A lateral driver model for vehicle–driver closed-loop simulation at the limits of handling

This paper presents a lateral driver model for vehicle–driver closed-loop simulation at the limits of handling. An appropriate driver model can be used to evaluate the performance of vehicle chassis control systems via computer simulations before vehicle tests which incurs expenses especially at the limits of handling. The driver model consists of two parts. The first part is an upper-level controller employing force-based approach to reduce the number of unknown vehicle parameters. The feedforward part of the upper controller has been designed by using the centre of percussion. The feedback part aims to minimise ‘tangential error’, defined as the sum of body slip angle and yaw error, to match vehicle direction and road heading angle. The part is designed to regenerate an appropriate skid motion similar to that of a professional driver at the limits. The second part is a lower-level controller which converts the desired front lateral force to steering wheel angle. The lower-level controller also consists of feedforward and feedback parts. A two-degree-of-freedom bicycle model-based feedforward part provides nominal steering wheel angle, and the feedback part aims to eliminate unmodelled error. The performance of the lateral driver model has been investigated via computer simulations. It has been shown that the steering behaviours of the proposed driver model are quite close to those of a professional driver at the limits. Compared with the previously developed lateral driver models, the proposed lateral driver model shows good tracking performance at the limits of handling.     

Vehicle Handling Improvement by Active Steering

Summary This paper first analyses some stability aspects of vehicle lateral motion, then a coprime factors and linear fractional transformations (LFT) based feedforward and feedback H 8 control for vehicle handling improvement is presented. The control synthesis procedure uses a linear vehicle model which includes the yaw motion and disturbance input with speed and road adhesion variations. The synthesis procedure allows the separate processing of the driver reference signal and robust stabilization problem or disturbance rejection. The control action is applied as an additional steering angle, by combination of the driver input and feedback of the yaw rate. The synthesized controller is tested for different speeds and road conditions on a nonlinear model in both disturbance rejection and driver imposed yaw reference tracking maneuvers.     

Vehicle Handling Improvement by Active Steering

Summary This paper first analyses some stability aspects of vehicle lateral motion, then a coprime factors and linear fractional transformations (LFT) based feedforward and feedback H 8 control for vehicle handling improvement is presented. The control synthesis procedure uses a linear vehicle model which includes the yaw motion and disturbance input with speed and road adhesion variations. The synthesis procedure allows the separate processing of the driver reference signal and robust stabilization problem or disturbance rejection. The control action is applied as an additional steering angle, by combination of the driver input and feedback of the yaw rate. The synthesized controller is tested for different speeds and road conditions on a nonlinear model in both disturbance rejection and driver imposed yaw reference tracking maneuvers.     

Stability control of 4WS vehicles using robust IMC techniques

A robust nonparametric approach to vehicle stability control by means of a four-wheel steer by wire system is introduced. Both yaw rate and sideslip angle feedbacks are used in order to effectively take into account safety as well as handling performances. Reference courses for yaw rate and sideslip angle are computed on the basis of the vehicle speed and the handwheel angle imposed by the driver. An output multiplicative model set is used to describe the uncertainty arising from a wide range of vehicle operating situations. The effects of saturation of the control variables (i.e. front and rear steering angles) are taken into account by adopting enhanced internal model control methodologies in the design of the feedback controller. Actuator dynamics are considered in the controller design. Improvements on understeer characteristics, stability in demanding conditions such as turning on low friction surfaces, damping properties in impulsive manoeuvres, and improved handling in closed loop (i.e. with driver feedback) manoeuvres are shown through extensive simulation results performed on an accurate 14 degrees of freedom nonlinear model, which proved to give good modelling results as compared with collected experimental data.     

基于变权重系数的分布式驱动无人车轨迹跟踪

为了提高分布式无人车轨迹跟踪的精度，提出了基于自主与差动协调转向控制的轨迹跟踪方法。首先，在车辆三自由度模型基础上，基于模型预测控制（MPC）实时计算前轮转角以控制车辆进行自主转向轨迹跟踪。在此过程中，为了提高自主转向下车辆的轨迹跟踪精度与行驶的稳定性，考虑多种因素，利用经验公式及神经网络控制对MPC的预瞄步数和预瞄步长进行多参数调整，实现预瞄时间的自适应控制。其次，在恒转矩需求的情况下，以轨迹偏差为PID控制器的输入及左右轮毂电机转矩为输出进行差动转向控制，实现了差动转向下的轨迹跟踪控制。然后，通过设置权重系数的方法将自主与差动转向相结合。考虑到车辆横纵向动力学因素，采用模糊控制及经验公式对权重系数进行了调整，从而在提高车辆转向灵活性与轨迹跟踪效果的同时保证车辆行驶的稳定性。CarSim与Simulink联合仿真以及实车试验结果表明：与自主转向轨迹跟踪相比，采用变权重系数的协调控制可以在不同的工况下提高车辆的转向灵活性与轨迹跟踪的精度，轨迹跟踪偏差的均方根值改善率达到了11%。所提出的协调转向控制方法可为分布式驱动车辆转向灵活性的提高及轨迹跟踪精度的改善提供一种新的思路。     

