Active Front Steering Research Articles

Real-Time Embedded Control of Vehicle Dynamics Using ESP32: A Discrete Nonlinear Approach

This article explores the application of the Espressif ESP32 System-On-Chip (SoC) for managing vehicle dynamics through real-time digital proportional–integral (PI-like) control. We present the development of advanced driving assistance algorithms for Active Front Steering (AFS) and Rear Torque Vectoring (RTV) on this cost-effective, commercially available embedded system. Using digital PI-like control algorithms designed for AFS and RTV, the primary ESP32 board receives and processes steering signals, executing a discrete-time control model of the vehicle dynamic to enable dynamic adjustments to steering and torque. To enhance simulation realism, a secondary ESP32 is employed to generate the steering signal, effectively mimicking a steer-by-wire system via its analog output ports. This configuration facilitates the simulation and evaluation of control algorithms in a realistic test environment, ensuring enhanced vehicle dynamic stability and maneuverability under various conditions. Additionally, simulations are conducted using MATLAB 2023a and CarSim 2017.1 to compare the efficacy and benefits of the implementation. Our objective is to establish a platform for evaluating discrete controllers capable of real-time vehicle operation. This methodology accelerates and reduces the cost of improving vehicle system stability and responsiveness, enabling the immediate verification and fine-tuning of control parameters as needed.

Active rack control of steer-by-wire systems for vehicle lateral stability

This paper describes a stability control strategy based on a steer-by-wire system to improve the lateral stability and manoeuvrability of vehicles by integrating individual chassis control modules, such as electronic stability control (ESC) and active front steering (AFS). Because of the uncertainty of cornering stiffness, an adaptive sliding-mode control is implemented without using the cornering stiffness value. An adaptive parameter is used instead of the cornering stiffness in the slip angle estimation and the lateral stability control. An unscented Kalman filter is used to estimate the slip angle and adaptive sliding mode control is used in lateral stability control. An equivalent desired command is calculated in lateral stability control. An integrated AFS and four individual wheel-braking controls were utilised to achieve an optimal distribution of longitudinal and lateral tyre forces, aiming to attain the desired command for lateral stability. Optimal coordination of the control authority for the AFS and the ESC has been chosen to minimise the force of each tyre. Computer simulations and vehicle tests of a closed-loop driver–vehicle–controller system subjected to a double-lane change have been carried out to verify that the proposed control strategy works.

Controllable region analysis of active front steering and differential braking system stability control characterized by additional yaw moment

Active Front Steering (AFS) and Differential Braking System (DBS) are commonly used execution systems for vehicle anti-rollover or handling stability control. They regulate the vehicle’s yaw moment by adjusting the lateral tire force and longitudinal tire force, respectively. However, these two systems differ in terms of control capabilities and regulatory sensitivities. In emergency conditions, it becomes crucial to allocate and coordinate the tasks for the execution systems according to their yaw moment control capability and adjustment sensitivity. This paper proposes a method for calculating the controllable region represented by the additional yaw moment. This method allows for the computation of the control capability of AFS and DBS based on the current state. Additionally, the influence of different vehicle states on the controllable regions of the two execution systems is analyzed. Building upon this analysis, the yaw moment adjustment sensitivities of AFS and DBS systems under the current state are further investigated. Finally, a task coordinated strategy between AFS and DBS is developed based on the analysis of controllable regions and sensitivities of different execution systems. Simulink simulations are conducted on yaw stability and roll stability conditions to comprehensively analyze the working process of the proposed task coordination strategy.

A modified handling stability control strategy for steer-by-wire vehicles based on variable steering ratio and active front steering control

Steer-by-wire (SBW) systems with steering actuator motors rotating the front wheels allow more flexibility for handling stability control; however, determining the desired steering angle and accurately tracking the desired steering angle are still key challenges. Therefore, a modified handling stability control strategy for handling stability is proposed in this paper. Firstly, based on the normal function, a unified variable steering ratio (UniVSR) model that varies with vehicle speed and steering wheel angle is developed. Then, the UniVSR model parameters are optimized by particle swarm optimization (PSO) algorithm in speed segments to improve the steering sensitivity at low speeds and the stability at medium and high speeds. Next, the active front steering (AFS) controller that considers the intervention timing and intervention threshold is proposed to improve the stability of the SBW vehicle under the driving conditions of low-adhesion road, split-μ road, and lateral wind interference. Lastly, the linear active disturbance rejection control (LADRC) based angle tracking control algorithm is presented to guarantee the desired angle tracking accuracy of the steering actuator motor under both internal parameter and external torque perturbations. The simulations validate the effectiveness of the proposed UniVSR model and AFS controller in improving handling stability.

