In this paper, we investigate the vehicle lateral dynamics stabilisation problem to enhance vehicle handling by considering time-varying longitudinal velocity. The longitudinal velocity is described by a polytope with finite vertices and a novel technique is proposed to reduce the number of vertices. Since the tyre dynamics is nonlinear, the cornering stiffness is represented via the norm-bounded uncertainty. Concerning the time-varying velocity and the nonlinear tyre model, a linear parameter-varying vehicle model is obtained. As the velocity and the states are measurable, a gain-scheduling state-feedback controller is introduced. In the lateral control, the sideslip angle is required to be as small as possible and the yaw rate is constrained to a certain level. Thus, the control objective is to minimise the sideslip angle while the yaw rate is under a prescribed level or constrain both the sideslip angle and the yaw rate to prescribed levels. To consider the transient response of the closed-loop system,...

Robust gain-scheduling energy-to-peak control of vehicle lateral dynamics stabilisation

Considering the uncertainty of tyre cornering stiffness due to the frequent variation of running conditions, a new coordination scheme is proposed based on optimal guaranteed cost control technique by coordinating active front steering and direct yaw moment control. A general procedure to develop an optimal guaranteed cost coordination controller (OGCC) is presented, and the effect of uncertainty deviation magnitude on the control system is discussed. An optimal coordination (OC) scheme based on LQR is also presented. Many simulations are carried out on an 8-DOF nonlinear vehicle model for a slalom manoeuvre and a lane-change manoeuvre, respectively. The simulation results show that the OGCC scheme has superior stability and tracking performances at different running conditions compared with the OC scheme.

Coordinated control of AFS and DYC for vehicle handling and stability based on optimal guaranteed cost theory

This paper presents a robust yaw-moment controller design for improving vehicle handling and stability with considerations of parameter uncertainties and control saturation. The parameter uncertainties dealt with are the changes of vehicle mass and moment of inertia about the yaw axis and the variations of cornering stiffnesses. The control saturation considered is due to the physical limitations of actuators and tires. Both polytopic and norm-bounded approaches are used to describe parameter uncertainties, and a norm-bounded approach is applied to handle the saturation nonlinearity. The conditions for designing such a controller are derived as linear matrix inequalities (LMIs). A nonlinear vehicle model is utilized to validate the effectiveness of the proposed approach. The simulation results show that the designed controller can improve vehicle handling and stability, regardless of the changes in vehicle mass and moment of inertia and the variations of road surfaces and saturation limitations.

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Stabilizing Vehicle Lateral Dynamics With Considerations of Parameter Uncertainties and Control Saturation Through Robust Yaw Control

This paper focuses on the vehicle dynamic control system for a four in-wheel motor drive electric vehicle, aiming at improving vehicle stability under critical driving conditions. The vehicle dynamics controller is composed of three modules, i.e. motion following control, control allocation and vehicle state estimation. Considering the strong nonlinearity of the tyres under critical driving conditions, the yaw motion of the vehicle is regulated by gain scheduling control based on the linear quadratic regulator theory. The feed-forward and feedback gains of the controller are updated in real-time by online estimation of the tyre cornering stiffness, so as to ensure the control robustness against environmental disturbances as well as parameter uncertainty. The control allocation module allocates the calculated generalised force requirements to each in-wheel motor based on quadratic programming theory while taking the tyre longitudinal/lateral force coupling characteristic into consideration. Simulations under a variety of driving conditions are carried out to verify the control algorithm. Simulation results indicate that the proposed vehicle stability controller can effectively stabilise the vehicle motion under critical driving conditions.

Vehicle dynamics control of four in-wheel motor drive electric vehicle using gain scheduling based on tyre cornering stiffness estimation

This paper investigates a hierarchically coordinated vehicle dynamics control approach with individual wheel torque and steering actuation. A high-level robust nonlinear sliding mode controller is designed to determine the generalized forces/moments required to achieve vehicle motion objectives. A weighted pseudo-inverse based control allocation method is employed for computationally efficient distribution of control effort to the slip and slip angle of each wheel. To avoid saturation, tire-road friction estimation is an essential part of the control distribution scheme. Two adverse driving scenario simulations are used to evaluate the effectiveness of this control system.

Coordinated vehicle dynamics control with control distribution

Recent trends of vehicle chassis control are reviewed, paying attention to the basic nature of the vehicle dynamics, tyre characteristics and the effectiveness and limit of four-wheel steer...

M Abe

Papers

Vehicle dynamics and control for improving handling and active safety: From four-wheel steering to direct yaw moment control