Active Front Steering Research Articles

NMPC-Based Yaw Stability Control by Active Front Wheel Steering

This paper proposes a nonlinear model predictive control (NMPC) method for active front steering (AFS) system to improve vehicle handling and stability performance at handling limits. Nonlinear vehicle and tire models are adopted in this proposed NMPC controller to describe the nonlinear dynamics of vehicle and tire. In addition, the nonlinear optimal problem is solved by nonlinear solver in MATLAB optimization toolbox. Finally, this study explores the effectiveness of the NMPC system through sine and double lane change maneuver. Results corroborate that the proposed NMPC system can enhance the yaw stability at the handling limits.

Intervention criterion and control research for active front steering with consideration of road adhesion

ABSTRACTA multi-objective active front steering (AFS) control system considering the road adhesion constraint on vehicle stability is developed using the sliding mode control (SMC) method. First, an identification function combined with the relationship between the yaw rate and the steering angle is developed to determine whether the tyre state is linear or nonlinear. On this basis, an intervention criterion for the AFS system is proposed to improve vehicle handling and stability in emergent conditions. A sideslip angle stability domain enveloped by the upper, lower, left, and right boundaries, as well as the constraint of road adhesion coefficient, is constructed based on the phase-plane method. A dynamic weighting coefficient to coordinate the control of yaw rate and sideslip angle, and a control strategy that considers changing control objectives based on the desired yaw rate, the desired sideslip angle, and their proportional weights, are proposed for the SMC controller. Because road adhesion has a significant effect on vehicle stability and to meet the control algorithm's requirement of real-time access to vehicle states, a unscented Kalman filter-based state observer is proposed to estimate the adhesion coefficient and the required states. Finally, simulations are performed using high and low road adhesion conditions in a Matlab/Simulink environment, and the results show that the proposed AFS control system promptly intervenes according to the intervention criterion, effectively improving vehicle handling and stability.

Model predictive control of vehicle stability using coordinated active steering and differential brakes

This paper studies model predictive control of lateral stability of vehicles using coordinated active front steering and differential brakes. The controller is designed based on a bicycle model of the vehicle and the moment of the differential brakes is considered as an external torque. The prediction model calculates the prospective values of the vehicle’s yaw rate, lateral velocity, and tire slip angles over the prediction window. The sideslip angle of the vehicle is enforced within a permissible range using soft constraints on the lateral velocity in order to guarantee persistent feasibility. Using computer simulations, the controller is shown to provide proactive control actions to control the vehicle’s sideslip angle. The closed-loop response of the controller is also studied in experimental tests on an instrumented test vehicle. The results show satisfactory performance in various combinations of active front steering and differential brakes. In addition, the computational time of the controller is measured and shown to be safely below the sample time of the controller.

A Human-Machine-Cooperative-Driving Controller Based on AFS and DYC for Vehicle Dynamic Stability

It is a difficult and important project to coordinate active front steering (AFS) and direct yaw moment control (DYC), which has great potential to improve vehicle dynamic stability. Moreover, the balance between driver’s operation and advanced technologies’ intervention is a critical problem. This paper proposes a human-machine-cooperative-driving controller (HMCDC) with a hierarchical structure for vehicle dynamic stability and it consists of a supervisor, an upper coordination layer, and two lower layers (AFS and DYC). The range of AFS additional angle is constrained, with consideration of the influence of AFS on drivers’ feeling. First, in the supervisor, a nonlinear vehicle model was utilized to predict vehicle states, and the reference yaw rate, and side slip angle values were calculated. Then, the upper coordination layer decides the control object and control mode. At last, DYC and AFS calculate brake pressures and the range of active steering angle, respectively. The proposed HMCDC is evaluated by co-simulation of CarSim and MATLAB. Results show that the proposed controller could improve vehicle dynamic stability effectively for the premise of ensuring the driver’s intention.

