Vehicle Yaw Stability Control Research Articles

Research on Vehicle Stability Control Based on a Union Disturbance Observer and Improved Adaptive Unscented Kalman Filter

This paper considers external disturbances imposed on vehicle systems. Based on a vehicle dynamics model of the vehicle with three degrees of freedom (3-DOFs), a union disturbance observer (UDO) composed of a nonlinear disturbance observer (NDO) and an extended state observer (ESO) was designed to obtain external disturbances and unmodeled items. Meanwhile, an improved adaptive unscented Kalman filter (iAUKF) with anti-disturbance and anti-noise properties is proposed, based on the UDO and the unscented Kalman filter (UKF) method, to evaluate the sideslip angle of vehicle systems. Finally, a vehicle yaw stability controller was designed based on UDO and the global fast terminal sliding mode control (GFTSMC) method. The results of co-simulation demonstrated that the proposed UDO was effectively able to observe external disturbances and unmodeled items. The proposed iAUKF, which considers external disturbances, not only achieves adaptive updating and adjustment of filtering parameters under different sensor noise intensities but can also resist external disturbances, improving the estimation accuracy and robustness of the UKF. In the anti-disturbance performance test, the maximum estimation error of the sideslip angle of the iAUKF under the three working conditions was less than 0.1°, 0.02°, and 0.5°, respectively. Based on the UDO and the GFTSMC, a vehicle yaw stability controller is described, which improves the accuracy of control and the robustness of the vehicle’s stability control system and greatly strengthens the driving safety of the vehicle.

Research on Stability Control Algorithm of Distributed Drive Bus under High-Speed Conditions

Aiming at the instability problem of a four-wheel independent drive electric bus under high-speed conditions, this paper first designs a vehicle yaw stability controller based on a linear two-degree-of-freedom model and a linear quadratic programming (LQR) algorithm. A vehicle roll stability controller is then designed based on a linear three-degree-of-freedom model and a model predictive control algorithm (MPC). Moreover, a coordinated control rule based on the lateral load transfer rate (LTR) is designed for the coupled problem of yaw and roll dynamics. Finally, the effectiveness of the proposed control algorithm is verified by simulation. The obtained results show that when the vehicle is running at a high speed of 90 km/h, the stability control algorithm can control the yaw rate tracking error within 0.05 rad/s. In addition, the control algorithm can reduce the maximum amplitude of the side slip angle, the maximum value of the roll angle, the maximum value of the roll angular velocity, and the amplitude of the lateral acceleration by more than 96%, 81.1%, 65.0%, and 11.1%, respectively.

Coordination control method of autonomous ground electric vehicle for simultaneous trajectory tracking and yaw stability control

A hierarchical trajectory tracking and yaw stability combined control strategy of autonomous ground vehicle within-wheel motor is proposed in this paper to achieve simultaneous and accurate trajectory tracking and vehicle yaw stability control. A trajectory-tracking controller is designed on the basis of model predictive control algorithm, and the ideal front-wheel steering angle requirement is calculated to follow the referenced trajectory. In order to improve the accuracy of vehicle steering control, a vehicle steering controller is designed based on high-order sliding mode control method, in which the control demand of front-wheel steering angle is satisfied by real-time torque control of vehicle steering motor. Simultaneously, a double power reaching rate-based sliding mode control method is applied to design the vehicle yaw stability controller, in which the yaw moment control requirement is met by an optimal oriented tire force allocation algorithm. The simulation and experiment results show that the presented control method can improve the accuracy and real-time performance of trajectory tracking control while ensuring vehicle yaw stability.

Vehicle yaw stability control with a two-layered learning MPC

This paper proposes a novel framework to address the model-vehicle mismatch (MVM) challenge of yaw stability control, which introduces the Gaussian Process-based Model Predictive Control into the classical two-layer structure. In the upper layer, the supervisor controller calculates the compensation torque required for vehicle turning. Gaussian Process regression is employed to compensate model mismatch and unmodelled dynamics. The chance constraints on sideslip angle are converted into double half-space constraints by the normal distribution quantile function. In the lower layer, the subordinate controller utilises the nonlinear slip rate model to distribute torque to the wheels in the form of braking torque. A new assignment rule of braking torque weight is proposed according to the yaw torque analysis. The stability of the two-layered learning MPC is ensured through proof and simulation. In the Simulink and Carsim co-simulation environment, the superiority of the proposed method is verified in the task of rapid double-lane change. Compared with the traditional MPC-based yaw stability controller, the proposed method has increased the stability tracking index and energy consumption index by around 13% and 8%.

