Asymptotic sideslip angle and yaw rate decoupling control in four-wheel steering vehicles

This paper shows that, for a four-wheel steering vehicle, a proportional-integral (PI) active front steering control and a PI active rear steering control from the yaw rate error together with an additive feedforward reference signal for the vehicle sideslip angle can asymptotically decouple the lateral velocity and the yaw rate dynamics; that is the control can set arbitrary steady state values for lateral speed and yaw rate at any longitudinal speed. Moreover, the PI controls can suppress oscillatory behaviours by assigning real stable eigenvalues to a widely used linearised model of the vehicle steering dynamics for any value of longitudinal speed in understeering vehicles. In particular, the four PI control parameters are explicitly expressed in terms of the three real eigenvalues to be assigned. No lateral acceleration and no lateral speed measurements are required. The controlled system maintains the well-known advantages of both front and rear active steering controls: higher controllability, enlarged bandwidth for the yaw rate dynamics, suppressed resonances, new stable cornering manoeuvres and improved manoeuvrability. In particular, zero lateral speed may be asymptotically achieved while controlling the yaw rate: in this case comfort is improved since the phase lag between lateral acceleration and yaw rate is reduced. Also zero yaw rate can be asymptotically achieved: in this case additional stable manoeuvres are obtained in obstacle avoidance. Several simulations, including step references and moose tests, are carried out on a standard small SUV CarSim model to explore the robustness with respect to unmodelled effects such as combined lateral and longitudinal tyre forces, pitch, roll and driver dynamics. The simulations confirm the decoupling between the lateral velocity and the yaw rate and show the advantages obtained by the proposed control: reduced lateral speed or reduced yaw rate, suppressed oscillations and new stable manoeuvres.     

基于微分几何的四轮独立驱动车辆运动解耦控制研究

针对车辆在纵向运动和横摆运动时的强耦合关系给车辆动力学控制带来的困难，以四轮独立电驱动车辆作为研究对象，基于微分几何理论设计了车辆系统运动解耦控制方法，将非线性强耦合的四轮驱动车辆动力学系统解耦为纵向和横向两个相对独立运动控制子系统，并设计了鲁棒控制器，以提高抵抗车辆行驶时不确定外力如侧风的干扰能力。基于 Trucksim 软件建立四轮驱动车辆模型，并针对车辆解耦控制策略和抗干扰策略进行了仿真测试。结果表明，相比于无解耦控制的车辆，采用微分几何解耦控制的四轮独立驱动车辆纵向速度偏差降低了 82.1%，横摆角速度偏差降低了80.7%，且微风干扰下的抗干扰能力明显改善，车辆稳定性显著提升。为验证该运动解耦控制策略在实时系统中的控制效果，还进行了硬件在环试验，结果表明，硬件在环试验的结果与仿真结果一致。     

A Fuzzy Logic Direct Yaw-Moment Control System for All-Wheel-Drive Electric Vehicles

Summary In-wheel-motors are revolutionary new electric drive systems that can be housed in vehicle wheel assemblies. Such E-wheels permit packaging flexibility by eliminating the central drive motor and the associated transmission and driveline components, including the transmission, the differential, the universal joints and the drive shaft. Apart from many advantages of such a system, unequalled independent wheel control allows vehicle dynamic improvement to assist the driver in enhancing cornering and straight-line stability on slippery roads and in adverse ground conditions. In this paper a Fuzzy logic driver-assist stability system for all-wheel-drive electric vehicles based on a yaw reference DYC is introduced. The system assists the driver with path correction, thus enhancing cornering and straight-line stability and providing enhanced safety. A feed-forward neural network is employed to generate the required yaw rate reference. The neural net maps the vehicle speed and the steering angle to give the yaw rate reference. The vehicle true speed is estimated using a multi-sensor data fusion method. Data from wheel sensors and an embedded accelerometer are fed into an estimator, where a Fuzzy logic system decides which input is more reliable. The efficiency of the proposed system is approved by conducting a computer simulation. The proposed control system is an effective and easy to implement method to enhance the stability of all-wheel-drive electric vehicles.     

A Fuzzy Logic Direct Yaw-Moment Control System for All-Wheel-Drive Electric Vehicles

Summary In-wheel-motors are revolutionary new electric drive systems that can be housed in vehicle wheel assemblies. Such E-wheels permit packaging flexibility by eliminating the central drive motor and the associated transmission and driveline components, including the transmission, the differential, the universal joints and the drive shaft. Apart from many advantages of such a system, unequalled independent wheel control allows vehicle dynamic improvement to assist the driver in enhancing cornering and straight-line stability on slippery roads and in adverse ground conditions. In this paper a Fuzzy logic driver-assist stability system for all-wheel-drive electric vehicles based on a yaw reference DYC is introduced. The system assists the driver with path correction, thus enhancing cornering and straight-line stability and providing enhanced safety. A feed-forward neural network is employed to generate the required yaw rate reference. The neural net maps the vehicle speed and the steering angle to give the yaw rate reference. The vehicle true speed is estimated using a multi-sensor data fusion method. Data from wheel sensors and an embedded accelerometer are fed into an estimator, where a Fuzzy logic system decides which input is more reliable. The efficiency of the proposed system is approved by conducting a computer simulation. The proposed control system is an effective and easy to implement method to enhance the stability of all-wheel-drive electric vehicles.     

