Vehicle Lateral Stability Research Articles

Distributed driving electric vehicle lateral stability control method considering time delay

This paper introduces a novel control method to address lateral stability challenge in distributed driving electric vehicles. By considering inherent time delay and unknown sensor measurement error generated from design, manufacturing, and external disturbances, the proposed approach achieves better robustness. Firstly, we establish a two-degree-of-freedom (2-DOF) dynamic model for lateral motion of an electric vehicle driven by in-wheel motors (EV-DIM). Based on this model, a control system considering time delay and unknown sensor measurement error is constructed. The control system incorporates a controller based on a dual domination gains observer, and its global asymptotic stability is rigorously proved by the Lyapunov method. Numerical simulations and co-simulations via CarSim and Simulink verify the method’s effectiveness. Compared to the sliding mode control, the proposed method shows better performance which indicates this approach promising for enhancing lateral stability of an electric vehicle.

Lateral-Stability-Oriented Path-Tracking Control Design for Four-Wheel Independent Drive Autonomous Vehicles with Tire Dynamic Characteristics under Extreme Conditions

This paper proposes a lateral-stability-oriented path-tracking controller for four-wheel independent drive (4WID) autonomous vehicles. The proposed controller aims to maintain vehicle stability under extreme conditions while minimizing lateral deviation. Firstly, a tiered control framework comprising upper-level and lower-level controllers is introduced. The upper-level controller is a lateral stability path-tracking controller that incorporates tire dynamic characteristics, developed using model predictive control (MPC) theory. This controller dynamically updates the tire lateral force constraints in real time to account for variations in tire dynamics under extreme conditions. Additionally, it enhances lateral stability and reduces path-tracking errors by applying additional yaw torque based on minimum tire utilization. The lower-level controllers execute the required steering angles and yaw moments through the appropriate component equipment and torque distribution. The joint simulation results from CarSim and MATLAB/Simulink show that, compared to the traditional MPC controller with unstable sideslip, this controller can maintain vehicle lateral stability under extreme conditions. Compared to the MPC controller, which only considers lateral force constraints, this controller can significantly reduce lateral tracking errors, with an average yaw rate reduction of 31.62% and an average sideslip angle reduction of 40.21%.

Estimating vehicle sideslip angle through kinematic and dynamic contributions: Theory and experimental results

Vehicle lateral stability plays an important role within vehicle passenger safety. The study of lateral stability is typically related to investigating the dynamics of relevant vehicle states: among these, the vehicle sideslip angle ([Formula: see text]) emerges as a prominent candidate. Sideslip angle measurement is expensive and impractical, hence estimation techniques are often used, typically based on Kalman filters or neural networks, both with their issues. This work presents an alternative estimation method based on the idea of splitting sideslip angle into kinematic and dynamic contributions, and by observing that the kinematic contribution is straightforward to estimate. Therefore, efforts are devoted into estimating dynamic sideslip angle, which is herein obtained through a parametric interpolation harnessing lateral acceleration. Only data available from traditional vehicle onboard sensors are used in the process. Experimental results are presented along several manoeuvres on a full-scale vehicle, with the estimator running online within a dSPACE unit, ultimately supporting the efficacy and real-time feasibility of the proposed approach.

Interacting multiple model-based yaw stability control for distributed drive electric vehicle via adaptive model predictive control algorithm

The vehicle lateral stability control is a challenging problem due to the tire nonlinearity and the immeasurable sideslip angle. Thus, an adaptive model predictive control (AMPC) scheme based on interacting multiple model (IMM) vehicle sideslip angle observer is proposed in this paper. First, the observer is composed of the Extended Kalman filter (EKF) and the Unscented Kalman filter (UKF), which improves the real-time performance as well as the observation accuracy. Then, a multi-objective controller based on adaptive vehicle model prediction is designed using model predictive control algorithm. This controller aims to achieve a balance between the actuation and state constraints. The T-S fuzzy algorithm is used to observe the tire cornering stiffness and design an adaptive vehicle model. By utilizing the appropriate objective function and a quadratic programing solver, the controller output is obtained to achieve vehicle stability control. Finally, the effectiveness of the designed AMPC scheme under various working conditions is verified by Carsim-Simulink joint simulation platform and hardware-in-the-loop (HIL) test.

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.