Vehicle yaw stability control: literature review

Vehicle yaw stability control: literature review

Vehicle yaw stability control: literature review

Vehicle yaw stability control: literature review

Observation of Dynamic State Parameters and Yaw Stability Control of Four-Wheel-Independent-Drive EV

Vehicle yaw stability control is an important part of the active safety of electric vehicles. In order to realize the yaw stability control of vehicles, this paper takes 4-WID electric vehicles as the research object, studies the nonlinear estimation of the state parameters of the lateral stability dynamic system and the yaw stability control strategy. The vehicle state parameter estimation strategy, based on the unscented Kalman filter (UKF) algorithm and the model predictive control algorithm, are designed to control the vehicle yaw stability, which realizes the safe and stable driving of the vehicle. Through CarSim–Simulink joint simulation and hardware-in-the-loop (HIL) experiments based on MicroAutoBox, the effectiveness and real-time performance of the designed control strategy are fully verified, which accelerate the development process of the vehicle controller, and realizes the safe and stable driving of the vehicle.

Design of Yaw Stability Control System for Electric Vehicle Driven by Hub Motor

In extreme weather condition, the electric vehicle yaw stability control accuracy is low. A new yaw stability control system for electric vehicle driven by hub motor is designed to simplify the hardware system design and improve the system response speed. The driving control module is used to analyse the driving state parameters of the vehicle and calculate the four-wheel moment to control the yaw stability of the vehicle, which is transmitted to the battery control module. The UDU in the control module adjusts the motor speed and power output in real time according to the vehicle power demand after analyzing the vehicle driving state data. In the software part of the system, the vehicle dynamic model is built and yaw stability control strategy is used to complete the vehicle yaw stability control. The experimental results show three important parameters of the designed system for evaluating the manoeuvrability tend to ideal values under the control of the system, in which yaw angular velocity is controlled from 0.277 rads to 0.286 rads and the difference between them is 0.002 and 0.011. The yaw stability control accuracy is also high.

Vehicle Yaw Stability Control at the Handling Limits Based on Model Predictive Control

This study proposes a double linear model predictive control (DLMPC) structure to improve the tyre force utilization of active front steering (AFS) vehicle at the handing limits. The DLMPC structure consists of a linear model predictive control (LMPC) and a linear time-varying model predictive control (LTV-MPC). During normal driving conditions, the AFS adopts LMPC to control the vehicle. When vehicle running at the handing limits, the tyre force is near saturation, LTV-MPC is activated to prevent tyre force from entering unstable region. The proposed DLMPC controller can reflect the nonlinear dynamic characteristic of tyres by the expression design of tyre force. Double lane change and sine with dwell maneuver tests are provided to demonstrate the effectiveness and feasibility of the DLMPC controller. Results corroborate that the proposed DLMPC controller can fully exploit the potential of AFS and maintain the yaw stability of the vehicle at the handling limits.

Adaptive neural control of vehicle yaw stability with active front steering using an improved random projection neural network

ABSTRACT Active front steering (AFS) can enhance the vehicle yaw stability. However, the control of vehicle yaw rate is very challenging due to (1) the unmodelled nonlinearity and uncertainties in vehicle dynamics; (2) timely response in control scheme. These two issues can be simultaneously alleviated through a random projection neural network (RPNN) for its high model generalisation and fast computational speed. However, typical RPNN cannot be directly applied to adaptive control applications. Therefore, a new RPNN-based adaptive neural control method is proposed, which is equipped with a newly designed adaptation law based on the theorem of Lyapunov stability. To test the performance of the proposed control method, simulations were carried out using a validated vehicle model. The simulation results show that, compared to conventional backpropagation neural network (BPNN) based controller, the proposed RPNN-based adaptive controller can reduce the response time and attenuate oscillatory steering in the case of cornering manoeuvre under fast variant vehicle speed. The results also demonstrate that the proposed RPNN-based adaptive controller outperforms the state-of-the-art fuzzy logic controller and the error feedback controller in multiple aspects including tracking nominal vehicle yaw rate, desired sideslip angle and intended path, showing its significance in vehicle yaw stability control.