Distributed-Drive Vehicle Lateral-Stability Coordinated Control Based on Phase-Plane Stability Region

The lateral stability control of vehicles is one of the most crucial aspects of vehicle safety. This article introduces a coordinated-control strategy designed to enhance the handling stability of distributed-drive electric vehicles. The upper controller uses active front steering and direct yaw moment-control controllers designed based on sliding-mode control theory. The lower controller optimally allocates control inputs to the upper controller, considering factors such as load transfer and tire load rate. It divides the stability region by relying on the phase plane and develops a coordinated-control strategy based on the degree of deviation of the vehicle state from the stability region. The results of the simulation experiments demonstrate that the proposed control strategy effectively improves handling stability under extreme working conditions.

Hierarchical extension H2/H∞ control approach for active front steering system of vehicle

Aiming at improving the vehicle handling stability and vehicle control performance by conventional H2/H∞ control, this paper investigates the active front steering (AFS) system by proposing a hierarchical extension H2/H∞ control strategy. Considering uncertainties and the vehicle handling stability, a mixed H2/H∞ control method is presented to generate the additional front wheel angle through tracking the desired vehicle yaw rate in the upper level. Furthermore, to enhance the H2/H∞ control effect, the novel extension control is proposed to adjust the H2/H∞ control signal dynamically according to different domains defined by the vehicle states. To track front wheel angle from the upper level, this study puts forward the fractional-order proportional-integral-derivative (FOPID) controller for driving the electro-hydraulic steering actuators. The hardware-in-the-loop experiments are performed to demonstrate the hierarchical control theory. The test results indicate that the proposed hierarchical extension H2/H∞ control strategy improves the vehicle cornering stability well, as well as can make the vehicle have better handling stability than conventional H2/H∞ and sliding mode control.

Bi-level path tracking control of tractor semi-trailers by coordinated active front steering and differential braking

In recent years, autonomous tractor semi-trailers have been considered a promising solution for transportation on highways, ports, and large logistics centers to improve safety and efficiency. However, due to the complicated dynamics introduced by articulation structure, there are still challenges in achieving high-precision path tracking and stability control for tractor semi-trailers, especially in critical scenarios. In this work, a bi-level path tracking control scheme for the autonomous tractor semi-trailer is proposed. At the higher level, a robust model predictive controller coordinating active front steering and differential braking is devised for addressing path tracking, stability control and robustness for an autonomous tractor semi-trailer. At the lower level, incorporating a logic switching mechanism, the designed optimal braking torque distribution module and the PID-based longitudinal control module prioritize the implementation of differential braking and target speed tracking. Simulation results demonstrate that the proposed control strategy offers remarkable path tracking performance in three designed testing scenarios.

A fixed-time nonsingular terminal sliding mode control based on radial basis function neural network for vehicle active front steering system

In our work, a novel fixed-time nonsingular terminal sliding mode controller is developed to improve the control performance for the active front steering system of electric vehicles. First, the sliding mode surface and the sliding mode convergence law are constructed so that the sliding variable can be stabilized to zero at a fixed time. Moreover, the radial basis function neural network is introduced to estimate the systematic uncertainties, which can make the system have stronger anti-disturbance ability. The Lyapunov analysis also is given to verify the fixed-time stability of the whole system. The presented control scheme possesses two appealing advantages, including the strong robustness to perturbations and the fixed-time convergence to zero. Notably, the settling time is independent of the initial value while only related to the controller parameters. Through the joint simulation of CarSim and MATLAB, the given controller is compared with the conventional sliding mode controller and nonsingular terminal sliding mode controller to demonstrate the plausibility and validity of the presented control strategy.

Backup Pattern for traction system of FWIA electric vehicle to guarantee maneuverability and stability in presence of motor faults and failures

Faults and failures in driving motors of four-wheel-independently-actuated (FWIA) electric vehicles can lead to hazardous accidents. To address this challenge, this paper introduces a novel “Backup Pattern” by grouping the driving motors into front and rear traction subsystems. This “Backup Pattern” ensures the optimal allocation of driving torque between functional motors, providing a reliable and effective mechanism to mitigate the impact of faulty motors on the vehicle’s overall performance. Based on the torque distribution strategy, a composite controller structure is presented, utilizing the second-order sliding mode algorithm to design both the traction controllers for longitudinal and differential torques and an active-front-steering (AFS) controller for additional steering angle. The composite controller not only enhances the vehicle’s maneuverability and stability but also copes with uncertainties and disturbances in the vehicle system. Hardware-in-loop (HiL) tests validate the superior effectiveness and robustness of the designed controller, showcasing its ability to enhance FWIA electric vehicle performance compared to the conventional first-order sliding mode control-based method.