Investigating off-road vehicle lateral stability with integrated chassis control

This study investigates the improvement of off-road vehicle lateral stability by integrated control of active rear steering (ARS) and rear differential braking (RDB) and how the performance of such systems compares on smooth and rough roads. The ARS and RDB controllers comprise a sliding mode controller (SMC) for which critical design choices are the SMC reference model, SMC gain and integration rule. Findings include that the kinematic model reference error is preferred over the phase plane location error on both terrains, the SMC gain is terrain dependent, and the rear axle slip angle is the preferred integration rule over the stability index (SI) on both terrains. The study also found that RDB, and to a lesser degree ARS, tends to improve on the baseline vehicle path-following ability for a double lane change (DLC) manoeuvre on both terrains, but RDB has a larger loss of speed compared to ARS. The Rear axle slip angle was found to be a terrain-dependent tuneable integration rule to combine ARS and RDB, and this resulted in a control system that has the good path-following ability of RDB but the low loss of speed associated with ARS after tuning.

An NMPC-Based Integrated Longitudinal and Lateral Vehicle Stability Control Based on the Double-Layer Torque Distribution.

With the ongoing promotion and adoption of electric vehicles, intelligent and connected technologies have been continuously advancing. Electrical control systems implemented in electric vehicles have emerged as a critical research direction. Various drive-by-wire chassis systems, including drive-by-wire driving and braking systems and steer-by-wire systems, are extensively employed in vehicles. Concurrently, unavoidable issues such as conflicting control system objectives and execution system interference emerge, positioning integrated chassis control as an effective solution to these challenges. This paper proposes a model predictive control-based longitudinal dynamics integrated chassis control system for pure electric commercial vehicles equipped with electro-mechanical brake (EMB) systems, centralized drive, and distributed braking. This system integrates acceleration slip regulation (ASR), a braking force distribution system, an anti-lock braking system (ABS), and a direct yaw moment control system (DYC). This paper first analyzes and models the key components of the vehicle. Then, based on model predictive control (MPC), it develops a controller model for integrated stability with double-layer torque distribution. The required driving and braking torque for each wheel are calculated according to the actual and desired motion states of the vehicle and applied to the corresponding actuators. Finally, the effectiveness of this strategy is verified through simulation results from Matlab/Simulink. The simulation shows that the braking deceleration of the braking condition is increased by 32% on average, and the braking distance is reduced by 15%. The driving condition can enter the smooth driving faster, and the time is reduced by 1.5 s~5 s. The lateral stability parameters are also very much improved compared with the uncontrolled vehicles.

Preview‐Based Path‐tracking Stability Control with Vehicle Dynamic Uncertainty via Robust Weighted LPV/[formula omitted] Technique

This article proposes a preview-based robust path-tracking control technique for maintaining lateral stability and tracking performance of autonomous vehicles, particularly in the presence of external disturbances and modeling uncertainties. First, a vehicle-road dynamic model with tire norm-bounded uncertainty is developed, which includes time-varying velocities and preview distances. The lateral and yaw dynamic characteristics are also analyzed in the frequency domain. Subsequently, an optimal preview model corresponding to sideslip-yaw rate states and longitudinal velocities is formulated employing a fuzzy logic model, and the sideslip angle is estimated using a sliding mode observer. Furthermore, a linear parameter-varying (LPV)/H∞ path-tracking controller that satisfies the pole placement and performance constraint is constructed to guarantee robustness and lateral stability across the whole parameters space with the coexistence of external disturbances and parametric uncertainties. Finally, the simulation results demonstrate that the proposed controller substantially enhances tracking performance while also maintaining excellent lateral stability.

Adaptive Advanced Emergency Braking on Combined Road Friction Coefficients

In this study, an Advanced Emergency Braking System (AEBS) is adopted to the combined road friction coefficients by proposing an emergency steering maneuver. AEBS is one of the significant driver assistant systems to avoid rear-end collisions. AEBS supports the drivers with acoustic and optical warnings before applying the full braking maneuver. However, in special cases, such as the sudden decrease of road friction coefficient during braking, a single hard braking maneuver without a proper steering assist may not be sufficient to prevent a rear-end collision. Therefore, AEBS may work with the autonomous emergency steering systems to prevent inevitable rear-end collisions. The originality of this study arises from the necessity of the adaptation of the AEBS to work in cooperation with the autonomous emergency steering systems. A predictive controller was used to support the emergency braking maneuver with an autonomous steering maneuver via observing the yaw rate of the vehicle. The predictive controller was developed in MATLAB software. The implementation of the controller was performed in a non-linear four-wheel vehicle model in the IPG/CarMaker simulation environment. The communication between the simulation environment and MATLAB software was established in the Simulink interface of MATLAB. The results proved that the predictive controller maintained the vehicle lateral stability without causing any type of collisions.

