An investigation into vehicle rollover prevention by coordinated control of active anti-roll bar and electronic stability program

This paper presents a method for designing a controller that uses an active anti-roll bar (AARB) and an electronic stability program (ESP) for rollover prevention. ESP with longitudinal speed control (LSC) can carry out active braking to reduce vehicle speed and lateral acceleration to prevent a rollover. To enhance the rollover prevention capability of the ESP, an AARB is adopted. The controller for the AARB was designed based on linear quadratic (LQ) static output feedback (SOF) control methodology, which attenuates the effect of lateral acceleration on the roll angle and roll rate by control of the suspension stroke and the tire deflection of the vehicle. Although this AARB significantly increases ride comfort and rollover prevention, it has a drawback — the vehicle loses its maneuverability. Therefore, the ESP with LSC is used to overcome this drawback. Simulations showed that the proposed method was effective in preventing a rollover.     

Vehicle tests of a longitudinal control law for application to stop-and-go cruise control

This paper presents the implementation and vehicle tests of a vehicle longitudinal control scheme for Stop and Go cruise control. The control scheme consists of a vehicle-to-vehicle distance control algorithm and throttle/brake control algorithm for acceleration tracking. The desired acceleration of a vehicle for vehicle-to-vehicle distance control has been designed using Linear Quadratic optimal control theory. Performance of the control algorithm has been investigated via vehicle tests. A millimeter wave radar sensor has been used for distance measurement. A stepper motor and an electronic vacuum booster have been used for throttle/ brake actuators, respectively. It has been shown that the proposed control algorithm can provide satisfactory performance.     

A multi-target tracking algorithm for application to adaptive cruise control

This paper presents a Multiple Target Tracking (MTT) Adaptive Cruise Control (ACC) system which consists of three parts; a multi-model-based multi-target state estimator, a primary vehicular target determination algorithm, and a single-target adaptive cruise control algorithm. Three motion models, which are validated using simulated and experimental data, are adopted to distinguish large lateral motions from longitudinally excited motions. The improvement in the state estimation performance when using three models is verified in target tracking simulations. However, the performance and safety benefits of a multi-model-based MTT-ACC system is investigated via simulations using real driving radar sensor data. The MTT-ACC system is tested under lane changing situations to examine how much the system performance is improved when multiple models are incorporated. Simulation results show system response that is more realistic and reflective of actual human driving behavior.     

Modeling and control of an electronic-vacuum booster for vehicle cruise control

A mathematical model and control laws for an Electronic-Vacuum Booster (EVB) For application to vehicle cruise control will be presented. Also this paper includes performance test result of EVB and vehicle cruise control experiments. The pressure difference between the vacuum chamber and the apply chamber is controlled by a PWM-solenoid-valve. Since the pressure at the vacuum chamber is identical to that of the engine intake manifold, the output of the electronic-vacuum booster is sensitive to engine speed. The performance characteristics of the electronic-vacuum booster have been investigated via computer simulations and vehicle tests. The mathematical model of the electronic-vacuum booster developed in this study and a two-state dynamic engine model have been used in the simulations. It has been shown by simulations and vehicle tests that the EVB-cruise control system can provide a vehicle with good distance control performance in both high speed and low speed stop and go driving situations.     

Nonlinear brake control for vehicle CW/CA systems

A brake control law for vehicle collision warning/collision avoidance (CW/CA) systems has been proposed in the paper. The control law has been designed for optimized safety and comfort. A solenoid-valve-controlled hydraulic brake actuator system for the CW/CA systems has been investigated. A nonlinear computer model and a linear model of the hydraulic brake actuator system have been developed. Both models were found to represent the actual system with good accuracy. Uncertainties in the brake actuator model have been considered in the design of the control law for the robustness of the controller. The effects of brake control on CW/CA vehicle response has been investigated via simulations. The simulations were performed using a complete nonlinear vehicle model. The results indicate that the proposed brake control law can provide the CW/CA vehicles with an optimized compromise between safety and comfort     

Modeling,validation and energy flow analysis of a wheel loader

This paper presents a wheel loader simulation model, validation results and energy flow analysis. The developed simulation model will facilitate the performance evaluation and optimization process in the development stage of a prototype wheel loader. The wheel loader simulation model consists of mechanical and hydraulic powertrain model, multi-body dynamic model and working part dynamic model. The multi-body dynamic model is simplified since the effect of pitch and roll motion of the wheel loader on the energy flow of the powertrain and hydraulic actuator systems is insignificant, a simplified planar model for the dynamic vehicle is good enough for the objective of this study. Every component is modeled and integrated in a simulation package developed using Matlab/Simulink. The simulation model has been validated using experiment data and the validation results show that it effectively represents the actual dynamic characteristic of the target wheel loader. The verified simulation model will be used as a virtual platform to evaluate the performance of alternative powertrain models such as a dual-clutch transmission and hydrostatic transmission. An advanced control system can also be implemented and evaluated using the virtual platform.     

