Vehicle Lateral Dynamics Research Articles

A cooperative control strategy for yaw rate and sideslip angle control combining torque vectoring with rear wheel steering

ABSTRACT Automobiles are becoming more and more complex as multiple control systems are integrated into the vehicle platform. This paper investigates the coordination of active rear steering (RWS) and torque vectoring (TV) – which is enabled by independent electric motors at the rear axle – in controlling vehicle lateral dynamics. The proposed controller aims at enhancing vehicle handling performance and stability while cornering. The coordination of the two actuators is achieved by weighting their contribution based on their impact on vehicle dynamics according to the working condition. The impact of each control system is assessed by means of phase portraits. These plots are a very powerful tool for analysing vehicle nonlinear dynamics as they readily display vehicle stability properties and map equilibrium point locations and movement to changing parameters and control inputs. Based on phase portrait analysis, a performance index is thus proposed, which weights more the control action (TV or RWS) capable of leading the vehicle at the nearest equilibrium point with the fastest rate. The controller performance is assessed through numerical simulations carried out using a nonlinear 14 dofs vehicle model. Results are compared with ones of the two controllers alone (RWS and TV) in different manoeuvers and adherence conditions.

Automated vehicle lateral guidance using multi-PID steering control and look-ahead point reference

In this paper, a complete analysis of the influence of a look-ahead distance and the longitudinal vehicle velocity on the vehicle lateral dynamics is made in order to choose an adequate control str...

Platoon Transitional Maneuver Control System: A Review

Connectivity and autonomy are considered two of the most promising technologies to improve mobility, fuel consumption, travel time, and traffic safety in the automated transportation industry. These benefits can be realized through vehicle platooning. A vehicle platoon is composed of a group of connected automated vehicles (CAVs) traveling together at consensual speed, following the leading vehicle (leader) while maintaining a prespecified inter-vehicle distance. This paper reviews the different existing control techniques associated with the transitional platoon maneuvers such as merge/split and lane change. Different longitudinal and lateral vehicle dynamics that are mainly used in the transitional platoon maneuvers are discussed. The most used control algorithms for both longitudinal and lateral control used for transitional platoon maneuvers are reviewed and the advantages and limitations of each control strategy are discussed. The most recent articles on platoon control maneuvers have been analyzed based on the proposed control algorithm, homogeneously or heterogeneously of platoon members, type of platoon maneuver, the aim of control problem, type of implementation, and used simulation tools. This paper also discusses different trajectory planning techniques used in lateral motion control and studies the most recent research related to trajectory planning for automated vehicles and summarizes them based on the used trajectory planning technique, platoon or/and lane change, the type of traffic, and the cost functions. Finally, this paper explores the open issues and directions for future research.

Use of Naturalistic Driving Studies for Identification of Vehicle Dynamics

This paper discusses the feasibility of data captured in a long-term Naturalistic Driving Study (NDS) for identification of vehicle dynamics. Driving data were captured for over a year. In this data capture, there was minimal effort to define or control everyday driving practices. While the use of real-world data for model parameter identification is a well-known method, NDS are commonly used to explore the behavior of drivers or to analyze real-world traffic situations. Data from NDS have not yet been used for the purpose of parameterizing vehicle dynamics models since everyday drives commonly do not reflect the full range of vehicle dynamics. This leads to the question if the data from an NDS contains the needed information to describe vehicle dynamics accurately. This paper shows that data captured from long-term everyday vehicle usage is sufficient to characterize vehicle dynamics models. It uses lateral vehicle dynamics as an example to show how the data quantity changes the model accuracy and robustness. There is a point where any further data capture produces redundancy and does not add to the overall information. The well-known single-track model serves as the modeling example which offers options to simply compare the derived model behavior with a reference.

Estimation and control of the lateral dynamics of an automotive vehicle

Estimation and control of the lateral dynamics of an automotive vehicle

T-S fuzzy observers design and actuator fault tolerant control applied to vehicle lateral dynamics

T-S fuzzy observers design and actuator fault tolerant control applied to vehicle lateral dynamics

Blending based multiple-model adaptive control of multivariable systems with application to lateral vehicle motion control

This paper develops multiple fixed model blending based adaptive parameter identification schemes for multi-input multi-output (MIMO) systems with polytopic parameter uncertainty. The developed identification schemes are proven to be asymptotically stable for uncertain linear time-invariant (LTI) MIMO systems, and is shown to provide fast adaptation for even uncertain linear time-varying (LTV) systems. Furthermore, utilizing the proposed parameter identification schemes, a linear-quadratic (LQ) optimal multiple-model adaptive control (MMAC) scheme is developed for linear MIMO systems with polytopic uncertainties. The proposed MMAC scheme is proven to be asymptotically stable for LTI MIMO systems and applied to tracking control of uncertain lateral vehicle dynamics. A set of simulation test results are presented to verify the stability, effectiveness, and comparison of the proposed MMAC scheme.