面向车道变换的路径规划及模型预测轨迹跟踪

为解决智能车辆在车道变换过程中的路径规划和路径跟踪问题,首先,利用梯形加速度法设计了车道变换虚拟理想轨迹,该路径规划方法的适应性取决于车道变换时间、横向加速度及变化率等关键变量的约束条件,因而对各关键变量之间的数学关系进行了定量计算,并绘制了不同工况下的车道变换虚拟理想轨迹,用于分析各关键变量对路径规划的影响;其次,建立了线性离散的车辆动力学预测模型,综合分析了车辆模型的控制输入、状态变量以及道路结构参数等约束条件,构建了多约束模型预测控制（MMPC）系统用于车道变换路径跟踪,并基于Hildreth二次规划算法对其目标函数进行了求解,获得前轮转向角控制量,从而保证智能车辆在车道变换过程中的路径跟踪性能及操纵稳定性能;最后,利用MATLAB和Carsim软件对提出的多约束模型预测控制系统进行联合仿真,并构建单约束模型预测控制（SMPC）系统与其进行性能比较,分别对车道变换时间为3 s和6 s时的车道变换性能进行比较分析。结果表明：当车道变换时间为6 s时,2种控制系统都能较好地实现车道变换功能;当车道变换时间为3 s时,与SMPC控制系统相比较,MMPC控制系统能够在有效跟踪期望行驶路径的同时改善车辆的操纵稳定性,从而提高车辆在路径跟踪过程中的主动安全性能。     

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.     

Development of an active front steering (AFS) system with QFT control

This paper investigates an active front steering control strategy based on quantitative feedback theory (QFT). By incorporating feedback from a yaw rate sensor into the active steering system, the control system improves the dynamic response of the vehicle. The steering response of a vehicle generally depends upon uncertain quantities like mass, velocity, and road conditions. Thus, QFT is used to design a controller with robust performance. A multi-degree-of-freedom nonlinear model is co-simulated here by MATLAB Simulink and ADAMS/CAR. The performance of the control system is evaluated under various emergency maneuvers and road conditions. The result shows that the designed robust control system has good control performance and can efficiently improve handing qualities and stability characteristics.     

智能汽车路径跟踪精度及操纵稳定性耦合机理分析

针对现有智能汽车路径跟踪算法研究中存在的智能汽车路径跟踪精度与操纵稳定性相互耦合和相互制约问题,在车辆二自由度模型基础上,设计了基于传统预瞄误差模型的PID控制方法,研究了智能汽车在蛇形道路工况、定曲率变车速工况和定车速变曲率工况下,车速及道路曲率对智能汽车路径跟踪精度和操纵稳定性的影响。仿真结果表明,随着车速和道路曲率的增加,智能汽车路径跟踪精度以及操纵稳定性降低;智能汽车的路径跟踪精度提高,操纵稳定性变差。     

Desired yaw rate and steering control method during cornering for a six-wheeled vehicle

This paper proposes a steering control method based on optimal control theory to improve the maneuverability of a six-wheeled vehicle during cornering. The six-wheeled vehicle is believed to have better performance than a four-wheeled vehicle in terms of its capability for crossing obstacles, off-road maneuvering and fail-safe handling when one or two of the tires are punctured. Although many methods to improve the four-wheeled vehicle’s lateral stability have been studied and developed, there have only been a few studies on the six-wheeled vehicle’s lateral stability. Some studies of the six-wheeled vehicle have been reported recently, but they are related to the desired yaw rate of a four-wheeled vehicle to control the six-wheeled vehicle’s maneuvering during corning. In this paper, the sideslip angle and yaw rate are controlled to improve the maneuverability during cornering by independent control of the steering angles of the six wheels. The desired yaw rate that is suitable for a six-wheeled vehicle is proposed as a control target. In addition, a scaled-down vehicle with six drive motors and six steering motors that can be controlled independently is designed. The performance of the proposed control methods is verified using a full model vehicle simulation and scaled-down vehicle experiment.     