Decoupling control in velocity-varying four-wheel steering vehicles with H∞ performance by longitudinal velocity and yaw rate feedback

In this paper, decoupling control with H_∞ performance for four-wheel steering (4WS) vehicles under varying longitudinal velocity is studied. A novel control scheme for a nonlinear model of three states, respectively, the longitudinal and lateral velocities, and yaw rate, is proposed to address this issue. The scheme is composed of two varying-parameter controllers designing problems for both longitudinal and lateral systems with coupling performance. Varying parameters of both these controllers depend only on longitudinal velocity. Controlled by these controllers, the longitudinal system is decoupled with lateral velocity and yaw rate, and the lateral system is input–output decoupling with H_∞ performance. In addition, feedback signals are the longitudinal velocity and yaw rate, hence observations or measurements of lateral velocity are not necessary. Simulations show that vehicles controlled by our scheme are input–output diagonal decoupling and execute very well while longitudinal velocity varies in a large range, coupling appears between longitudinal and lateral systems, and external disturbances do exist. In summary, this control scheme can improve handling characteristics, safety and comfort proved from theory to practice in this paper.     

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.     

On the handling performance of a vehicle with different front-to-rear wheel torque distributions

ABSTRACT

The handling characteristic is a classical topic of vehicle dynamics. Usually, vehicle handling is studied by analyzing the understeer coefficient in quasi-steady-state maneuvers. In this paper, experimental tests are performed on an electric vehicle with four independent motors, which is able to reproduce front-wheel-drive, rear-wheel-drive and all-wheel-drive (FWD, RWD and AWD, respectively) architectures. The handling characteristics of each architecture are inferred through classical and new concepts. The study presents a procedure to compute the longitudinal and lateral tire forces, which is based on a first estimate and a subsequent correction of the tire forces that guarantee the equilibrium. A yaw moment analysis is performed to identify the contributions of the longitudinal and lateral forces. The results show a good agreement between the classical and new formulations of the understeer coefficient, and allow to infer a relationship between the understeer coefficient and the yaw moment analysis. The handling characteristics vary with speed and front-to-rear wheel torque distribution. An apparently surprising result arises at low speed: the RWD architecture is the most understeering configuration. This is discussed by analyzing the yaw moment caused by the longitudinal forces of the front tires, which is significant for high values of lateral acceleration and steering angle.     

Coupled lateral-longitudinal vehicle dynamics and control design with three-dimensional state portraits

The dynamics of vehicles with pneumatic tyres are well-known to be non-holonomic, nonlinear, and subject to state bounds in order to remain on defined roadways. As such, it can be challenging to apply many of the tools typically used to analyse nonlinear dynamics and synthesise control strategies. Furthermore, the use of traditional stability analyses is often insufficient for vehicle control design since adherence to the roadway geometry implies a constrained space that dictates stricter conditions on the states than provable stability. A two-state phase portrait approach has been used to analyse vehicle dynamics and provides an illustrative view of the state trajectories at constant speed. This paper extends the phase portrait to three states to represent the nonlinear vehicle dynamics with steering and longitudinal tyre force inputs and consideration of the longitudinal vehicle dynamics. The concept of a fixed point in the phase plane is extended to a stable curve and example controllers are examined and synthesised using the three-dimensional vector space.     

智能汽车轨迹跟踪与横摆稳定性协同控制

为了提高四轮独立驱动智能电动汽车在变曲率弯道下的轨迹跟踪精度和横摆稳定性,提出了一种模型预测控制与直接横摆力矩控制协同的综合控制方法。建立了横纵向耦合的车辆动力学模型,采用2阶龙格库塔离散法保证了离散模型的精度,并基于简化的2自由度动力学模型推导了车辆横摆稳定性约束,设计了非线性模型预测控制器;利用直接横摆力矩控制能够改变车辆横摆角速度和航向角的特点,考虑模型预测控制器的预测状态、控制量以及跟踪误差,设计了协同控制规则。仿真结果表明,协同控制方法解决了考虑横摆稳定性约束的模型预测控制器中存在的稳定性约束与控制精度相矛盾的问题,并补偿了模型预测控制器没有可行解时对横摆稳定性的约束,同时提高了智能汽车的轨迹跟踪精度和横摆稳定性。     

基于NMPC的智能汽车纵横向综合轨迹跟踪控制

本文中针对大曲率转弯工况下,智能汽车纵横向动力学特性的耦合和动力学约束导致轨迹跟踪精度和稳定性下降的问题,提出一种基于非线性模型预测控制(NMPC)的纵横向综合轨迹跟踪控制方法,通过NMPC和障碍函数法(BM)的有效结合,提高了跟踪精度,改善了行驶稳定性.首先建立四轮驱动-前轮转向智能汽车动力学模型和轨迹跟踪模型,采用...     

