线控转向系统控制技术综述

线控转向系统通过线控化、智能化可以实现个性驾驶、辅助驾驶、无人驾驶等目标,是智能网联汽车落地的关键技术,其相关动力学控制技术更是影响线控转向系统整体性能的核心技术.该文介绍了线控转向系统的基本结构类型及其动力学建模,分别对线控转向系统的路感控制技术、稳定性控制技术、容错控制技术等关键技术进行了全面概述,分析了线控转向技...     

Robust control for four-wheel-independent-steering electric vehicle with steer-by-wire system

A four-wheel-independent-steering (4WIS) electric vehicle (EV) with steer-by-wire (SBW) system is proposed in this paper. The fast terminal sliding mode controller (FTSMC) is designed for the SBW system to suppress external disturbances. Taking unstructured and structured uncertainties into consideration, a robust controller is designed for the 4WIS EV utilizing μ synthesis approach and the controller order reduction is implemented based on Hankel-Norm approximation. Since sideslip angle is the feedback signal of robust controller and it is hard to measure, the extended Kalman filter (EKF) is employed to estimate sideslip angle. To evaluate the vehicle performance with the designed control system, step and sinusoidal steering maneuvers are simulated and analyzed. Simulation results show that the designed control system have good tracking ability, strong robust stability and good robust performance to improve vehicle stability and handing performance.     

A vehicle stability control strategy with adaptive neural network sliding mode theory based on system uncertainty approximation

Modelling uncertainty, parameter variation and unknown external disturbance are the major concerns in the development of an advanced controller for vehicle stability at the limits of handling. Sliding mode control (SMC) method has proved to be robust against parameter variation and unknown external disturbance with satisfactory tracking performance. But modelling uncertainty, such as errors caused in model simplification, is inevitable in model-based controller design, resulting in lowered control quality. The adaptive radial basis function network (ARBFN) can effectively improve the control performance against large system uncertainty by learning to approximate arbitrary nonlinear functions and ensure the global asymptotic stability of the closed-loop system. In this paper, a novel vehicle dynamics stability control strategy is proposed using the adaptive radial basis function network sliding mode control (ARBFN-SMC) to learn system uncertainty and eliminate its adverse effects. This strategy adopts a hierarchical control structure which consists of reference model layer, yaw moment control layer, braking torque allocation layer and executive layer. Co-simulation using MATLAB/Simulink and AMESim is conducted on a verified 15-DOF nonlinear vehicle system model with the integrated-electro-hydraulic brake system (I-EHB) actuator in a Sine With Dwell manoeuvre. The simulation results show that ARBFN-SMC scheme exhibits superior stability and tracking performance in different running conditions compared with SMC scheme.     

Integrated control of ground vehicles dynamics via advanced terminal sliding mode control

An integrated vehicle dynamics control (IVDC) algorithm, developed for improving vehicle handling and stability under critical lateral motions, is discussed in this paper. The IVDC system utilises integral and nonsingular fast terminal sliding mode (NFTSM) control strategies and coordinates active front steering (AFS) and direct yaw moment control (DYC) systems. When the vehicle is in the normal driving situation, the AFS system provides handling enhancement. If the vehicle reaches its handling limit, both AFS and DYC are then integrated to ensure the vehicle stability. The major contribution of this paper is in improving the transient response of the vehicle yaw rate and sideslip angle tracking controllers by implementing advanced types of sliding mode strategies, namely integral terminal sliding mode and NFTSM, in the IVDC system. Simulation results demonstrate that the developed control algorithm for the IVDC system not only has strong robustness against uncertainties but also improves the transient response of the control system.     

Lyapunov control of vehicle handling dynamics

Nonlinear control is applied to road vehicle handing dynamics, and performance is evaluated under conditions where road friction is uncertain and rapidly changing. This is in contrast to earlier control schemes which rely on prescribed or detailed estimation of road friction. Particular attention is devoted to the problem of adapting the reference signals to achieve effective and stable control.     

