Lateral acceleration potential field function control for rollover safety of multi-wheel military vehicle with in-wheel-motors

This article proposes an automatic longitudinal deceleration based method for multi-wheel vehicle rollover safety in autonomous mode. The information of lateral acceleration and vehicle roll angle is used to generate the longitudinal acceleration at which the vehicle will remain stable to rollover. The lateral and roll dynamics are coupled with longitudinal dynamics using a potential field function for lateral acceleration. This virtual potential field is developed on g-g diagram which represents vehicle portrait of lateral and longitudinal acceleration on abscissa and ordinate respectively. The motion of vehicle is represented by a point moving on this phase portrait of g-g diagram. TruckSim model of multi-wheel military vehicle with in-wheel motors is used with this algorithm which shows that the vehicle is less susceptible to rollover. The safe longitudinal acceleration is achieved by torque control of in-wheel motors fitted in each wheel. Using this method, the vehicle followed the desired trajectory as higher speeds which are safe. This is particularly useful for vehicle autonomous driving with rollover stability.

     

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.     

Hybrid attitude control in steering maneuver using ARC Hil setup

This paper presents the design of an active roll controller for a vehicle and an experimental study using an electric actuating roll control system. Firstly, based on a three degrees of freedom linear vehicle model, the controller is designed using lateral acceleration and rollrate feedback. In order to investigate the feasibility of an active control system, experimental work is carried out using a hardware-in-the-loop (Hil) setup which has been constructed using the devised electric actuating system and the full vehicle model including tire characteristics. The performance is evaluated by an experiment using the Hil setup in which steering maneuvers are carried out. Finally, in order to enhance the control performance in a transient region, the hybrid control strategy is proposed and evaluated.     

Detection of Impending Vehicle Rollover with Road Bank Angle Consideration Using a Robust Fuzzy Observer

 This article describes a method of vehicle dynamics estimation for impending rollover detection. We estimate vehicle dynamic states in presence of the road bank angle as a disturbance in the vehicle model using a robust observer. The estimated roll angle and roll rate are used to compute the rollover index which is based on the prediction of the lateral load transfer. In order to anticipate rollover detection, a new method is proposed to compute the time to rollover (TTR) using the load transfer ratio (LTR). The nonlinear model, deduced from the vehicle lateral and roll dynamics, is represented by a Takagi-Sugeno (T-S) fuzzy model. This representation is used to account for the nonlinearities of lateral cornering forces. The proposed T-S observer is designed with unmeasurable premise variables to cater for non-availability of the slip angles measurement. The proposed approach is evaluated using CarSim simulator under different driving scenarios. Simulation results show good efficiency of the proposed T-S observer and the rollover detection method.     

重型车辆侧翻预警系统的开发

建立了重型车辆三自由度车辆模型,经过鱼钩工况仿真验证,确定此模型比较准确,可用于预警系统的仿真研究;以横向载荷转移率(LTR)预警门限值为参考值,应用经典卡尔曼滤波原理对车辆运行状态进行实时估计,实时计算出反映侧倾危险的侧翻时刻,从而开发了一套对重型车辆进行观测的侧翻预警系统。经在高附着路面上进行实车试验,设LTR预警门限值为0.2,侧翻时刻为3s,并在侧向加速度为0.2的条件下,该系统能及时做出预报,说明此系统有效可靠。     

Adaptive rollover prevention controller for driver–vehicle systems

In the paper, we propose an adaptive rollover prevention controller for heavy vehicles. At first, a design method for an ideal vehicle model is proposed. The designed ideal vehicle model has the property that good rollover prevention performance can be assured even if the driver steering characteristics vary. If the behavior of the actual heavy vehicle tracks that of the designed ideal vehicle model, rollover prevention can be achieved. Therefore, next, to realize good rollover prevention, we propose an adaptive steering controller. In the heavy vehicle system using the controller, the actual heavy vehicle can track the ideal vehicle model. Then, rollover prevention can be achieved. Finally, to demonstrate the usefulness of the proposed controller, numerical simulations are carried out.     