An individualized robust stability control strategy for active front steering vehicles

To improve the vehicle stability and driver steering performance, this paper presents an individualized yaw stability control strategy based on H∞ robust control for active front steering (AFS) vehicles. A driver-vehicle system, including a driver steering model and a vehicle dynamics model with AFS, is formed. To analyze the steering characteristics of different drivers, a set of driving data of 36 drivers is collected, and the driver’s characteristics parameters are identified by using the particle swarm optimization (PSO) algorithm. A general evaluation function considering the trajectory tracking performance, vehicle stability, driver workloads, and driver’s characteristics parameters are established to evaluate the comprehensive steering performance. To accomplish the personalized control of vehicle yaw stability, an individualized H∞ robust yaw stability controller is presented by adjusting the gain of the weighting function according to the general evaluation of each driver. Driver-in-the-loop experiment is conducted based on the Matlab/Simulink-CarSim®-Prescan co-simulation platform, and the results demonstrates that the proposed control strategy can provide driver with individualized driving assistance while improving the overall driving performance and reducing the driver’s workloads.

Notice of Violation of IEEE Publication Principles: Integrated Control of Braking and Steering Subsystems for Autonomous Vehicle based on an Efficient Yaw Moment Distribution

Notice of Violation of IEEE Publication Principles Control of Braking and Subsystems for Autonomous Vehicle based on an Efficient Yaw Moment by Shaobo Lu, Sheng Cen, Xiaosong Hu, Cheewah Lim and Jinlong Zhang, in the IEEE Transactions on Industrial Electronics, Early Access, May 2017 After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE’s Publication Principles. This paper copies equations from the paper(s) cited below. The content was copied without attribution (including appropriate references to the original author(s) and/or paper title) and without permission. The lead and the second author of the paper were responsible for the violation. A correction letter for this misconduct was submitted and published at http://ieeexplore.ieee.org/document/8017449 Coordinated Control with Electronic Stability Control and Active Front Using the Optimum Yaw Moment Distribution Under a Lateral Force Constraint on the Active Front Steering by Seongjin Yim, Seungjun Kim and Heesung Yun, in the Proceedings of Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 2016, Vol. 230(5) pp. 581-592 This paper presents an Integrated Chassis Control (ICC) strategy for Electronic Stability Control (ESC) and Active Four Wheel (AFWS) based on an efficient optimal yaw moment distribution. To further enhance the handling and lateral stability of vehicle equipped with ESC, a new Weighted Pseudo- inverse Control Allocation (WPCA) based ICC is proposed. The cornering forces of both front and rear wheels are used to cooperate with the ESC braking forces, so as to further extend the operational envelope of the vehicle. A bi-level hierarchical control structure is employed. In the upper level, the sliding mode control with a combined sliding surface is used to generate the desired virtual control. In the lower level, a revised optimal function is defined to tune the control authority of actuators, and an algebraic operation based WPCA method is adopted. To avoid tire forces saturation and enforce a certain stability margin, a boundary layer constraint is further considered in the proposed optimization problem. A severe lane change maneuver is used to investigate the performance via closed-loop driver-vehicle- controller simulations using CarSim and MATLAB/Simulink. Simulation results demonstrate that the proposed algorithm outperforms current control practice without violating the actuators physical limitation.

Cooperative Control of Path Tracking and Driving Stability for Intelligent Vehicles on Potholed Road

When a vehicle hits a pothole, the reaction force of the pothole on the tire causes an imbalance in the driving forces on both sides of the vehicle and may cause the wheels to jump, potentially resulting in path deviation and roll instability. To address these issues, a cooperative control system for path tracking and driving stability is proposed. Roll stability is achieved by the roll moment generated by reasonably distributing the driving torque among the four IWMs. The necessary roll moment is calculated by the designed robust sliding mode control (RSMC), which enhances the transient performance of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H_∞</i> by 48.9%. The path tracking is ensured by active front steering (AFS) based on model predictive control (MPC), and the front wheel angle is used as the disturbance of the stability control. Simulation and bench test results demonstrate that the developed controller can maintain vehicle stability even when the greatest path deviation is 0.03 m, whereas conventional direct yaw-moment control (DYC) and AFS controllers fail to achieve the same level of control. These findings provide a theoretical foundation and serve as a reference for cooperative control on potholed roads.