Robust hierarchical controller with conditional integrator based on small gain theorem for reference trajectory tracking of autonomous vehicles

ABSTRACT

A robust trajectory tracking controller is designed for autonomous vehicles based on a hierarchical architecture to make the autonomous vehicle track a given reference trajectory. The controller consists of two sub controllers: kinematic controller and dynamic controller. Based on the kinematics of tracking reference trajectory, a desired yaw rate is calculated by kinematic controller to make the lateral deviation global asymptotic stable. Then, steering wheel angle is calculated by a vehicle dynamic controller to make the vehicle yaw rate converge to the desired value and make the vehicle dynamic stable. Conditional integration method is used in the sub controllers. This method guarantees global asymptotic stability of tracking reference values and considers the uncertainty of parameters and constraints of desired yaw rate and actuators. Then based on small-gain theorem, the condition of the finite-gain L stability is given to the hierarchical controller to ensure the interconnected sub systems stable and prevent the amplification of system disturbance. Finally, the effectiveness and robustness of the controller are validated by real vehicle experiments.     

Disturbance Observer-Based Sideslip Angle Control for Improving Cornering Characteristics of In-Wheel Motor Electric Vehicles

In this paper, a robust sideslip angle controller based on the direct yaw moment control (DYC) is proposed for in-wheel motor electric vehicles. Many studies have demonstrated that the DYC is one of the effective methods to improve vehicle maneuverability and stability. Previous approaches to achieve the DYC used differential braking and active steering system. Not only that, the conventional control systems were commonly dependent on the feedback of the yaw rate. In contrast to the traditional control schemes, however, this paper proposes a novel approach based on sideslip angle feedback without controlling the yaw rate. This is mainly because if the vehicle sideslip angle is controlled properly, the intended sideslip angle helps the vehicle to pass through the corner even at high speed. On the other hand, the vehicle may become unstable because of the too large sideslip caused by unexpected yaw disturbances and model uncertainties of time-varying parameters. From this aspect, disturbance observer (DOB) is employed to assure robust performance of the controller. The proposed controller was realized in CarSim model described actual electric vehicle and verified through computer simulations.     

Comparing rear wheel steering and rear active differential approaches to vehicle yaw control

A comparison between two different approaches to vehicle stability control is carried out, employing a robust non-parametric technique in the controller design. In particular, an enhanced internal model control strategy, together with a feedforward action and a suitably generated reference map, is employed for the control of a vehicle equipped either with a rear wheel steering (RWS) system or with a rear active differential (RAD) device. The uncertainty arising from the wide range of operating conditions is described by an additive model set employed in the controller design. Extensive steady state and transient tests simulated with an accurate 14 degrees of freedom nonlinear model of the considered vehicle show that both systems are able to improve handling and safety in normal driving conditions. RAD devices can make the vehicle reach higher lateral acceleration values but they achieve only slight stability improvements against oversteer. On the other hand, 4WS systems can greatly improve both vehicle safety and manoeuvrability in all driving situations, making this device an interesting and powerful stability system.     

Integrated Control of Active Rear Wheel Steering and Direct Yaw Moment Control

An integrated control system of active rear wheel steering (4WS) and direct yaw moment control (DYC) is presented in this paper. Because of the tire nonlinearity that is mainly due to the saturation of cornering forces, vehicle handling performance is improved but limited to a certain extent only by steering control. Direct yaw moment control using braking and/or driving forces is effective not only in linear but also nonlinear ranges of tire friction circle. The proposed control system is a model matching controller which makes the vehicle follow the desired dynamic model by the state feedback of both yaw rate and side slip angle. Various computer simulations are carried out and show that vehicle handling performance is much improved by the integrated control system.     

Integrated Control of Active Rear Wheel Steering and Direct Yaw Moment Control

SUMMARY

An integrated control system of active rear wheel steering (4WS) and direct yaw moment control (DYC) is presented in this paper. Because of the tire nonlinearity that is mainly due to the saturation of cornering forces, vehicle handling performance is improved but limited to a certain extent only by steering control. Direct yaw moment control using braking and/or driving forces is effective not only in linear but also nonlinear ranges of tire friction circle. The proposed control system is a model matching controller which makes the vehicle follow the desired dynamic model by the state feedback of both yaw rate and side slip angle. Various computer simulations are carried out and show that vehicle handling performance is much improved by the integrated control system.     