汽车侧翻预警及防侧翻控制

为了减少汽车侧翻事故,提出了一种基于模型的汽车侧翻预警算法以及在预警基础上的防侧翻控制算法.预警算法通过三自由度线性汽车侧翻模型计算将来一段时间内汽车横向载荷转移律的绝对值,由侧翻条件得到侧翻危险时间;控制算法根据预警时间来触发比例-微分控制器对汽车实施控制.结果表明,预警算法能够及时准确预测汽车侧翻危险,而控制方法可以更好地发挥制动器效能,防止汽车侧翻.     

智能车载感知与侧翻预警系统的设计

为了防止汽车在行驶过程中发生侧翻,使汽车始终处在安全工况下行驶,减少交通事故,设计了一种基于ARM9的智能车载感知和侧翻预警系统,对汽车在途行驶时的侧倾角和侧倾角速度进行监测,并采用多阶递推模型对汽车侧倾姿态进行预测,当预测到侧倾达到极限工况时发出报警信息,提醒驾驶人员注意并采取相应减少侧向加速度的措施,从而达到预防汽车侧翻事故的发生,并基于VB2005,Matlab和NIMeasurement Studio开发了车载感知与侧翻预警系统软件,进行了系统仿真。实车道路试验与系统仿真实验进行了比较,结果表明:车载感知和预警系统能够及时准确预测汽车侧翻,提高汽车主动安全。     

汽车操纵稳定性的自适应控制策略研究

针对汽车系统的非线性和参数不确定性,设计了一种“前馈+反馈”自适应神经模糊控制器,通过ESP和AFS的协调控制来提高汽车操纵稳定性.ESP反馈控制器采用模糊控制策略,以横摆角速度和质心侧偏角为控制目标;AFS前馈控制器采用径向基神经网络控制,以反馈控制器的输出作为误差进行学习,从而实现自适应控制.仿真结果表明,上述控制策略是可行和有效的,能显著改善汽车在高速或湿滑路面上的操纵稳定性.     

考虑车辆横向主动安全的智能驾驶员模型

结合智能车面临的横向安全问题, 设计了一种具有横向安全性的智能驾驶员模型. 该系统由转向控制、速度控制和决策规划三个模块组成. 该系统的主要作用包括: 一是通过在转向控制中加入主要约束提高车辆在转向过程中的横向稳定性, 减小车辆发生侧滑、侧倾、侧偏等风险; 二是在换道场景下, 决策规划单元合理分析交通环境中的车间距并计算出驶入临近车道的速度和轨迹, 使智能车实现安全换道. CarSim/Simulink仿真结果表明, 该智能驾驶员系统提高了车辆行驶的横向安全性.     

A novel integrated control framework of AFS,ASS, and DYC based on ideal roll angle to improve vehicle stability

The current research on vehicle stability control mainly focuses on following the ideal yaw rate and sideslip angle, without considering the potential of ideal roll angle in improving the vehicle stability. In addition, the mutation of tire-road friction coefficient promotes a great challenge to the stability control. To improve the vehicle stability, in this study, firstly, the three-dimensional stability region of “lateral speed-yaw rate-roll angle” was studied, and a method to determine the ideal roll angle was proposed. Secondly, a novel integrated control framework of AFS, ASS, and DYC based on ideal roll angle was proposed to actively control the front tire slip angles, suspension forces, and motor torques: In the upper-level controller, model predictive control and tire force distribution algorithm were used to obtain the optimal four-tire longitudinal forces, front tire lateral forces and additional roll moment under constraints; In the lower-level controller, the upper virtual target was realized by the optimal allocation algorithm of actuators and the tire slip controller. Finally, the proposed control framework was verified on the varied-µ road. The results indicated that compared with the two existing control strategies, the proposed framework can significantly improve the vehicle following performance and stability.     

Lateral motion stability control of electric vehicle via sampled-data state feedback by almost disturbance decoupling

The paper presents a lateral motion stability control method for electric vehicle (EV) driven by four in-wheel motors, which considers time-variable vehicle speed and uncertain disturbance caused by external factors. First, an EV lateral motion dynamics tracking control model is presented. Then in order to deal with the uncertain disturbance in the lateral motion model, an almost disturbance decoupling method using sampled-data state feedback is proposed. Third, a sampled-data state feedback controller is constructed based on the state feedback domination approach. The proposed controller can attenuate the disturbances’ effect on the output to an arbitrary degree of accuracy. Simulation and test results under different vehicle speeds show the effectiveness of the control method.     