Coordination of Active Front Steering and Direct Yaw Control Systems Using MIMO Sliding Mode Control

Coordination of Active Front Steering and Direct Yaw Control Systems Using MIMO Sliding Mode Control

Fault diagnosis and fault tolerant control for distributed drive electric vehicles through integration of active front steering and direct yaw moment control

For the purpose of improving the lateral stability in the path following process for the distributed drive electric vehicles subject to multiple actuator/sensor faults, a new fault diagnosis and fault tolerant control method is proposed in this paper through the integration of the active front steering (AFS) and direct yaw-moment control (DYC). Firstly, considering the actuator/sensor faults and parameter uncertainties together, a Takagi–Sugeno fuzzy model is established to describe the integrated AFS/DYC system with nonlinear dynamics. Secondly, because the fault information plays a key role in the fault tolerant control, a fuzzy estimation observer is presented to diagnose actuator/sensor faults online. Thirdly, considering the high cost of the measurement sensors for lateral speed, it is hard to measure the complete state of the vehicle. Thus, in the frame of dynamic output feedback structure, a fuzzy fault tolerant control method is proposed to improve the path following performance and guarantee the dynamic stability. Finally, the hardware-in-the-loop experimental results of two typical driving maneuvers show that the proposed control method has a superior performance in the improvement of the driving stability and active safety.

An Active Front Steering System Design Considering the CAN Network Delay

The x-by-wire technology promotes the rapid development of intelligent vehicles, but it comes with the network delays, which would deteriorate the control performance. Therefore, this paper proposes an active front steering (AFS) design scheme considering the network delays to ensure the vehicle path-tracking accuracy and stability performance. First, the vehicle system with delays induced by the Controller Area Network (CAN) is analyzed, based on which an augmented model is built to describe the vehicle motion combined with the random network delays. Considering the uncertainty of the delay, the model is reconstructed by the polytope method. Then, a robust H∞ state feedback controller is developed to ensure the system performance when handling the parametric uncertainties. Furthermore, the robust invariant set is introduced to depict the system constraints, which can guarantee the vehicle stability. Through transforming into the linear matrix inequalities, a feasible solution is calculated. Finally, the rapid control prototype (RCP) based on the CarSim/Simulink test platform is used to validate the proposed controller. The results compared with the model predictive control show the effectiveness to ensure the prescribed performance.

Research on Collaborative Control of Differential Drive Assisted Steering and Active Front Steering for Distributed Drive Electric Vehicles

A collaborative control strategy for distributed drive electric vehicles (DDEVs) focusing on differential drive assisted steering (DDAS) and active front steering (AFS) is proposed to address the issues of sudden torque changes, reduced steering characteristics, and weak collaborative control capabilities caused by the coupling of the AFS and DDAS systems in DDEVs. This paper establishes a coupled dynamic model of the AFS and DDAS systems and, on this basis, designs AFS controllers for yaw velocity feedback control and DDAS controllers for steering wheel torque control, respectively. Additionally, it analyzes the interference factors of the two control systems and develops a collaborative control strategy for DDAS and AFS; this control strategy establishes a corner motor correction module, steering wheel torque correction module, and assistance correction module. Co-simulation is carried out on Matlab/Simulink and the Carsim platform to verify the correctness of the model under typical working conditions; to reduce the sudden change in the steering wheel torque caused by AFS additional angle interventions; to improve the poor steering characteristics caused by DDAS, introducing additional yaw torque; to greatly enhance the collaborative control effect; and to meet the requirements for vehicle handling stability, portability, and safety.

AFS control system research of distributed drive electric vehicles by adaptive super-twisting sliding mode control

To solve the problems of serious buffeting in traditional sliding mode control and difficulty in obtaining the derivative information of the system sliding mode surface, a distributed drive electric vehicles active front steering (AFS) control method based on adaptive super-twisting sliding mode control (ASTSMC) is proposed. Taking the yaw rate deviation as the state quantity, the stable and convergent sliding mode surface is designed to obtain the equivalent control input of the front wheel angle. The sliding mode function information is substituted into the parameters of the super-twisting algorithm; the discontinuous term is kept in the integrand function to keep the control signal continuous and weaken the system chattering; the adaptive control law is added to design the AFS controller. The co-simulation results of Matlab/Simulink and Carsim show that ASTSMC can reduce the yaw rate by 40.59% compared with no control under step steering condition. Compared with the sliding mode controller, ASTSMC has optimized the sideslip angle by 5.41% under the double line shifting condition.