Modal Controllers for Active Steering of Railway Vehicles with Solid Axle Wheelsets

This paper presents the development of a modal control strategy for the active steering of solid axle railway vehicles and reveals benefits of actively stabilising the wheelsets of a railway vehicle. A modal decomposition is applied to a 2-axle railway vehicle to de-couple its body lateral and yaw motions and hence to allow more detailed analysis of the vehicle behaviour and more robust design of active controllers. Independent controllers for the two motions are developed based on the two de-coupled modes. Parameter variations such as creep coefficients and wheelset conicity are taken into account in the design process to guarantee a robust design. The study shows that, compared to a passive vehicle, the vehicles with actively steered wheelsets not only perform much better on a curved track, but also improve the ride quality on straight track. Computer simulations are used in the study to verify the development of the controllers and assess the system performance with the control scheme proposed.     

Yaw rate and side-slip control considering vehicle longitudinal dynamics

Most conventional vehicle stability controllers operate on the basis of many simplifying assumptions, such as a small steering wheel angle, constant longitudinal velocity and a small side-slip angle. This paper presents a new approach for controlling the yaw rate and side-slip of a vehicle without neglecting its longitudinal dynamics and without making simplifying assumptions about its motion. A sliding-mode controller is used to develop a differential braking controller for tracking a desired vehicle yaw rate for a given steering wheel angle, while keeping the vehicle’s side-slip angle as small as possible. The trade-off that exists between yaw rate and side-slip control is described. Conventional and proposed algorithms are presented, and the effectiveness of the proposed controller is investigated using a seven-degree-of-freedom vehicle dynamics model. The simulation results demonstrate that the proposed controller is more effective than the conventional one.     

Effects of Model Complexity on the Performance of Automated Vehicle Steering Controllers: Model Development,Validation and Comparison

SUMMARY

Recent research on autonomous highway vehicles has begun to focus on lateral control strategies. The initial work has focused on vehicle control during low-g maneuvers at constant vehicle speed, typical of lane merging and normal highway driving. In this paper, and its companion paper, to follow, the lateral control of vehicles during high-g emergency maneuvers is addressed. Models of the vehicle dynamics are developed, showing the accuracy of the different models under low and high-g conditions. Specifically, body roll, tire and drive-train dynamics, tire force saturation, and tire side force lag are shown to be important effects to include in models for emergency maneuvers. Current controllers, designed for low-g maneuvers only, neglect these effects. The follow on paper demonstrates the performance of lateral controllers during high-g lateral emergency maneuvers using these vehicle models.     

Effects of Model Complexity on the Performance of Automated Vehicle Steering Controllers: Model Development, Validation and Comparison

Recent research on autonomous highway vehicles has begun to focus on lateral control strategies. The initial work has focused on vehicle control during low-g maneuvers at constant vehicle speed, typical of lane merging and normal highway driving. In this paper, and its companion paper, to follow, the lateral control of vehicles during high-g emergency maneuvers is addressed. Models of the vehicle dynamics are developed, showing the accuracy of the different models under low and high-g conditions. Specifically, body roll, tire and drive-train dynamics, tire force saturation, and tire side force lag are shown to be important effects to include in models for emergency maneuvers. Current controllers, designed for low-g maneuvers only, neglect these effects. The follow on paper demonstrates the performance of lateral controllers during high-g lateral emergency maneuvers using these vehicle models.     

Nonlinear PI front and rear steering control in four wheel steering vehicles

Vehicle steering dynamics show resonances, which depend on the longitudinal speed, unstable equilibrium points and limited stability regions depending on the constant steering wheel angle, longitudinal speed and car parameters.

The main contribution of this paper is to show that a combined decentralized proportional active front steering control and proportional-integral active rear steering control from the yaw rate tracking error can assign the eigenvalues of the linearised single track steering dynamics, without lateral speed measurements, using a standard single track car model with nonlinear tire characteristics and a non-linear first-order reference model for the yaw rate dynamics driven by the driver steering wheel input. By choosing a suitable nonlinear reference model it is shown that the responses to driver step inputs tend to zero (or reduced) lateral speed for any value of longitudinal speed: in this case the resulting controlled vehicle static gain from driver input to yaw rate differs from the uncontrolled one at higher speed. The closed loop system shows the advantages of both active front and rear steering control: higher controllability, enlarged bandwidth for the yaw rate dynamics, suppressed resonances, new stable cornering manoeuvres, enlarged stability regions, reduced lateral speed and improved manoeuvrability; in addition comfort is improved since the phase lag between lateral acceleration and yaw rate is reduced.

