. Adaptive fuzzy control was applied to ESP and, based on the neural network PID control, a torque distribution control system was designed. On the basis of the proposed coordinated control model, a performance simulation and a hardware-in-the-loop test of the control system under the typical working condition of single line shift were carried out. From the final results, it can be seen that the proposed control strategy can greatly improve the safety of the vehicle after serious side slip, increase the stability of the whole vehicle, and effectively increase the vehicle lateral stability.

A Distributed Integrated Control Architecture of AFS and DYC Based on MAS for Distributed Drive Electric Vehicles

Reconstitution of control architecture creates a great challenge for distributed drive electric vehicles (DDEV), due to the emergence of a new distributed driving strategy. To this end, a novel distributed control architecture is proposed in this paper for integrated control of active front steering (AFS) system and direct yaw moment (DYC) system. First, a multi-agent system (MAS) is employed to construct a general framework, where AFS and DYC act as agents that work together to improve vehicle lateral stability and simultaneously reduce workloads of drivers during path tracking. The cooperative control strategies of two agents are obtained through Pareto-optimality theory to ensure optimal control performance of AFS and DYC. Then, on the basis of dynamic interaction between agents, terminal constraints, including terminal cost function and terminal input with local static feedback, are designed to guarantee the asymptotic stability of the close-loop system. Finally, virtual simulations are conducted to evaluate the proposed controller. The results indicate that the proposed control architecture can effectively preserve vehicle stability and reduce workloads of drivers, especially for the inexperienced driver. Furthermore, the hardware-in-loop (HIL) test results also demonstrate the feasibility of the proposed controller.

Observer-based multi-objective integrated control for vehicle lateral stability and active suspension design

This paper investigates an observer-based robust gain-scheduling integrated control strategy to improve the maneuverability, stability and ride comfort of vehicle by coordinating direct yaw moment control and active suspension system. The uncertainty of tire cornering stiffness, the actuator saturation and the hard constrains of suspension design are taken into account. The longitudinal velocity is considered time-varying which makes the designed controller more practical, and a polytope with trapezoidal structure is used to describe the velocity-dependent parameters. An observer is designed to estimate the vehicle sideslip angle, suspension deflection and tire deflection simultaneously. Based on it, a robust saturated gain-scheduling H∞/GH2 controller is obtained by solving a set of linear matrix inequalities (LMIs), which guarantees that the sideslip angle and yaw rate tracking error are minimized, the vertical acceleration and pitch acceleration are attenuated, and the suspension deflection, tire deflection are bounded. The simulation results illustrate the effectiveness of the proposed integrated control strategy under different road profiles and maneuvers.

A novel adaptive-rear axles steering controller for an 8 × 8 combat vehicle

Multi-axle vehicles are widely used in several applications such as transportation, industrial, and military field, because of its higher reliability in comparison with conventional two axles vehicles. Despite that, there is a paucity of research studies that consider lateral stability enhancement of these vehicles, especially on rough terrain. This simulation-based research study fills this gap and introduces a new adaptive Active Rear Steering (ARS) controller that improves the lateral stability of an 8x8 combat vehicle for rough-terrain operation. The developed controller is designed utilizing the Integral Sliding Mode Control theory (ISMC) based on Gain-Scheduled Linear Quadratic Regulator (GSLQR). Besides, the GSLQR control gains are optimized by a Genetic Algorithm (GA) toolbox using a new synthesized cost function to ensure asymptotic stability. Furthermore, a new Adaptive-ISMC (AISMC) is introduced by using genetic programming to generate control equations that can replace the developed high-dimension GSLQR gains and facilitate future hardware implementation. The developed controller is evaluated by performing a series of simulation-based Double Lane Change (DLC) maneuvers on several rough terrains. The evaluation is conducted for both high friction and slippery surfaces at high and moderate speed, consequently. The results show high fidelity and robustness of the developed controller in comparison with a previously designed optimal LQR controller.