Disturbance Decoupling and Tracking Controller Design for Lateral Vehicle Dynamics

This paper addresses an augmented nonlinear lateral vehicle and lane keeping dynamics in the presence of some unknown disturbances. In a geometric basin, considering unobservable spaces, their orthogonal complements, and using control invariant properties, a disturbance decoupling mechanism is designed for the mentioned dynamics. Afterward, a nonlinear tracking controller is designed to steer the vehicle on a reference path. The obtained disturbance decoupling and tracking controllers are implemented on a typical passenger car in a simulation environment to demonstrate the effectiveness and performance of the proposed method. It is shown that the controller decouples both the uniformly distributed and exponentially attenuated disturbances from the output.

Integrated lateral dynamics control concept for over-actuated vehicles with state and parameter estimation and experimental validation

In order to improve the driving dynamics and the driving safety, the car manufacturers have introduced several systems like active front and rear steering, torque vectoring or braking systems. This work presents an integrated lateral dynamics control concept for a over-actuated vehicle. The system incorporates only sensors and actuators available in current series production cars. The driver’s commands are translated by a trajectory generation module, which calculates the desired lateral vehicle dynamics. A kinematic feedforward and a stabilizing feedback controller provide the desired vehicle motion, which is realized by an optimization-based model inversion algorithm using a nonlinear two-track model including all relevant driving dynamics effects. The convex optimization problem, taking also input constraints into account, can be solved in real-time. The non-measured states and additional parameters as the friction coefficient or the road inclination and bank angles are accurately estimated using a second order divided difference Kalman filter. Experimental validation results of a fully equipped test vehicle are provided, which show the excellent performance of the proposed control concept up to the adhesion limit of the tires on several road conditions.

Managing driving disturbances in lateral vehicle dynamics via adaptive integrated chassis control

This paper presents a vehicle stability control method based on a multi-input multi-output (MIMO) model reference adaptive control (MRAC) strategy as an advanced driver assistance system (ADAS) to enhance the handling and yaw stability of the vehicle lateral dynamics. The corrective yaw moment and additive steering angle are generated using direct yaw moment control (DYC) and active front steering (AFS) at the upper control level in the hierarchical control algorithm. A nonlinear term is added to the conventional adaptive control laws to handle parametric uncertainties and disturbances. The desired yaw moment generated by the upper-level controller is converted to the brake forces and is distributed to the rear wheels by an optimal procedure at the lower-level. The major contribution of this study is the introduction of a nonlinear integrated adaptive control method based on a constraint optimization algorithm. To verify the effectiveness of the proposed control strategy, the nonlinear integrated adaptive controller, and linear time-varying MRAC are designed and used for comparison. Simulation results are performed for the J-turn and double lane change (DLC) manoeuvres at high speeds and low tyre-road friction coefficients. The desired performance of the proposed controller exhibited significant improvement compared to the conventional MRAC in terms of yaw rate tracking and handling of sideslip limitation.

Stability Regions of Vehicle Lateral Dynamics: Estimation and Analysis

Abstract A new method is proposed to estimate and analyze the vehicle lateral stability region, which provides a direct and intuitive demonstration for the safety and stability control of ground vehicles. Based on a four-wheel vehicle model and a nonlinear two-dimensional (2D) analytical LuGre tire model, a local linearization method is applied to estimate the vehicle lateral stability regions by analyzing the vehicle stability at each operation point on a phase plane, which includes but not limited to the equilibrium points. As the collections of all the locally stable operation points, the estimated stability regions are conservative because both vehicle and tire stability are simultaneously considered, which are especially important for characterizing the stability features of highly/fully automated ground vehicles (AGV). The obtained lateral stability regions can be well explained by the vehicle characteristics of oversteering and understeering in the context of vehicle handling stability. The impacts of vehicle lateral load transfer, longitudinal velocity, tire-road friction coefficient, and steering angle on the estimated stability regions are presented and discussed. To validate the correctness of the estimated stability regions, a case study by matlab/simulink and CarSim® co-simulation is presented and discussed.