Design of Active Disturbance Rejection Controller for Trajectory-Following of Autonomous Ground Electric Vehicles

In this paper, the concept of symmetry is utilized in the promising trajectory-following control design of autonomous ground electric vehicles—that is, the construction and the solution of active disturbance rejection controllers are symmetrical. This paper presents an active disturbance rejection controller (ADRC) for improving the trajectory-following performance of autonomous ground electric vehicles (AGEV) with an advanced active front steering system. Since AGEV trajectory dynamics are inherently affected by complex traffic conditions, various driving maneuvers, and other road environment, the main control objective is to deal with the AGEV trajectory control challenges of system uncertainties, system nonlinearities, and external disturbance. First, the vehicle dynamics trajectory-following model and its state space representation system are established. Then, the augmented control-oriented vehicle-trajectory-following system with dynamic error is developed. The resulting active disturbance rejection controller of the vehicle-trajectory-following system is finally designed using the trajectory performance index and active disturbance compensation, and the stability of the active disturbance rejection controller is also analyzed and derived via Lyapunov stability theory. The effectiveness of the proposed controller is validated through double lane change and serpentine maneuvers under the co-simulation platform of MATLAB/Simulink-Carsim®. Simulation results show that the designed controller provides enhanced vehicle-trajectory-following performance compared to the linear quadratic regulator controller (LQR) and model predictive controller (MPC). It will provide a certain guidance for the controller engineering design of the AGEV trajectory-following system.

Coordinated control of AFS and DYC for electric vehicles with mechanical elastic electric wheels considering the roll effects and uncertain parameters

In order to improve the lateral stability of in-wheel motors electric vehicles (IMEV) equipped with mechanical elastic electric wheels (MEEW) under extreme conditions, this paper proposes an integral sliding mode control (ISMC) algorithm based on the coordination of active front steering (AFS) and direct yaw moment control (DYC) considering the roll effects and the uncertainty of tire cornering stiffness. Firstly, the AFS control algorithm based on adaptive integral terminal sliding mode is proposed, which uses radial-basis-function neural network (RBFNN) to adaptively approximate the integrated nonlinear unknown disturbance. Secondly, considering the roll effects and uncertain cornering stiffness, a mismatched uncertain system for integrated control of AFS and DYC is established. An integral sliding mode control algorithm based on linear matrix inequality (LMI) is designed, and the asymptotic stability of sliding mode dynamics is proved. Further, a constraint optimization algorithm is used to distribute the additional yaw moment. Then, a coordinated control strategy based on the elliptical stable region of the phase plane and the rollover index is designed to activate the integrated controller of AFS and DYC at the right time. Finally, the effectiveness of the control algorithm is verified by high-fidelity CarSim-Matlab simulations. The results show that the proposed controller can effectively and robustly ensure the vehicle lateral stability under extreme conditions.

Integrated Control of Motion Actuators for Enhancing Path Following and Yaw Stability of Over-Actuated Autonomous Vehicles

Advanced active safety systems play a crucial role in ensuring the safe driving of vehicles in critical conditions such as an obstacle avoidance manoeuvre. However, conventional techniques relying mainly on braking interventions may not result in the desired vehicle response in such situations. Over-actuation through the control of individual motion actuators could potentially improve the safety performance of vehicles. This study evaluates various configurations of motion actuators for path following and yaw stability control of vehicles in critical driving scenarios. The configurations include active front steering (S), active front steering + torque vectoring (ST), active front steering + active camber (SC) and active front steering + torque vectoring + active camber (STC). The evaluation is achieved based on a nonlinear model predictive control formulation, which considers yaw stability and the physical limits of motion actuators. This problem formulation uses a double-track vehicle model, combined with the Dugoff tyre model and its variant with the camber effect, to model the vehicle dynamics. The actuator configurations are evaluated regarding the passing velocity, tracking accuracy, safety distance and robustness to reference trajectory variation. The results indicate that the integrated control of STC performs the best among all the four configurations while S performs the worst. Furthermore, SC is generally superior to ST.