Fuzzy adaptive sliding mode controller for an air spring active suspension

A fuzzy adaptive sliding mode controller for an air spring active suspension system is developed. Due to nonlinearity, preload-dependent spring force and parameter uncertainty in the air spring, it is difficult to control the suspension system. To achieve the desired performance, a fuzzy adaptive sliding mode controller (FASMC) is designed to improve the passenger comfort and the manipulability of the vehicle. The fuzzy adaptive system handles the nonlinearity and uncertainty of the air suspension. A normal linear suspension model with an optimal state feedback control is designed as the reference model. The simulation results show that this control scheme more effectively and robustly isolates vibrations of the vehicle body than the conventional sliding mode controller (CSMC).     

State observer-based sliding mode control for semi-active hydro-pneumatic suspension

This paper proposes an improved virtual reference model for semi-active suspension to coordinate the vehicle ride comfort and handling stability. The reference model combines the virtues of sky-hook with ground-hook control logic, and the hybrid coefficient is tuned according to the longitudinal and lateral acceleration so as to improve the vehicle stability especially in high-speed condition. Suspension state observer based on unscented Kalman filter is designed. A sliding mode controller (SMC) is developed to track the states of the reference model. The stability of the SMC strategy is proven by means of Lyapunov function taking into account the nonlinear damper characteristics and sprung mass variation of the vehicle. Finally, the performance of the controller is demonstrated under three typical working conditions: the random road excitation, speed bump road and sharp acceleration and braking. The simulation results indicated that, compared with the traditional passive suspension, the proposed control algorithm can offer a better coordination between vehicle ride comfort and handling stability. This approach provides a viable alternative to costlier active suspension control systems for commercial vehicles.     

Coordinated control strategies for active steering,differential braking and active suspension for vehicle stability,handling and safety improvement

ABSTRACT

In this paper, a coordinated control strategy is proposed to provide an effective improvement in handling stability of the vehicle, safety, and comfortable ride for passengers. This control strategy is based on the coordination among active steering, differential braking, and active suspension systems. Two families of controllers are used for this purpose, which are the high order sliding mode and the backstepping controllers. The control strategy was tested on a full nonlinear vehicle model in the environment of MATLAB/Simulink. Rollover avoidance and yaw stability control constraints have been considered. The control system mainly focuses on yaw stability control. When rollover risk is detected, the proposed strategy controls the roll dynamics to decrease rollover propensity. Simulation results for two different critical driving scenarios, the first one is a double lane change and the other one is a J-turn manoeuvre, show the effectiveness of the coordination strategy in stabilising the vehicle, enhancing handling and reducing rollover propensity.     

A reduced-order nonlinear sliding mode observer for vehicle slip angle and tyre forces

In this paper, a reduced-order sliding mode observer (RO-SMO) is developed for vehicle state estimation. Several improvements are achieved in this paper. First, the reference model accuracy is improved by considering vehicle load transfers and using a precise nonlinear tyre model ‘UniTire’. Second, without the reference model accuracy degraded, the computing burden of the state observer is decreased by a reduced-order approach. Third, nonlinear system damping is integrated into the SMO to speed convergence and reduce chattering. The proposed RO-SMO is evaluated through simulation and experiments based on an in-wheel motor electric vehicle. The results show that the proposed observer accurately predicts the vehicle states.     

Optimisation of active suspension control inputs for improved vehicle handling performance

Active suspension is commonly considered under the framework of vertical vehicle dynamics control aimed at improvements in ride comfort. This paper uses a collocation-type control variable optimisation tool to investigate to which extent the fully active suspension (FAS) application can be broaden to the task of vehicle handling/cornering control. The optimisation approach is firstly applied to solely FAS actuator configurations and three types of double lane-change manoeuvres. The obtained optimisation results are used to gain insights into different control mechanisms that are used by FAS to improve the handling performance in terms of path following error reduction. For the same manoeuvres the FAS performance is compared with the performance of different active steering and active differential actuators. The optimisation study is finally extended to combined FAS and active front- and/or rear-steering configurations to investigate if they can use their complementary control authorities (over the vertical and lateral vehicle dynamics, respectively) to further improve the handling performance.     