Robust vehicle yaw stability controlby active front steering with active disturbance rejection controller

Due to the complicated driving conditions, the influence of the external disturbance and the system uncertainty, the traditional active front-steering control methods which are based on the exact mathematical model cannot meet the control requirements. This article presents a new active front-steering control strategy which is based on active disturbance rejection control for vehicle yaw stability control. The proposed controller can dynamically estimate and compensate the total disturbance, which enables it to provide good control performance in a range of conditions without the need for a sophisticated vehicle model. In this article, the implementation of the active disturbance rejection control–based yaw stability controller is introduced in detail, and the convergence of the extended state observer and the stability of the whole controller are theoretically proved. In order to verify the effectiveness of the proposed control strategy, a co-simulation environment is used to carry out real-time simulations on typical driving conditions to verify the performances of the proposed controller. The simulation results show that the proposed controller can effectively improve the yaw stability of the vehicle and has strong robustness.

Compensation of time delay effect in vehicle yaw stability control systems by using communication disturbance observer

Compensation of time delay effect in vehicle yaw stability control systems by using communication disturbance observer

Vehicle yaw stability control using active rear steering: Development and experimental validation

In this paper, a novel pulse active steering system for improving vehicle yaw stability is developed. In the proposed method, pulses are sent to the steerable rear wheels whenever the error between the expected and actual yaw rate is outside a predetermined range. The proposed method and its performance are verified experimentally by full vehicle testing. For this purpose, a simplified vehicle model and a rear suspension model are developed. Vehicle stability is investigated and the steering pulse parameters on the vehicle’s stability are studied. A control system is designed and numerical simulations are performed. Moreover, the active rear steering system is implemented on a Lexus for performing road experiments. Results from simulations and experiments indicate that considerable improvement in the yaw stability performance can be achieved by the proposed system. The proposed method is more cost effective and simpler for vehicle stability control.

Vehicle yaw stability control using active limited-slip differential via model predictive control methods

In this paper, the problem of vehicle yaw control using an active limited-slip differential (ALSD) applied on the rear axle is addressed. The controller objective is to minimise yaw-rate and body slip-angle errors, with respect to target values. A novel model predictive controller is designed, using a linear parameter-varying (LPV) vehicle model, which takes into account the ALSD dynamics and its constraints. The controller is simulated using a 10DOF Matlab/Simulink simulation model and a CarSim model. These simulations exemplify the controller yaw-rate and slip-angle tracking performances, under challenging manoeuvres and road conditions. The model predictive controller performances surpass those of a reference sliding mode controller, and can narrow the loss of performances due to the ALSD's inability to transfer torque regardless of driving conditions.

A Review on Integrated Active Steering and Braking Control for Vehicle Yaw Stability System

A review study on integrated active steering and braking control for vehicle yaw stability system is conducted and its finding is discussed in this paper. For road-vehicle dynamic, lateral dynamic control is important in order to determine the vehicle stability. The aw stability control system is the prominent approach for vehicle lateral dynamics where the actual yaw rate and sideslip should be tracked by the controller close to the desired response. To improve the performance of yaw stability control during steady state and critical driving conditions, a current approach using active control of integrated steering and braking could be implemented. This review study discusses the vehicle models, control objectives, control problems and propose control strategies for vehicle yaw stability control system. In the view of control system engineering, the transient performances of tracking control are essential. Based on the review, this paper discusses a basic concept of control strategy based on the composite nonlinear feedback (CNF) and sliding mode control (SMC) whichcan be proposed for integrated active steering and braking control in order to improve the transient performances of the yaw rate and sideslip tracking control in the presence of uncertainties and disturbances.

Composite Nonlinear Feedback for Vehicle Active Front Steering

In this paper, Composite Nonlinear Feedback (CNF) is applied on Active Front Steering (AFS) system for vehicle yaw stability control in order to have an excellent transient response performance. The control method, which has linear and nonlinear parts that work concurrently capable to track reference signal very fast with minimum overshoot, fast settling time, and without exceed nature of actuator saturation limit. Beside, modelling of 7 degree of freedom for typical passenger car with magic formula to represent tyre nonlinearity behaviour is also presented to simulate controlled vehicle as close as possible with a real situation. An extensive computer simulation is performed with considering a various profile of cornering manoeuvres with external disturbance to evaluate its performance in different scenarios. The performance of the proposed controller is compared to conventional Proportional Integration and Derivative (PID) for effectiveness analysis.