Active steering control strategy for articulated vehicles

To improve maneuverability and stability of articulated vehicles, we design an active steering controller, including tractor and trailer controllers, based on linear quadratic regulator (LQR) theory. First, a three-degree-of-freedom (3-DOF) model of the tractor-trailer with steered trailer axles is built. The simulated annealing particle swarm optimization (SAPSO) algorithm is applied to identify the key parameters of the model under specified vehicle speed and steering wheel angle. Thus, the key parameters of the simplified model can be obtained according to the vehicle conditions using an online look-up table and interpolation. Simulation results show that vehicle parameter outputs of the simplified model and TruckSim agree well, thus providing the ideal reference yaw rate for the controller. Then the active steering controller of the tractor and trailer based on LQR is designed to follow the desired yaw rate and minimize their side-slip angle of the center of gravity (CG) at the same time. Finally, simulation tests at both low speed and high speed are conducted based on the TruckSim-Simulink program. The results show significant effects on the active steering controller on improving maneuverability at low speed and lateral stability at high speed for the articulated vehicle. The control strategy is applicable for steering not only along gentle curves but also along sharp curves.     

Nested PID steering control for lane keeping in autonomous vehicles

In this paper a nested PID steering control in vision based autonomous vehicles is designed and experimentally tested to perform path following in the case of roads with an uncertain curvature. The control input is the steering wheel angle: it is designed on the basis of the yaw rate, measured by a gyroscope, and the lateral offset, measured by the vision system as the distance between the road centerline and a virtual point at a fixed distance from the vehicle. No lateral acceleration and no lateral speed measurements are required. A PI active front steering control based on the yaw rate tracking error is used to improve the vehicle steering dynamics. The yaw rate reference is computed by an external control loop which is designed using a PID control with a double integral action based on the lateral offset to reject the disturbances on the curvature which increase linearly with respect to time. The proposed control scheme leads to a nested architecture with two independent control loops that allows us to design standard PID controls in a multivariable context (two outputs, one input). The robustness of the controlled system is theoretically investigated with respect to speed variations and uncertain vehicle physical parameters. Several simulations are carried out on a standard big sedan CarSim vehicle model to explore the robustness with respect to unmodelled effects. The simulations show reduced lateral offset and new stable μ-split braking maneuvres in comparison with the model predictive steering controller implemented by CarSim. Finally the proposed control law is successfully tested by experiments using a Peugeot 307 prototype vehicle on the test track in Satory, 20 km west of Paris.     

基于模糊控制策略的车辆主动悬架研究

建立了车辆整车7自由度模型的主动悬架控制的系统状态方程模型,设计了两种模糊控制策略,方法一针对整车模型,采用一种控制方法,方法二针对整车模型的运动方式,设计不同的模糊控制器,垂直振动模糊控制器,俯仰振动模糊控制器,侧倾振动模糊控制器和逻辑控制器,仿真结果表明,所设计的模糊控制器对提高车辆的舒适性与操纵稳定性有较好的效果.     

A Novel LQG Controller of Active Suspension System for Vehicle Roll Safety

To improve vehicle roll safety during steering operation at high running speed, a new design approach for Linear Quadratic Gaussian (LQG) controller of active suspension system is proposed. Key steps of the new approach are as follows: 1) The front axle steered angle is written into a differential equation in accord with the minimum phase system and combines with the original system into the augmented system equation; 2) positive infinitesimals respectively including controls are added to the index; Thirdly, weights of the evaluating indicators of the LQG controller are determined by using analytic hierarchy process (AHP) and normalization methods based on vehicle motion statistics under the double-lane change maneuver as the typical steering maneuver. Performance comparisons are implemented between the active suspension system and the passive one under the double-lane change, slalom and fish-hook maneuvers. Results verify that the active suspension system with the proposed controller can achieve better vehicle roll safety and has a good adaptability under different steering maneuvers.     