Dynamic Modeling, Simulation, and Optimization of Vehicle Electronic Stability Program Algorithm Based on Back Propagation Neural Network and PID Algorithm

Dynamic Modeling, Simulation, and Optimization of Vehicle Electronic Stability Program Algorithm Based on Back Propagation Neural Network and PID Algorithm

Real-time integrated path tracking control using input dimensionality-reducing and asynchronous sampling methods

The integrated path tracking control (PTC) of steering and braking is crucial for enhancing the stability of autonomous vehicles under extreme conditions. In the present study, a control input dimensionality-reducing method and an asynchronous sampling method are presented to address the problem of the high computational cost of the steering and braking integrated path tracking controller (PTCer) based on model predictive control (MPC). First, based on tire friction limit and tire force utilization, the control input dimensionality-reducing method is designed and a vehicle model with reduced dimensionality of control input is derived. Second, the rolling iteration mechanism of MPC is analyzed and a variable-scale asynchronous sampling method between the control loop and prediction horizon is designed with the control horizon as the boundary. Finally, the integrated MPC-PTCer based on control input dimensionality-reducing and asynchronous sampling is designed. The real-time performance (RTP), path tracking accuracy, and vehicle stability of the proposed integrated MPC-PTC are tested and evaluated through the simulation and the hardware-in-the-loop platform. The test results of different test conditions show that the proposed integrated MPC-PTC improves the RTP by more than 70% and ensures the path tracking accuracy and lateral stability of autonomous vehicles under extreme conditions.

Steering collision avoidance and lateral stability coordinated control based on vehicle lateral stability region

The balance between vehicle lateral stabilization and collision avoidance is critical for steering collision avoidance in emergency situations. On the one hand, emergency steering may cause a vehicle to lose its lateral stability. On the other hand, the overly conservative stability controller may compress the safety margin of vehicle collision avoidance, leading to failure of collision avoidance. Therefore, steering collision avoidance and lateral stability coordinated control (SCALSC) based on the vehicle stability region is proposed. The Lyapunov’s Second Method is used to obtain the lateral stability region instead of the linear two-degree-of-freedom (2-DOF) vehicle states as the stability tracking target to ensure that the vehicle states are in the stability region. The SCALSC includes an active steering controller and a direct-yaw-moment controller (DYC). An active steering controller is used for collision avoidance in emergency conditions, while DYC is used for stability control. An intervention criterion for the DYC system is proposed by using the Hurwitz criterion. Finally, a simulation test was carried out based on MATLAB/Simulink. The simulation results show that the proposed coordinated control method ensures stability, improves the safety margin of collision avoidance, and realizes multiobjective coordinated control of collision avoidance and autonomous vehicle stability control in emergency situations.

A Novel Event-Triggered Torque Vectoring Control for Improving Lateral Stability and Communication Resource Consumption of Electric Vehicles

A Novel Event-Triggered Torque Vectoring Control for Improving Lateral Stability and Communication Resource Consumption of Electric Vehicles

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.

Enhancing Vehicle Lateral Stability: A DDPG-Based Active Anti-Roll Bar Control Strategy

Enhancing Vehicle Lateral Stability: A DDPG-Based Active Anti-Roll Bar Control Strategy

A novel conservative dynamics envelope of vehicle lateral stability under different tire characteristics

This paper proposes a dynamic stability envelope based on safety maneuver margin to estimate the lateral stability of nonlinear vehicle systems with different tire characteristics (i.e. understeering (UN) and oversteering (OV) vehicles). Firstly, this study employs phase portraits and handling diagrams to investigate the number of equilibrium points and the evolution trend of state variables under various manipulation conditions. Subsequently, the nonlinear bifurcation theory is applied to analyze the characteristics of the vehicle equilibrium, aiming to derive the safe maneuver margin of the vehicle and restrict the vehicle instability. Within this proposed margin, the stability of each point of the nonlinear system is analyzed using the local linearization method. Simultaneously, a more conservative estimate of the vehicle handling stability is further obtained by applying stability criteria, resulting in the dynamic stability envelope, which ensures vehicle stability. Finally, the reliability of the dynamic stability envelope results based on the safety maneuver margin is validated under sine-with-dwell conditions (SDC) and steady-state cornering driving scenarios (SSC). The simulation results indicate that maintaining an appropriate understeering range keeps the vehicle stable.