For the designed control law a robustness analysis is presented with respect to system failures, driver step inputs and critical car parameters such as mass, moment of inertia and front and rear cornering stiffness coefficients. Several simulations are carried out on a higher order experimentally validated nonlinear dynamical model to confirm the analysis and to explore the robustness with respect to unmodelled dynamics.     

Nonlinear PI front and rear steering control in four wheel steering vehicles

Vehicle steering dynamics show resonances, which depend on the longitudinal speed, unstable equilibrium points and limited stability regions depending on the constant steering wheel angle, longitudinal speed and car parameters.

The main contribution of this paper is to show that a combined decentralized proportional active front steering control and proportional-integral active rear steering control from the yaw rate tracking error can assign the eigenvalues of the linearised single track steering dynamics, without lateral speed measurements, using a standard single track car model with nonlinear tire characteristics and a non-linear first-order reference model for the yaw rate dynamics driven by the driver steering wheel input. By choosing a suitable nonlinear reference model it is shown that the responses to driver step inputs tend to zero (or reduced) lateral speed for any value of longitudinal speed: in this case the resulting controlled vehicle static gain from driver input to yaw rate differs from the uncontrolled one at higher speed. The closed loop system shows the advantages of both active front and rear steering control: higher controllability, enlarged bandwidth for the yaw rate dynamics, suppressed resonances, new stable cornering manoeuvres, enlarged stability regions, reduced lateral speed and improved manoeuvrability; in addition comfort is improved since the phase lag between lateral acceleration and yaw rate is reduced.

For the designed control law a robustness analysis is presented with respect to system failures, driver step inputs and critical car parameters such as mass, moment of inertia and front and rear cornering stiffness coefficients. Several simulations are carried out on a higher order experimentally validated nonlinear dynamical model to confirm the analysis and to explore the robustness with respect to unmodelled dynamics.     

Modal Controllers for Active Steering of Railway Vehicles with Solid Axle Wheelsets

This paper presents the development of a modal control strategy for the active steering of solid axle railway vehicles and reveals benefits of actively stabilising the wheelsets of a railway vehicle. A modal decomposition is applied to a 2-axle railway vehicle to de-couple its body lateral and yaw motions and hence to allow more detailed analysis of the vehicle behaviour and more robust design of active controllers. Independent controllers for the two motions are developed based on the two de-coupled modes. Parameter variations such as creep coefficients and wheelset conicity are taken into account in the design process to guarantee a robust design. The study shows that, compared to a passive vehicle, the vehicles with actively steered wheelsets not only perform much better on a curved track, but also improve the ride quality on straight track. Computer simulations are used in the study to verify the development of the controllers and assess the system performance with the control scheme proposed.     

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.     

分布式驱动电动汽车动力学集成控制研究进展及趋势

分布式驱动电动汽车具有四轮可独立控制和响应速度快等突出优势，对增强车辆操纵稳定性、安全性和经济性具有重要的意义。但车辆是一个非线性、强耦合的系统，需研究解决各个控制器相互耦合、过驱动系统复杂性和不确定性等核心问题，这依赖于多维 （纵向、横向和垂向） 集成控制模式和容错控制。对现有研究进行分类和总结，从传统单一维度控制到多维集成控制，综述分布式驱动电动汽车的关键技术和发展现状，重点归纳了汽车动力学集成控制的多层结构及其应用，特别是集成了纵向-横向-垂向动力学的综合控制。最后对分布式驱动电动汽车动力学控制系统所面临的挑战提出了一些建议。     

Vehicle dynamic control of a passenger car applying flexible body model

Modern software tools have enhanced modelling, analysis and simulation capabilities pertaining to control of dynamic systems. In this regard, in this paper a full vehicle model with flexible body is exposed by using MSC. ADAMS and MSC. NASTRAN. Indeed, one of the most significant vehicle dynamic controls is directional stability control. In this case, the vehicle dynamic control system (VDC) is used to improving the vehicle lateral and yaw motions in critical manoeuvres. In this paper, for design the VDC system, an optimal control strategy has been used for tracking the intended path with optimal energy. For better performance of VDC system, an anti-lock brake system (ABS) is designed as a lower layer of the control system for maintaining the tyre longitudinal slip in proper value. The performances of the controller on rigid and flexible models are illustrated, and the results show the differences between the control efforts for these models, which are related to the differences of dynamic behaviours of rigid and flexible vehicle dynamic models.