一种基于跟踪微分器的智能车辆加速度闭环控制方法

为了满足智能车辆进行L3及以上级别智能驾驶的需求,文章开发了一种基于跟踪微分器的加速度闭环控制方法.该方法采用跟踪微分器对加速度进行辨识,并对加速度进行闭环控制.其上层控制器根据车辆的当前速度、目标速度以及加速或者减速的距离计算一个加速度指令,并通过CAN网络将该指令发送到加速度闭环控制器中,从而实现对智能车辆进行加速...     

Robust adaptive backstepping sliding mode control for motion mode decoupling of two‐axle vehicles with active kinetic dynamic suspension systems

A mode decoupling control strategy is proposed for the active Kinetic Dynamic Suspension Systems (KDSS) with electrohydrostatic actuator (EHA) to improve the roll and warp mode performances. A matrix transfer method is employed to derive the modes of body and wheel station motions for full vehicle with active KDSS. The additional mode stiffness produced by the active KDSS is obtained and quantitatively described with the typical physical parameters. A new hierarchical feedback control strategy is proposed for the active KDSS to improve the roll and warp motion performances and simultaneously accounting for nonlinear dynamics of the actuators with hydraulic uncertainties. H∞ static output‐feedback control is employed to obtain the desirable mode forces, and a new projection‐based adaptive backstepping sliding mode tracking controller is designed for EHA to deal with address the nonlinearity and parameters uncertainty. This controller is used to realize the desirable pressure difference of EHA required from the target mode forces. Numerical simulations are presented to compare the roll and warp performances between the active KDSS, conventional spring‐damper suspension, and suspension with antiroll bar under typical excitation conditions. The evaluation indices are normalized and compared with radar chart. The obtained results illustrate that the proposed active KDSS with proposed controller does not produce additional warp motion for vehicle body, and has achieved more reasonable tire force distribution among wheel stations, the roll stability, road holding, and significantly improved ride comfort simultaneously.     

Integrated vehicle control through the coordination of longitudinal/lateral and vertical dynamics controllers: Flatness and LPV/‐based design

This paper deals with global chassis control of automotive vehicles. It focuses on the coordination of suspension and steering/braking vehicle controllers based on the interaction between the vertical and lateral behaviors of the vehicle. It is shown that the lateral acceleration and resulting roll motion of the car generate load transfers that considerably affect vehicle stability. A control law is designed in hierarchical way to improve the overall dynamics of the vehicle and cope with coupled driving maneuvers like obstacle avoidance using steering control and stop‐and‐go control using braking or driving wheel torque. This global control strategy includes two types of controllers. The first one is the longitudinal/lateral nonlinear flatness controller. Based on an appropriate choice of flat outputs, the flatness proof of a 3 DOF two‐wheel nonlinear vehicle model is established. Then, the combined longitudinal and lateral vehicle control is designed using algebraic estimation techniques to provide an accurate estimation of the derivatives and filtering of the reference flat outputs. The second part of the proposed strategy consists of a linear parameter‐varying/ suspension controller. This controller uses lateral acceleration as a varying parameter to account for load transfers that directly affect the suspension system. The coordination between the vehicle vertical and lateral dynamics is highlighted in this study, and the linear parameter‐varying/ framework ensures a specific collaborative coordination between the suspension and the steering/braking controllers, to achieve the desired performance. Simulations on a complex full vehicle model have been validated using experimental data obtained on‐board a real Renault Mégane Coupé. Copyright © 2017 John Wiley & Sons, Ltd.     

Simultaneous braking and steering control method based on nonlinear model predictive control for emergency driving support

Autonomous emergency braking (AEB) has drawn a lot of attention as an active safety system preventing rear-end collision avoidance when the relative speed between vehicles is slow. To increase the operation range of current AEB system, this paper suggests a collision avoidance strategy using steering and braking simultaneously with nonlinear model predictive control (NMPC) method. The NMPC predicts the vehicle’s future trajectory with its open-loop dynamics and calculates the error between the predicted and the desired paths. Then NMPC calculates the control inputs such as the wheel steering angle and vehicle acceleration by optimizing the cost function over future receding horizon with predetermined constraints. In this paper, constraints on the wheel steering angle is proposed in consideration of vehicle’s predicted lateral acceleration, which should be smaller than the threshold in order to maintain lateral vehicle’s stability. To verify the performance of the proposed strategy, two simulation scenarios were tested in MATLAB and CarSim simulation environments.