Using µ Feedforward for Vehicle Stability Enhancement

A differential braking control strategy using yaw rate feedback, coupled with µ feedforward is introduced for a vehicle cornering on different µ roads. A nonlinear 4-wheel car model is developed. A desired yaw rate is calculated from the reference model based on the driver steering input. It is shown that knowledge of µ offers significant improvement of the vehicle desired trajectory over that of a yaw rate controller alone. Uncertainties and time delay in estimating µ are shown to still yield a system that is superior to using no µ information at all.     

识别驾驶人意图的车道偏离防避有界控制

为了防止车辆偏离车道导致交通事故的发生和避免车道偏离防避系统（Lane Departure Avoidance Systems,LDAS）对驾驶人行为不必要的干预,提出基于中心区操纵特性阈值法和基于D-S（Dempster-Shafer）证据理论的车辆偏离车道驾驶人意图识别准则,并运用CarSim/Simulink联合仿真对比2种识别准则的有效性。建立转向盘角速度为输入的车路模型,设计LDAS滑模转向控制器,基于预瞄点的侧向偏移量和横摆角速度设计LDAS的期望横摆角速度观测器,并与基于道路曲率和预瞄点侧向偏移量的期望横摆角速度的LDAS进行性能对比。运用相平面法确定保证LDAS车辆稳定性的前轮转向角最大值,并基于CarSim/LabVIEW RT硬件在环试验平台验证基于BP神经网络训练获得D-S证据理论的初始概率赋值的驾驶人意图决策算法的有效性。结果表明：所提出的识别准则能够及时识别车辆偏离车道时的驾驶人意图,为LDAS控制器介入赢得了宝贵的时间,所设计的期望横摆角速度观测器具有很好的稳定性,所提出的方法能够有效避免车辆偏离车道。     

基于QFT的四轮转向控制系统设计

本文提出一种基于定量反馈理论的主动控制四轮转向策略，以汽车转向时的横摆角速度和车体侧偏角为被控制量，将汽车的速度、质量、轮胎等效侧偏刚度等参数视为有界的不确定参数，应用定量反馈理论（QFT）设计反馈控制系统。为了验证设计的有效性，采用具有非线性轮胎特性的汽车模型对控制系统作了多种工况下的仿真。仿真结果证明所设计的解耦控制系统对汽车参数的不确定性具有鲁棒性，同时具有较好的控制特性，能够有效提高汽车的主动安全性和操纵稳定性。     

Emergency steering control of autonomous vehicle for collision avoidance and stabilisation

ABSTRACT

Collision avoidance and stabilisation are two of the most crucial concerns when an autonomous vehicle finds itself in emergency situations, which usually occur in a short time horizon and require large actuator inputs, together with highly nonlinear tyre cornering response. In order to avoid collision while stabilising autonomous vehicle under dynamic driving situations at handling limits, this paper proposes a novel emergency steering control strategy based on hierarchical control architecture consisting of decision-making layer and motion control layer. In decision-making layer, a dynamic threat assessment model continuously evaluates the risk associated with collision and destabilisation, and a path planner based on kinematics and dynamics of vehicle system determines a collision-free path when it suddenly encounters emergency scenarios. In motion control layer, a lateral motion controller considering nonlinearity of tyre cornering response and unknown external disturbance is designed using tyre lateral force estimation-based backstepping sliding-mode control to track a collision-free path, and to ensure the robustness and stability of the closed-loop system. Both simulation and experiment results show that the proposed control scheme can effectively perform an emergency collision avoidance manoeuvre while maintaining the stability of autonomous vehicle in different running conditions.     

Lateral handling improvement with dynamic curvature control for an independent rear wheel drive EV

The integrated longitudinal and lateral dynamic motion control is important for four wheel independent drive (4WID) electric vehicles. Under critical driving conditions, direct yaw moment control (DYC) has been proved as effective for vehicle handling stability and maneuverability by implementing optimized torque distribution of each wheel, especially with independent wheel drive electric vehicles. The intended vehicle path upon driver steering input is heavily depending on the instantaneous vehicle speed, body side slip and yaw rate of a vehicle, which can directly affect the steering effort of driver. In this paper, we propose a dynamic curvature controller (DCC) by applying a the dynamic curvature of the path, derived from vehicle dynamic state variables; yaw rate, side slip angle, and speed of a vehicle. The proposed controller, combined with DYC and wheel longitudinal slip control, is to utilize the dynamic curvature as a target control parameter for a feedback, avoiding estimating the vehicle side-slip angle. The effectiveness of the proposed controller, in view of stability and improved handling, has been validated with numerical simulations and a series of experiments during cornering engaging a disturbance torque driven by two rear independent in-wheel motors of a 4WD micro electric vehicle.