Design of disturbance decoupled bilinear observers

An observer structure for bilinear systems is formulated such that the estimation error is independent of unknown external disturbances. The sufficient conditions for the existence of a stable bilinear observer are described. The proposed observer is applied to estimate the tire force in a vehicle semi-active suspension problem.     

Design and evaluation of a unified chassis control system for rollover prevention and vehicle stability improvement on a virtual test track

This paper describes the development of a unified chassis control (UCC) scheme and the evaluation of the control scheme on a virtual test track (VTT). The UCC scheme aims to prevent vehicle rollover, and to improve vehicle maneuverability and its lateral stability by integrating electronic stability control (ESC) and active front steering (AFS). The rollover prevention is achieved through speed control, and the vehicle stability is improved via yaw rate control. Since the UCC controller always works with the driver, the overall vehicle performance depends not only on how well the controller works but also on its interactions with the human driver. Vehicle behavior and the interactions between the vehicle, the controller, and the human driver are investigated through a full-scale driving simulator on the VTT which consists of a real-time vehicle simulator, a visual animation engine, a visual display, and suitable human–vehicle interfaces. The VTT has been developed and used for the evaluation of the UCC under various realistic conditions in the laboratory making it possible to evaluate the UCC controller in the laboratory without risk of injury prior to field testing, and promises to significantly reduce the cost of development as well as the overall cycle development time.     

Model predictive control-based fault detection and reconstruction algorithm for longitudinal control of autonomous driving vehicle using multi-sliding mode observer

This paper presents a model predictive control-based fault detection and reconstruction algorithm for longitudinal control of autonomous driving using a multi-sliding mode observer. In order to secure the safe longitudinal control of a vehicle, a numbers of factors must be ensured, such as the reliability of the longitudinal information, the data on the forward object from the environment sensor, and the acceleration of the ego vehicle. Thus, we propose a reasonable failure detection scheme for the acceleration signal of the host vehicle and the relative values of the front object of the radar. In order to identify the faults of the radar and the vehicle acceleration sensor related to the automated longitudinal control, the multiple sliding mode observer and prediction of model predictive control (MPC) algorithm are applied. The relative acceleration is reconstructed by applying a sliding mode observer (SMO) with clearance and relative speed measurements. The upper and lower limits of longitudinal acceleration were computed by analyzing human driving data under the preceding vehicle and reconstructed acceleration. A proper acceleration range can be defined precisely based on several reconstructed upper and lower bounds by using a multiple sliding mode observer with stored prediction data of relative values, making it possible to effectively identify the fault of the host vehicle’s acceleration sensor. By applying MPC for this study, optimal control input and prediction of relative states can be obtained that are more reasonable than those using the linear prediction model. The proposed fault detection algorithm can identify the abnormal state of the environment sensors by using the accumulated past sensor data. By comparing the stored prediction of relative states with the stored data on current states for a given period, the signal faults of the longitudinal target information can be detected from environment sensors. With these fault indices of states, the final fault diagnoses of sensors can be determined by assessing confidence through statistical analysis of 27 sets of normal driving data. In order to obtain a reasonable performance evaluation, this study uses actual driving data and a 3D full vehicle model constructed in the MATLAB/Simulink environment. The test results reveal that the proposed algorithm can successfully detect the fault of the radar and acceleration sensor of the automated driving vehicle.

     

Side slip angle based control threshold of vehicle stability control system

Vehicle Stability Control (VSC) system prevents vehicle from spinning or drifting out mainly by braking intervention. Although a control threshold of conventional VSC is designed by vehicle characteristics and centered on average drivers, it can be a redundancy to expert drivers in critical driving conditions. In this study, a manual adaptation of VSC is investigated by changing the control threshold. A control threshold can be determined by phase plane analysis of side slip angle and angular velocity which is established with various vehicle speeds and steering angles. Since vehicle side slip angle is impossible to be obtained by commercially available sensors, a side slip angle is designed and evaluated with test results. By using the estimated value, phase plane analysis is applied to determine control threshold. To evaluate an effect of control threshold, we applied a 23-DOF vehicle nonlinear model with a vehicle planar motion model based sliding controller. Controller gains are tuned as the control threshold changed. A VSC with various control thresholds makes VSC more flexible with respect to individual driver characteristics.