Sliding mode observation and control for semiactive vehicle suspensions

This paper investigates the application of robust, nonlinear observation and control strategies, namely sliding mode observation and control (SMOC), to semiactive vehicle suspensions using a model reference approach. The vehicle suspension models include realistic nonlinearities in the spring and magnetorheological (MR) damper elements, and the nonlinear reference models incorporate skyhook damping. Since full state measurement is difficult to achieve in practice, a sliding mode observer (SMO) that requires only suspension deflection as a measured input is developed. The performance and robustness of sliding mode control (SMC), SMO, and SMOC are demonstrated through comprehensive computer simulations and compared to popular alternatives. The results of these simulations reveal the benefits of sliding mode observation and control for improved ride quality, and should be directly transferable to commercial semiactive vehicle suspension implementations.     

Sliding mode observation and control for semiactive vehicle suspensions

This paper investigates the application of robust, nonlinear observation and control strategies, namely sliding mode observation and control (SMOC), to semiactive vehicle suspensions using a model reference approach. The vehicle suspension models include realistic nonlinearities in the spring and magnetorheological (MR) damper elements, and the nonlinear reference models incorporate skyhook damping. Since full state measurement is difficult to achieve in practice, a sliding mode observer (SMO) that requires only suspension deflection as a measured input is developed. The performance and robustness of sliding mode control (SMC), SMO, and SMOC are demonstrated through comprehensive computer simulations and compared to popular alternatives. The results of these simulations reveal the benefits of sliding mode observation and control for improved ride quality, and should be directly transferable to commercial semiactive vehicle suspension implementations.     

Reconfigurable fault-tolerant controller synthesis for a steer-by-wire vehicle using independently driven wheels

In this paper, a synthesis method for a reconfigurable fault-tolerant control system for use in a steer-by-wire vehicle is proposed. The vehicle considered in this paper is also assumed to have independently driven wheels. The control objective in this work is to enable the vehicle yaw rate to track the reference signal even when the steering actuator breaks down. Since the vehicle yaw rate can be controlled with either the front wheel turn angle or the yaw moment generated by the independently driven wheels, this system has actuator redundancy. We attempt to design a control system that manages this actuator redundancy so that the performance degradation due to the actuator failure is minimised. We utilise a control allocator based on on-line optimisation for managing the actuator redundancy. The fault-tolerant control system with a control allocator has several excellent properties. For example, the method can handle various failure situations. Also, since the control allocation problem is reduced to a convex quadratic programming problem, the on-line computational effort is relatively little. However, so far, it has been unclear whether the stability of the control system with the control allocator is guaranteed when the actuator failure occurs. Therefore, we propose a design method of a fault-tolerant controller based on on-line optimisation that guarantees the stability of the overall system. The effectiveness of the method is established through numerical examples.     

Nonlinear robust control of integrated vehicle dynamics

A new methodology to design the vehicle GCC (global chassis control) nonlinear controller is developed in this paper. Firstly, to handle the nonlinear coupling between sprung and unsprung masses, the vehicle is treated as a mechanical system of two-rigid-bodies which has 6 DOF (degree of freedom), including longitudinal, lateral, yaw, vertical, roll and pitch dynamics. The system equation is built in the yaw frame based on Lagrange's method, and it has been proved that the derived system remains the important physical properties of the general mechanical system. Then the GCC design problem is formulated as the trajectory tracking problem for a cascade system, with a Lagrange's system interconnecting with a linear system. The nonlinear robust control design problem of this cascade interconnected system is divided into two H _∞ control problems with respect to the two sub-systems. The parameter uncertainties in the system are tackled by adaptive theory, while the external uncertainties and disturbances are dealt with the H _∞ control theory. And the passivity of the mechanical system is applied to construct the solution of nonlinear H _∞ control problem. Finally, the effectiveness of the proposed controller is validated by simulation results even during the emergency manoeuvre.     