MPC-Based Trajectory Tracking Via Active Front Steering and External Yaw Moment

In this paper, we propose a trajectory tracking method based Model Predictive Control (MPC) by utilizing steering and yaw moment. The main control objective is to track the desired trajectory with the front steering angle and yaw moment. And an external logic computes the torques at the four wheels such that the yaw moment is achieved, at the same time the logic controls the tire slip ratio around 0.15. Finally, the effectiveness of the proposed approach is demonstrated through the simulations at low and high speed.

Piecewise Trajectory Replanner for Highway Collision Avoidance Systems with Safe-Distance Based Threat Assessment Strategy and Nonlinear Model Predictive Control

This paper proposes an emergency Trajectory Replanner (TR) for collision avoidance (CA) which works based on a Safe-Distance Based Threat Assessment Strategy (SDTA). The contribution of this work is the design of a piecewise-kinematic based TR, where it replans the path by avoiding the invisible rectangular region created by SDTA. The TR performance is measured by assessing its ability to yield a maneuverable path for lane change and lane keeping navigations of the host vehicle. The reliability of the TR is evaluated in multi-scenario computational simulations. In addition, the TR is expected to provide a reliable replanned path during the increased nonlinearity of high-speed collisions. For this reason, Nonlinear Model Predictive Control (NMPC) is adopted into the design to track the replanned trajectory via an active front steering and braking actuations. For path tracking strategy, comparisons with benchmark controllers are done to analyze NMPC’s reliability as multi-actuators nonlinear controller of the architecture to the CA performance in high-speed scenario. To reduce the complexity of the NMPC formulation, Move Blocking strategy is incorporated into the control design. Results show that the CA system performed well in emergency situations, where the vehicle successfully replanned the obstacle avoidance trajectory, produced dependable lane change and lane keeping navigations, and at the same time no side-collision with the obstacle’s edges occurred. Moreover, the multi-actuators and nonlinear features of NMPC as the PT strategy gave a better tracking performance in high-speed CA scenario. Assimilation of Move Blocking strategy into NMPC formulation lessened the computational burden of NMPC. The system is proven to provide reliable replanned trajectories and preventing multi-scenario collision risks while maintaining the safe distance and time constraints.

Application of Open-Loop Stackelberg Equilibrium to Modeling a Driver's Interaction with Vehicle Active Steering Control in Obstacle Avoidance

The increasing use of active front steering (AFS) technology for obstacle avoidance raises the question of drivers’ interaction with vehicle automation. Mathematical models capable of representing such interaction are in demand for driver behavior study. This paper presents the application of open-loop Stackelberg equilibrium to modeling a driver's interaction with vehicle AFS control in an obstacle avoidance scenario, where both the driver and the AFS controller are exerting steering control to the vehicle. In this paper, such driver–AFS interactive steering control is modeled as a leader–follower game. Mathematical expressions of the driver's and the AFS controller's steering control strategies are derived using the linear quadratic dynamic optimization approach and the distributed model predictive control (DMPC) approach. These two approaches are found to give identical control gains, which suggest their equivalence in representing driver–AFS interaction. The DMPC approach is found to consume far less computation time due to its numerical nature. Mathematical modifications to the steering control strategies are then introduced to allow practical implementation for a future experimental study. Simulation results including time histories of steering angles and vehicle responses are illustrated and discussed.

Fuzzy Scheduled Optimal Control of Integrated Vehicle Braking and Steering Systems

The safe hard braking of a turned vehicle requires short stopping distance while maintaining the vehicle in the path. To achieve the first aim, a wheel slip controller is designed to calculate the maximum braking force of each wheel according to the tire/road conditions. For the second aim, a new optimal multivariable controller for integrated active front steering and direct yaw moment control is analytically developed to control the vehicle directional stability directly. Since the required stabilizing external yaw moment has to be produced by reducing the maximum achievable braking forces of one side wheels, it leads to increase the stopping distance and should be kept as low as possible. In an effective way to manage the integrated control inputs, a fuzzy logic is defined to determine the weight factor of each control input in the integrated optimal control law. This logic is defined using the stability index obtained by the phase plane analysis of nonlinear vehicle model. Therefore, the proposed controller can be tuned automatically for different driving conditions. The simulation results carried out using a validated vehicle model demonstrate that the integrated control system has a better performance compared with stand-alone braking and steering systems to attain the desired purposes.