Multi-layer controller with state-constraint: Vehicle lateral stability control based on fuzzy logic

This paper deals with a new state-constrained control (SCC) system of vehicle, which includes a multi-layer controller, in order to ensure the vehicle’s lateral stability and steering performance under complex environment. In this system, a new constraint control strategy with input and state constraints is applied to calculate the steady-state yaw moment. It ensures the vehicle lateral stability by tracking the desired yaw rate value and limiting the allowable range of the side slip. Through the linkage of the three-layer controller, the tire load is optimized and achieve minimal vehicle velocity reduction. The seven-degree-of-freedom (7-DOF) simulation model was established and simulated in MATLAB to evaluate the effect of the proposed controller. Through the analysis of the simulation results, compared with the traditional ESC and integrated control, it not only solves the problem of obvious velocity reduction, but also solves the problem of high cost and high hardware requirements in integrated control. The simulation results show that designed control system has better performance of path tracking and driving state, which is closer to the desired value. Through hardware-in-the-loop (HIL) practical experiments in two typical driving conditions, the effectiveness of the above proposed control system is further verified, which can improve the lateral stability and maneuverability of the vehicle.

Coordinated longitudinal and lateral vehicle stability control based on the combined-slip tire model in the MPC framework

In extreme driving situations, the coupling between the longitudinal and lateral vehicle motion becomes significant with the highly nonlinear tire forces and influences vehicle overall stability. To address the above problem, a model predictive controller is proposed for four wheels independent motor-drive electric vehicles. Firstly, a LuGre combined-slip tire model is developed to describe the coupling nonlinearity of the tire. The variation of longitudinal velocity is considered a disturbance term in the vehicle dynamics model to consider its effect on vehicle stability. Then, the multiple objectives, including tracking the reference values of the yaw rate and lateral velocity, suppressing the tire slip ratios, and reducing the torque energy consumptions, are balanced by the additional torque generated by the designed model-based controller. The safety and actuator constraints are considered concurrently. Finally, the proposed controller is tested via co-simulation with CarSim and MATLAB/Simulink, and a hardware-in-loop system with extreme maneuvers. The results show that the handling performance, longitudinal and lateral stability are effectively improved under extreme conditions.

Robust adaptive non-singular fast terminal sliding-mode lateral control for an uncertain ego vehicle at the lane-change maneuver subjected to abrupt change

This paper investigates a new approach to deal with the path-tracking for an uncertain autonomous ground vehicle (AGV) exposed to the unknown external disturbances caused by abrupt changes in the road bank angle. A robust adaptive non-singular fast terminal sliding mode control (RANFTSMC) is designed for the lane change maneuver (LCM) lateral control. Initially, a reference LCM path is planned by a recent procedure. Then, assuming that the upper bound of unknown external disturbances and uncertainties is known, a robust steering controller is implemented via non-singular fast terminal sliding mode control (NFTSMC) to ensure the vehicle lateral stability. However, the upper limit of the vehicle uncertainties and perturbations is unknown in real-world driving situations, therefore, an adaptive tuning law is developed to estimate this unknown upper bound. As long as the efficiency of the controller depends on their parameters, a meta-heuristic optimization algorithm is employed to deliver the controller optimal settings. The effectiveness of the proposed RANFTSMC is proven with theoretical illustrations and numerical simulation results. The offered steering controller maintains the lateral stability even in severe conditions where the vehicle longitudinal speed is up to 120 km/h. In this connection, the suggested strategy is compared with the higher-order sliding mode controller (HOSMC) and conventional sliding mode controller (SMC).

Conflict and Sensitivity Analysis of Vehicular Stability Using a Two-State Linear Bicycle Model

Vehicle parameters and operation conditions play a critical role in vehicular handling and stability. This study aimed to evaluate vehicle stability based on cornering tire stiffness integrated with vehicle parameters. A passenger vehicle is considered in which a two-state linear bicycle model is developed in the Matlab/Simulink. The effect of the vehicle parameters on lateral vehicle stability has been investigated and analyzed. The investigated parameters included CG longitudinal position, wheelbase, and tire cornering stiffness. Furthermore, the effects of load variation and vehicle speed were addressed. Based on a Fishhook steering maneuver, the lateral stability criteria represented in lateral acceleration, yaw rate, vehicle sideslip angle, tire sideslip angles, and the lateral tire force were analyzed. The results demonstrated that the parameters that affect the lateral vehicle stability the most are the cornering stiffness coefficient and the CG longitudinal location. The findings also indicated a positive correlation between vehicle properties and lateral handling and stability.