Rollover prevention for heavy trucks using frequency shaped sliding mode control

Control and handling of heavy commercial vehicles carrying liquid cargo are influenced by liquid movement within the partially filled tank. During steering and braking maneuvering tasks, the truck may exhibit unstable behavior at lateral acceleration levels of 0.3 g to 0.4 g [m/s²]. The fluid slosh forces and dynamic load transfers in the lateral and longitudinal directions and parametric uncertainties caused by moving liquid cargo affect the overall dynamics of the vehicle. To solve a physical problem about the minimal excitation of the slosh dynamics associated with the longitudinal and lateral excitation of the vehicle, dynamic sliding surface design combined with recursive backstepping algorithm is introduced. Compensator dynamics are introduced in the sliding mode through a class of switching surfaces which has the interpretation of linear operators such that the resulting closed-loop system retains the insensitivity to uncertainties in the sliding mode while minimizing the excitation of flexible modes and unmodeled dynamics. The frequency shaped backstepping sliding mode algorithm, proposed by Acarman and Özgüner [Frequency shaping compensation for backstepping sliding mode control. Paper presented at the 15th IFAC World Congress, Barcelona, Spain, 2002], is designed to stabilize and to attenuate the sloshing effects of moving cargo by properly choosing the crossover frequencies of the dynamic compensators in accordance with the fundamental frequencies of the slosh dynamics.     

Nonlinear sliding mode observer for exhaust manifold pressure estimation in a light-duty diesel engine

In this paper, a sliding mode observer is proposed to estimate exhaust pressure for a diesel engine equipped with variable geometry turbocharger (VGT) and exhaust gas recirculation (EGR) systems. Since the exhaust pressure directly affects generation of the VGT power and the EGR rate in the cylinder, the exhaust pressure information is important for precise control of the VGT and EGR systems. In order to estimate the exhaust pressure accurately, a dynamic model of intake and exhaust pressure was derived. Furthermore, the mass flow rate and temperature of the air system in the diesel engines were modeled by consideration of physical phenomena and the thermodynamic law. Based on the developed models, a nonlinear sliding mode observer was designed to estimate the exhaust pressure. Convergence of the proposed observer was verified by the Lyapunov stability criterion. The proposed observer was implemented on a real-time embedded system and validated with the engine experiments. The experimental results show that the observer estimates the exhaust pressure accurately in both steady and transient engine operating conditions. Moreover, as a case study, the estimation results of the proposed observer could be applied for detecting a fault of the EGR system. The fault of the EGR system was detected precisely using the estimation result and the limited sensor information in mass-produced engines.     

Self-tuning control algorithm design for vehicle adaptive cruise control system through real-time estimation of vehicle parameters and road grade

The main purpose of this paper is to design a self-tuning control algorithm for an adaptive cruise control (ACC) system that can adapt its behaviour to variations of vehicle dynamics and uncertain road grade. To this aim, short-time linear quadratic form (STLQF) estimation technique is developed so as to track simultaneously the trend of the time-varying parameters of vehicle longitudinal dynamics with a small delay. These parameters are vehicle mass, road grade and aerodynamic drag-area coefficient. Next, the values of estimated parameters are used to tune the throttle and brake control inputs and to regulate the throttle/brake switching logic that governs the throttle and brake switching. The performance of the designed STLQF-based self-tuning control (STLQF-STC) algorithm for ACC system is compared with the conventional method based on fixed control structure regarding the speed/distance tracking control modes. Simulation results show that the proposed control algorithm improves the performance of throttle and brake controllers, providing more comfort while travelling, enhancing driving safety and giving a satisfactory performance in the presence of different payloads and road grade variations.     

Sliding mode observers for vehicle mode detection

This paper explores the use of sliding mode observers to detect the onset of potentially dangerous vehicle modes such as oversteer, understeer or split-μ braking. Provided these modes can be detected quickly enough, existing stability controllers can be engaged to ensure safe performance of the vehicle. It is shown that the equivalent output error injection signals associated with the sliding mode observer have distinctive signatures depending on the particular mode encountered. Appropriate thresholds on these signals can be set so the scheme ignores variations which arise during normal driving, but can detect and isolate different undesirable vehicle modes within 0.3 seconds of their onset.