Composite Nonlinear Feedback with Disturbance Observer for Active Front Steering

<p>One of the dominant virtue of Steer-By-Wire (SBW) vehicle is its capability to enhance handling performance by installing Active Front Steering (AFS) system without the driver’s interferences. Hence, this paper introduced an AFS control strategy using the combination of Composite Nonlinear Feedback (CNF) controller and Disturbance Observer (DOB) to achieve fast yaw rate tracking response which is also robust to the existence of disturbance. The proposed control strategy is simulated in J-curve and Lane change manoevres with the presence of side wind disturbance via Matlab/Simulink sotware. Futhermore, comparison with Proportional Integral Derivative (PID) and Linear Quadratic Regulator (LQR) controllers are also conducted to evaluate the effectiveness of the proposed controller. The results showed that the combined CNF and DOB strategy achieved the fastest yaw rate tracking capability with the least impact of disturbance in the AFS system installed in SBW vehicle.</p>

IMPLEMENTATION OF ROBUST COMPOSITE NONLINEAR FEEDBACK FOR ACTIVE FRONT STEERING BASED VEHICLE YAW STABILITY

In this paper, Robust Composite Nonlinear Feedback (CNF) was implemented on Active Front Steering (AFS) vehicle system for yaw stability control. In this control system, the main objective is to get excellent transient response of vehicle yaw rate and at the same time resist to side wind disturbance. To cater unknown constant disturbance, non-integral function for Robust CNF version is used. Meanwhile for vehicle model, 7 degree of freedom vehicle body with Pacejka Tire formula model for typical passenger car is used to simulate controlled vehicle. The computer simulation by Matlab software is performed to evaluate the system performance in J-Turn and Single sine steer with magnitude from 1 to 3.1 degree with additional 400 Nm external side wind disturbance. By using typical Proportional Integration and Derivative (PID) control auto-tuned by Matlab as comparison, the new designed controller demonstrates higher capability to track reference signal faster and having minimal tracking error during disturbance occur where having less than 0.01 degree compared 0.22 degree by PID. The Robust CNF based designed control system is able to compensate disturbance effect efficiently and also has super-fast tracking as classical CNF.

통합 섀시 제어를 위한 LQR의 가중치 변화에 대한 민감도 해석

This article presents a sensitivity analysis on the weight of the linear quadratic regulator (LQR) for integrated chassis control. Electronic stability control (ESC) and active front steering (AFS) are used as actuators needed to generate a control tire force. After computing the control yaw moment in the upper-level controller, the lower-level controller was used to distribute the control yaw moment into the control tire forces generated by ESC and AFS. In this paper, the LQR was used to design the upper-level controller. The Taguchi method was used to complete a sensitivity analysis on the weight of the linear quadratic (LQ) objective function in the LQR. For the sensitivity analysis, simulation was performed using CarSim, a vehicle simulation package. From the sensitivity analysis, the effect of the LQ objective function weight on the control performance was checked. Based on this sensitivity analysis, it was determined that the weights on lateral acceleration and yaw rate error had the largest effect on the control performance.

Path planning and stability control of collision avoidance system based on active front steering

Vehicle collision avoidance system is a kind of auxiliary driving system based on vehicle active safety, which can assist the driver to take the initiative to avoid obstacles under certain conditions, so as to effectively improve the driving safety of vehicle. This paper presents a collision avoidance system for an autonomous vehicle based on an active front steering, which mainly consists of a path planner and a robust tracking controller. A path planner is designed based on polynomial parameterization optimized by simulated annealing algorithm, which plans an evasive trajectory to bypass the obstacle and avoid crashes. The dynamic models of the AFS system, vehicle as well as the driver model are established, and based on these, a robust tracking controller is proposed, which controls the system to resist external disturbances and work in accordance with the planning trajectory. The proposed collision avoidance system is testified through CarSim and Simulink combined simulation platform. The simulation results show that it can effectively track the planning trajectory, and improve the steering stability and anti-interference performance of the vehicle.