Vehicle roll centre estimation with transient dynamics via roll rate

The roll centre (RC) is a core parameter for vehicle lateral dynamics and control, which can be obtained via suspension geometry configuration or suspension kinematics and compliance (K&C) test. However, these methodologies are used for laboratory tests and are suitable at low lateral acceleration. In other words, the RC is hard to measure directly while the vehicle is running on the road. In this paper, the online RC estimation methodologies including the adaptive sliding mode observer (ASMO) and the extended Kalman filter (EKF) only with roll rate are proposed considering vehicle transient dynamics. The performance of these algorithms is evaluated and compared with the recursive least square with disturbance observer algorithm (RLSDA) via vehicle dynamics study. Simulation results manifest that, compared with the RLSDA with three roll signals, the proposed ASMO and EKF, only with roll rate, can estimate RC successfully for both the transient and steady-state cases and can be applied for online vehicle RC estimation. In detail, the proposed ASMO is recommended for the steady-state case, and the proposed EKF is recommended for the transient case. Furthermore, the static RC is recommended as the estimation initial value to improve estimation.

Unknown Input Observer Design for Linear Parameter-Varying Systems in a Bounded Error Context

This article studies unknown input observer design for linear parameter-varying systems in a bounded error context. By presenting a novel unknown input observer structure, the output equation of linear parameter-varying systems is not restricted to be in a linear form. Moreover, by integrating decoupling technique and set-membership approach, a compromise is achieved between the restrictiveness and the conservativeness of estimation. Based on P-radius criteria, sufficient design conditions are derived in terms of linear matrix inequalities. Finally, numerical simulations of a vehicle lateral dynamics system are conducted to demonstrate the validity of the presented method.

Robust $\mathcal {H}_\infty$ Filtering for Vehicle Sideslip Angle With Quantization and Data Dropouts

This paper studies the robust $\mathcal {H}_\infty$ filtering problem for the in-vehicle networked system with sensor failure, dynamic quantization and data dropouts. The nonlinear vehicle lateral dynamics is described as the Takagi-Sugeno fuzzy system. We assume that the sensor failure is adopted to present inaccurately work of the sensor, and both the measurement and performance output signals are quantized by the dynamic quantizers before being transmitted to the network channel. Moreover, the Bernoulli random binary distribution is considered to describe the data dropouts phenomenon both in the measurement and performance outputs. The proposed filter design method is given in the form of linear matrix inequalities which guarantee that the filtering error system is stochastically stable with $\mathcal {H}_\infty$ performance index. Finally, the co-simulation of the Matlab/Simulink and Carsim is used to validate the proposed filter design method.

Vehicle sideslip estimation via kernel-based LPV identification: Theory and experiments

Many vehicle control systems depend on the body sideslip angle, but robust and cost-effective direct measurement of this angle is yet to be achieved for production vehicles. Estimation from indirect measurements is thus the only viable option. In the paper, a sideslip estimator is obtained through the identification of a linear parameter varying (LPV) model. Although inspired by physical insights into the vehicle lateral dynamics, the structure of the LPV estimator is not parametrized beforehand. Instead, the estimator is learned by means of a state-of-the-art non-parametric method for linear parameter varying identification, namely least-squares support vector machines (LS-SVM). Its performance is assessed over an extensive and heterogeneous set of experimental data, showing the effectiveness of the proposed estimator.

Relaxed State and Fault Estimation for Vehicle Lateral Dynamics Represented by T–S Fuzzy Systems

This paper deals with the problem of observer design of the vehicle model which is represented by Takagi–Sugeno (T–S) fuzzy systems with the presence of uncertainties. A relaxed observer design is presented to estimate the unmeasurable states and the faults of the vehicle lateral dynamics model, simultaneously. The vehicle model is transformed into a system with unknown inputs. Then, it is rebuilt by adding the default to the system state equation. Based on the Lyapunov function approach and the introduction of some slack variables, sufficient conditions of unknown input observer design are formulated as Linear Matrix Inequalities (LMIs). Finally, the simulation section clearly shows the importance and effectiveness of the proposed strategy.