The Research of Wheel Drive Vehicle Yaw Stability Controller Based on Model Predictive Control

As an important active safety control method, vehicle yaw stability control guarantees the dynamic stability of vehicle. A wheel drive vehicle yaw stability controller based on model predictive control theory is designed to plan the longitudinal forces of the four wheels online to control the driving torque or braking torque of each wheel. With the designed controller, the vehicle is able to track the desired yaw rate in the process of turning. The yaw stability and longitudinal characteristics of the vehicle are guaranteed at the same time.

Vehicle Yaw Stability Control by Coordinated Active Front Steering and Differential Braking in the Tire Sideslip Angles Domain

Vehicle active safety receives ever increasing attention in the attempt to achieve zero accidents on the road. In this paper, we investigate a control architecture that has the potential of improving yaw stability control by achieving faster convergence and reduced impact on the longitudinal dynamics. We consider a system where active front steering and differential braking are available and propose a model predictive control (MPC) strategy to coordinate the actuators. We formulate the vehicle dynamics with respect to the tire slip angles and use a piecewise affine (PWA) approximation of the tire force characteristics. The resulting PWA system is used as prediction model in a hybrid MPC strategy. After assessing the benefits of the proposed approach, we synthesize the controller by using a switched MPC strategy, where the tire conditions (linear/saturated) are assumed not to change during the prediction horizon. The assessment of the controller computational load and memory requirements indicates that it is capable of real-time execution in automotive-grade electronic control units. Experimental tests in different maneuvers executed on low-friction surfaces demonstrate the high performance of the controller.

Vehicle Yaw Rate Estimation Using a Virtual Sensor

Road vehicle yaw stability control systems like electronic stability program (ESP) are important active safety systems used for maintaining lateral stability of the vehicle. Vehicle yaw rate is the key parameter that needs to be known by a yaw stability control system. In this paper, yaw rate is estimated using a virtual sensor which contains kinematic relations and a velocity-scheduled Kalman filter. Kinematic estimation is carried out using wheel speeds, dynamic tire radius, and front wheel steering angle. In addition, a velocity-scheduled Kalman filter utilizing the linearized single-track model of the road vehicle is used in the dynamic estimation part of the virtual sensor. The designed virtual sensor is successfully tested offline using a validated, high degrees of freedom, and high fidelity vehicle model and using hardware-in-the-loop simulations. Moreover, actual road testing is carried out and the estimated yaw rate from the virtual sensor is compared with the actual yaw rate obtained from the commercial yaw rate sensor to demonstrate the effectiveness of the virtual yaw rate sensor in practical use.

On the Use of Torque-Biasing Systems for Electronic Stability Control: Limitations and Possibilities

This brief paper focuses on the concept of utilizing torque-biasing systems on a four-wheel drive vehicle for improving vehicle stability and handling performance. In contrast to brake-based yaw stability control systems, torque biasing has the potential to provide yaw stability control without slowing down the longitudinal response of the vehicle. An inexpensive system configuration is considered in which the driveline is based on front-wheel drive with on-demand transfer of torque to the rear. The torque-biasing components of the system are an electronically controlled center coupler and a rear electronically controlled limited slip differential. First, modeling of the torque-biasing devices is briefly introduced. Then, a hierarchical control architecture is presented in which an upper controller determines desired yaw moment for achieving yaw rate and slip angle control. The lower controller attempts to achieve the desired yaw moment using torque biasing. Theoretical analysis shows that transfer of longitudinal tire forces can effectively be used to achieve any desired yaw moment for the vehicle. However, the use of torque biasing cannot always achieve the desired transfer of longitudinal tire forces. Simulations show that the proposed control system can always effectively provide understeering yaw moments but can provide oversteering torque moments only during on-throttle maneuvers. Experimental data show that significant stability improvements are obtained using the proposed system for low-friction slalom maneuvers and a T-junction launch maneuver. The results presented in this brief shed important light on the possibilities and limitations of using torque biasing for vehicle yaw stability control