Investigation on Aerodynamic Fluid–Structure Coupling Vibration of 160 km/h EMU Tail in Single-Track Tunnels

Recently, the phenomenon of tail-sustained swaying of the 160[Formula: see text]km/h EMU in single-track tunnels has gained much attention, especially for the rear-powered vehicle. This phenomenon is investigated from the perspective of aerodynamic fluid–structure coupling vibration in this study. The aerodynamics simulation model of the train in tunnels and the multi-body dynamics model of the rear-powered vehicle were respectively established through the software of XFlow and Simpack, and then the fluid–structure coupling vibration was simulated by using real-time data dynamic exchange between the two models. Moreover, the carbody’s vibration acceleration and the aerodynamic loads acting on the carbody under various wheel–rail contact geometrical conditions were discussed. Finally, the train tail swaying in field was tested, and the dominant frequencies were analyzed. The results show that the periodic aerodynamic loads and the frequency locking effect caused by the coupled vibration are the main factors for ride comfort deterioration. The violent vibration caused by fluid–structure coupling is named vortex-induced vibration (VIV) in some industries such as bridge and submarine pipeline. For the vehicle in this work, with the decrease of equivalent conicity in wheel–rail contact, the amplitude of carbody swaying increases owing to the carbody hunting, which enhances the fluid–structure coupling vibration, and further deteriorates the ride comfort. The swaying of the carbody is dominated by the vehicle hunting frequency, and the improvement of vehicle lateral stability can weaken this phenomenon.

Model-free autonomous control of four-wheel steering using artificial flow guidance

Four-wheel steering (4WS) is an effective technique to improve handling performance and lateral stability of road vehicles. Conventionally, controllers utilise the driver's actions and vehicle dynamics to coordinate front and rear-axle steering. This paper proposes a novel approach for 4WS controller design, based on the concept of Artificial Flow Guidance (AFG), which relies on a spatially distributed motion reference through a two-dimensional vector field. This field provides high-level guidance while lower-level steering controllers to control axle centres motions relative to the flow. These flow vectors, computed in real-time via simple geometric construction, can be pre-computed globally to evaluate the guidance algorithm's efficacy. When controlling only the front axle, this same approach can function as an autonomous driving system. Relying solely on a spatial reference field and control targets' velocities enables the controller to work in a simple and robust fashion, without using a reference vehicle dynamics model or lengthy parameter tuning. The proposed approach's effectiveness is validated through co-simulation with MATLAB/Simulink and the CarMaker simulation platform. AFG control performance is found to be at least comparable to that of more complex 4WS controllers using methods such as MPC; in the cases considered, AFG provides superior path-tracking performance.

Influence of wheelset structural flexibility on dynamic properties of a wide-gauge six-axle heavy-haul locomotive

Wheelset structural flexibility, that is the elastic deformation of the wheelset as a structure, has an important influence on the dynamic properties of railway locomotive vehicles at medium and high frequencies. Based on the practical structural parameters, this paper proposes a multi-degree of freedom rigid-flexible coupling dynamic model of a wide-gauge freight electric locomotive with C0-C0 bogies with an axle suspension driving system. The wheelset with the interference-fit large gear is made flexible using the finite element method, and then the rigid-flexible coupling vehicle model with elastic wheelsets is established in the software SIMPACK 2020. A short-wave irregularity superposed on the American fifth-grade track irregularity is used as the track excitation to study the performance at higher frequencies. From the modal analysis of the vehicle, it is obtained that the lowest frequency at which the elastic deformation of the wheelset occurs is 24.631 Hz. The lateral vibration responses of the vehicle with elastic wheelsets are reduced mainly in the frequency range of 30-150 Hz. There are two resonances in the lateral vibration responses at the mode frequencies of the vehicle over 50 Hz, which are close to the wheelset’s first mode frequency. Taking the ГОСТ standard of wide-gauge countries as the main reference, simulations are separately taken in straight-line and curved-line cases. Results show that the wheelset structural flexibility mainly influences the vehicle lateral stability and safety.

Research on Lane-Change Decision and Planning in Multilane Expressway Scenarios for Autonomous Vehicles

Taking into account the issues faced by self-driving vehicles in multilane expressway scenarios, a lane-change decision planning framework that considers two adjacent lanes is proposed. Based on this framework, the lateral stability of an autonomous vehicle under near-limit conditions during lane change is studied by the phase-plane method. Firstly, a state-machine-based driving logic is designed and a decision method is proposed to design the lane-change intention based on the surrounding traffic information and to consider the influence of the motion state of other vehicles in the adjacent lanes on the self-driving vehicle. In order to realize adaptive cruising under the full working conditions of the vehicle, a safety distance model is established for different driving speeds and switching strategies for fixed-speed cruising, following driving, and emergency braking are developed. Secondly, for the trajectory planning problem, a lane-change trajectory based on a quintuple polynomial optimization method is proposed. Then, the vehicle lateral stability boundary is investigated; the stability boundary and rollover boundary are incorporated into the designed path-tracking controller to improve the tracking accuracy while enhancing the rollover prevention capability. Finally, a simulation analysis is carried out through a joint simulation platform; the simulation results show that the proposed method can ensure the driving safety of autonomous vehicles in a multilane scenario.