On Nonlinear Model Predictive Control for Energy-Efficient Torque-Vectoring

A recently growing literature discusses the topics of direct yaw moment control based on model predictive control (MPC), and energy-efficient torque-vectoring (TV) for electric vehicles with multiple powertrains. To reduce energy consumption, the available TV studies focus on the control allocation layer, which calculates the individual wheel torque levels to generate the total reference longitudinal force and direct yaw moment, specified by higher level algorithms to provide the desired longitudinal and lateral vehicle dynamics. In fact, with a system of redundant actuators, the vehicle-level objectives can be achieved by distributing the individual control actions to minimize an optimality criterion, e.g., based on the reduction of different power loss contributions. However, preliminary simulation and experimental studies – not using MPC – show that further important energy savings are possible through the appropriate design of the reference yaw rate. This paper presents a nonlinear model predictive control (NMPC) implementation for energy-efficient TV, which is based on the concurrent optimization of the reference yaw rate and wheel torque allocation. The NMPC cost function weights are varied through a fuzzy logic algorithm to adaptively prioritize vehicle dynamics or energy efficiency, depending on the driving conditions. The results show that the adaptive NMPC configuration allows stable cornering performance with lower energy consumption than a benchmarking fuzzy logic TV controller using an energy-efficient control allocation layer.

Cooperative ecological cruising using hierarchical control strategy with optimal sustainable performance for connected automated vehicles on varying road conditions

Facing the increasingly severe energy and environmental problems, platooning of multiple vehicles has great potential for sustainability of intelligent transportation systems. This study develops a novel hierarchical ECACC strategy with energy-saving achievements by conducting the ecological velocity trajectory planning of the leading vehicle based on dynamic programming and car-following driving of the rest of the vehicles in the platoon based on combined feedforward-feedback control. The main purpose is to reduce the energy consumption of multiple vehicles in intelligent transportation systems with consideration of trip time and car-following performance. The optimal velocity planning uses an innovative integrated longitudinal and lateral vehicle dynamics approach where both the lateral stability and energy efficiency in continuous curved roads are guaranteed at the same time. The results show that the proposed ECACC in energy-optimal mode can reduce energy consumption by up to 38.1% compared to conventional energy-optimal fixed speed cruising. Moreover, the connected automated vehicle platoon presents better car-following performance with string stability as opposed to the Cooperative Adaptive Cruise Control based on feedback control and model predictive control. The results indicate the great potential of the proposed ECACC strategy to further improve the sustainability of intelligent transportation systems.

A nonlinear dynamical approach to the path correction of multi-steering articulated vehicles

ABSTRACT When designing articulated tractor-trailer systems, engineers should take care to contrast some undesired phenomena associated with the lateral dynamics: the path off-tracking, namely the trajectory deviation of the points of the two units compared to the midpoint of the tractor fore; the rearward amplification of the transverse acceleration. The off-tracking may lead the vehicle tail to invade the opposite direction lane or the emergency lane, whereas the rearward amplification may involve the danger of the trailer rollover. Nonetheless, the arrangement of multi-steering axle systems with the proper correlation among the steering angles may substantially cancel the off-tracking, both along a path with constant curvature and while entering or leaving the road bend. Moreover, the proper control of the increase and decrease of the steering angle during the transient phases can restrain the lateral acceleration of the towed unit. The present analysis considers several nonlinear effects of the vehicle lateral dynamics, such as large steering angles, nonlinear cornering characteristics and changes of the cornering forces because of the centrifugal effect. The goal is a practical formulation of the correlation among the steering angles to correct the vehicle run and ensure lateral stability.

Repetitive control design for vehicle lateral dynamics with state‐delay

In this work, the authors precisely concentrate on the subject of enhanced vehicle handling performance of the bicycle model with two-degrees-of-freedom via improved-equivalent-input-disturbance and repetitive control technique. To be specific, improved-equivalent-input-disturbance estimator is inserted into the controller design for attenuating the effect of the crosswind in the considered vehicle system with state-delay. A modified two-dimensional repetitive control design is implemented for improving the accurate tracking performance of the considered model. In particular, by combining an improved-equivalent-input-disturbance approach together with two-dimensional modified repetitive control design, steering angles of front and rear wheels of the considered vehicle have been controlled in order to achieve the accurate tracking performance of the vehicle states. The criteria for the robust asymptotic stability on the basis of Lyapunov stability theory is developed by means of the sufficient conditions which are obtained in the form of linear-matrix-inequalities. Simultaneously, through these inequality conditions, the parameters of proposed improved-equivalent-input-disturbance based repetitive control strategy are designed for improving the accurate tracking performance against the crosswind effect. Finally, simulation results are presented to show that the proposed control design is more effective when aperiodic disturbances occur.