Coordinated Chassis Control Based on Vehicle Lateral Acceleration Using Fuzzy Logic Control

This paper presents an advanced coordination of integrated control system which consist of three different controllers namely Electronic Stability Control (ESC), Active Front Steering (AFS), and Active Suspension (AS) using Fuzzy Logic Control (FLC) in order to improve vehicle handling, cornering stability, and rollover prevention with anti-lock brakingsystem (ABS) to avoid wheel locking during generating differential braking by ESC control. Based on a well-developed and validated fourteen degrees of freedom full vehicle model with non-linear tire characteristics, a reference yaw-roll plane vehicle model is introduced to compare and therefore control the yaw rate, side slip angle, and roll angle of the vehicle body. For rollover prevention indices, the dynamic load transfer ratio is defined to check the effectiveness of the proposed controller. The Coordination chassis control is based on the lateral acceleration value as input to FLC, and the outputs are the increment factors to the three controllers varying from zero to one. Three membership functions are chosen to represent the lateral acceleration as input to the supervisor controller, to define the control authority for each actuator. The universe of discourse for each membership function is selected according to the study of the effect of eachcontroller stand alone in vehicle performance. The numerical modelling is carried out through the MATLAB / Simulink environment which suits the control and optimization process. Different standard test maneuvers namely J-turn,fishhook, and double lane change have been carried out by considering standard test maneuvers with different driving speeds. The simulation results are compared during three cases namely, the uncontrolled system, the combined controller, and the proposed coordinated controller. The results show a substantial improvement of the vehicle stability in terms ofvehicle lateral acceleration, side slip angle, yaw rate, roll angle, and the for the developed coordinated controller compared to combined controller or the conventional system without control.

Coordinated control of ESC and AFS with adaptive algorithms

This paper presents a coordinated control of electronic stability control (ESC) and active front steering (AFS) with adaptive algorithms for yaw moment distribution in integrated chassis control (ICC). In order to distribute a control yaw moment into control tire forcres of ESC and AFS, and to coordinate the relative usage of ESC to AFS, a LMS/Newton algorithm (LMSN) is adopted. To make the control tire forces zero in applying LMS and LMSN, the zero-attracting mechanism is adopted. Simulations on vehicle simulation software, CarSim®, show that the proposed algorithm is effective for yaw moment distribution in integrated chassis control.

Composite Active Front Steering Controller Design for Vehicle System

The active front steering (AFS) technique is one of the effective methods to handle the stability of a vehicle. In this paper, some AFS control schemes have been proposed. First, a two degree of freedom mathematical model for the vehicle dynamics has been introduced in order to calculate the desired yaw rate. On this basis, the actual sideslip angle is further identified and estimated by constructing a sliding-mode observer. Then, two kinds of baseline AFS controllers are proposed by using PID and terminal sliding mode techniques, such that the actual yaw rate will approach its reference value as closely as possible. To further improve the performance of the closed-loop AFS control system, taking the uncertainties and external disturbances into account, the composite control schemes are developed by combining the previous designed state-feedback controllers and feedforward compensation term generated by the disturbance observer. The effectiveness of the designed AFS control schemes is verified by using the Carsim Software. It has been verified that the performance under two composite controllers is better than both baseline controllers.

Study on the vertical and lateral coupling dynamics control of the in-wheel motor-driven electric vehicles under multi-excitation

To study the coupling dynamics control in the vertical and lateral directions of the in-wheel motor (IWM)-driven electric vehicles under the steering input, road and electromagnetic excitation, a verified 16-degrees-of-freedom coupling dynamic model is given. To improve the vehicle coupling dynamics, a dynamics controller is designed based on the active suspension, active front steering (AFS) and direct yaw control (DYC) system. The dynamics controller includes a supervisory coordination layer controller and the above sub-system controller with different control algorithms, respectively. Finally, comparative analysis is carried out to verify the validity of the controller designed in this paper. The results show that, whether the road has a high or low adhesion coefficient, the controller developed in this paper is highly effective for the coupling dynamics of the IWM-driven vehicle. Especially, on a road with low adhesion coefficient, the control effect on the vehicle running stability and path track capacity is more obvious.

Adaptive optimal control for integrated active front steering and direct yaw moment based on approximate dynamic programming

In this paper, a novel adaptive optimal control algorithm based on approximate dynamic programming (ADP) approach is proposed for integrated active front steering (AFS) and direct yaw moment control (DYC). The corrective yaw moment and active steering angle are generated online without knowing system dynamics, which is realised by using a neural network (NN) identifier to identify the unknown system dynamics and a critic NN to calculate the optimal control action, respectively. Control commands are executed via active steering angle on front wheels and proper brake torque distribution on the effective wheels. Computer simulations under three different driving manoeuvres, i.e., lane change manoeuvre, step steer manoeuvre and sine with dwell manoeuvre, are carried out to evaluate the proposed control method. Simulation results show that the proposed ADP-based control method demonstrates improved tracking performance in terms of enhancing vehicle handling and stability performance when encountering the varying longitudinal velocity, the uncertain cornering stiffness and the different road/tyre friction coefficients. Model-free and self-adaptive properties of the proposed method provide a new solution to vehicle stability controller design instead of the commonly used model-based methods.

Adaptive optimal control for integrated active front steering and direct yaw moment based on approximate dynamic programming

In this paper, a novel adaptive optimal control algorithm based on approximate dynamic programming (ADP) approach is proposed for integrated active front steering (AFS) and direct yaw moment control (DYC). The corrective yaw moment and active steering angle are generated online without knowing system dynamics, which is realised by using a neural network (NN) identifier to identify the unknown system dynamics and a critic NN to calculate the optimal control action, respectively. Control commands are executed via active steering angle on front wheels and proper brake torque distribution on the effective wheels. Computer simulations under three different driving manoeuvres, i.e., lane change manoeuvre, step steer manoeuvre and sine with dwell manoeuvre, are carried out to evaluate the proposed control method. Simulation results show that the proposed ADP-based control method demonstrates improved tracking performance in terms of enhancing vehicle handling and stability performance when encountering the varying longitudinal velocity, the uncertain cornering stiffness and the different road/tyre friction coefficients. Model-free and self-adaptive properties of the proposed method provide a new solution to vehicle stability controller design instead of the commonly used model-based methods.

Multi-Objective Sliding Mode Control on Vehicle Cornering Stability with Variable Gear Ratio Actuator-Based Active Front Steering Systems.

Active front steering (AFS) is an emerging technology to improve the vehicle cornering stability by introducing an additional small steering angle to the driver’s input. This paper proposes an AFS system with a variable gear ratio steering (VGRS) actuator which is controlled by using the sliding mode control (SMC) strategy to improve the cornering stability of vehicles. In the design of an AFS system, different sensors are considered to measure the vehicle state, and the mechanism of the AFS system is also modelled in detail. Moreover, in order to improve the cornering stability of vehicles, two dependent objectives, namely sideslip angle and yaw rate, are considered together in the design of SMC strategy. By evaluating the cornering performance, Sine with Dwell and accident avoidance tests are conducted, and the simulation results indicate that the proposed SMC strategy is capable of improving the cornering stability of vehicles in practice.

Optimal workload actuator balancing and dynamic reference generation in active vehicle control

This paper addresses the problem of vehicle attitude control by means of active front steering and rear torque vectoring in the presence of saturating actuators. A novel approach of actuation balancing is proven to be the optimal way to keep the vehicle off saturation or, at least, to postpone the saturation occurrences as much as possible. To this end, a control law is proposed, achieving the tracking goal while keeping the balancing among the actuators. Exponential tracking is shown in nominal (non-saturated) conditions, where the optimality guarantees that the actuators remain as far as possible from their bounds. However, in hard conditions, saturations may still occur and tracking may be lost. Hence, it is shown how to modify dynamically the reference signals in order to compensate the lack of control action of actuators entering a possible saturation condition. As a consequence, less strict references are obtained and the tracking goal is recovered, while keeping the actuators within their saturation bounds. On top of the formal results, the method is validated by means of simulations performed in a non-ideal setting, including parameter uncertainties and unmodeled actuation delays.