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.     

Drive control system design for stability and maneuverability of a 6WD/6WS vehicle

This paper describes a drive controller designed to improve the lateral vehicle stability and maneuverability of a 6-wheel drive / 6-wheel steering (6WD/6WS) vehicle. The drive controller consists of upper and lower level controllers. The upper level controller is based on sliding control theory and determines both front and middle steering angle, additional net yaw moment, and longitudinal net force according to the reference velocity and steering angle of a manual drive, remotely controlled, autonomous controller. The lower level controller takes the desired longitudinal net force, yaw moment, and tire force information as inputs and determines the additional front steering angle and distributed longitudinal tire force on each wheel. This controller is based on optimal distribution control and takes into consideration the friction circle related to the vertical tire force and friction coefficient acting on the road and tire. Distributed longitudinal/lateral tire forces are determined as proportion to the size of the friction circle according to changes in driving conditions. The response of the 6WD/6WS vehicle implemented with this drive controller has been evaluated via computer simulations conducted using the Matlab/Simulink dynamic model. Computer simulations of an open loop under turning conditions and a closed-loop driver model subjected to double lane change have been conducted to demonstrate the improved performance of the proposed drive controller over that of a conventional DYC.     

轮胎／路面附着系数估算方法

为提高汽车主动安全系统自适应控制性能,需要对轮胎／路面附着系数进行精确的识别或估算。鉴于附着系数估计的复杂性,文章综述了目前路面附着系数估算中的汽车动力学建模和轮胎／路面摩擦模型建模,重点讨论了轮胎／路面附着系数识别算法中传感器的直接检测估计法,以及基于车辆动力学、回正力矩和状态观测器等动力学模型的估计算法,并对各估算方法存在的问题与发展趋势等进行了分析。对开发汽车主动安全电控系统和提高汽车产业核心竞争力具有重要意义。     

Adaptive Control of 4WS System by Using Neural Network

An adaptive control system of the model following type is proposed for drive motion control of a four wheel steering (4WS) car with using neural network (NN) which has mastered nonlinear friction force between tire and road surface. A model of one rigid body is adopted which represents appropriately two kinds of car motion caused by steering action, namely the lateral displacement and the yawing rotation, and an equation of motion is described in a simplified form to make a system equation for motion control possible. Nonlinear relation between the cornering force of tire and the slip angle is obtained by numerical analysis with the tire model proposed by E. Fiala, taking friction coefficient and car speed as the parameters. The result is used as the teaching signal for NN. Three NN are used in the control system composed of both the feed-forward and the feedback circuits in order to realize adaptive control. Validity and usefulness of the proposed adaptive control system with NN are verified by three kinds of computer simulation.     

Model-Based Road Friction Estimation

The tire/road friction coefficient, μ, has a significant role in vehicle longitudinal and lateral control, and there has been associated efforts to measure or estimate the road surface condition to provide additional information for stability augmentation systems of automobiles. In this paper, a model based road friction estimation algorithm is proposed from easily measured signals such as yaw rate and wheel speed. For the development of the estimator, a low order vehicle model incorporated with simple but effective tire model. Field tests of the estimator using actual vehicle measurements show promising results.     

Adaptive Control of 4WS System by Using Neural Network

SUMMARY

An adaptive control system of the model following type is proposed for drive motion control of a four wheel steering (4WS) car with using neural network (NN) which has mastered nonlinear friction force between tire and road surface. A model of one rigid body is adopted which represents appropriately two kinds of car motion caused by steering action, namely the lateral displacement and the yawing rotation, and an equation of motion is described in a simplified form to make a system equation for motion control possible. Nonlinear relation between the cornering force of tire and the slip angle is obtained by numerical analysis with the tire model proposed by E. Fiala, taking friction coefficient and car speed as the parameters. The result is used as the teaching signal for NN. Three NN are used in the control system composed of both the feed-forward and the feedback circuits in order to realize adaptive control. Validity and usefulness of the proposed adaptive control system with NN are verified by three kinds of computer simulation.     

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.     

Sideslip angle estimation based on input–output linearisation with tire–road friction adaptation

An adaptive sideslip angle observer considering tire–road friction adaptation is proposed in this paper. The single-track vehicle model with nonlinear tire characteristics is adopted. The tire parameters can be easily obtained through road test data without using special test rigs. Afterwards, this model is reconstructed and a high-gain observer (HGO) based on input–output linearisation is derived. The observer stability is analysed. Experimental results have confirmed that the HGO has a better computational efficiency with the same accuracy when compared with the extended Kalman filter and the Luenberger observer. Finally, a road friction adaptive algorithm based on vehicle lateral dynamics is proposed and validated through driving simulator data. As long as the tires work in the nonlinear region, the maximal friction coefficient could be estimated. This algorithm has excellent portability and is also suitable for other observers.     

A vehicle ABS adaptive sliding-mode control algorithm based on the vehicle velocity estimation and tyre/road friction coefficient estimations

A sliding-mode observer is designed to estimate the vehicle velocity with the measured vehicle acceleration, the wheel speeds and the braking torques. Based on the Burckhardt tyre model, the extended Kalman filter is designed to estimate the parameters of the Burckhardt model with the estimated vehicle velocity, the measured wheel speeds and the vehicle acceleration. According to the estimated parameters of the Burckhardt tyre model, the tyre/road friction coefficients and the optimal slip ratios are calculated. A vehicle adaptive sliding-mode control (SMC) algorithm is presented with the estimated vehicle velocity, the tyre/road friction coefficients and the optimal slip ratios. And the adjustment method of the sliding-mode gain factors is discussed. Based on the adaptive SMC algorithm, a vehicle's antilock braking system (ABS) control system model is built with the Simulink Toolbox. Under the single-road condition as well as the different road conditions, the performance of the vehicle ABS system is simulated with the vehicle velocity observer, the tyre/road friction coefficient estimator and the adaptive SMC algorithm. The results indicate that the estimated errors of the vehicle velocity and the tyre/road friction coefficients are acceptable and the vehicle ABS adaptive SMC algorithm is effective. So the proposed adaptive SMC algorithm can be used to control the vehicle ABS without the information of the vehicle velocity and the road conditions.     

基于自适应模型预测的智能汽车横向轨迹跟踪控制

当路面附着情况和车辆行驶状态不断变化时,基于恒定侧偏刚度的模型预测控制(MPC)不能考虑轮胎非线性特性的影响,难以保证车辆轨迹跟踪的适应性。为此,提出一种考虑轮胎侧向力计算误差的自适应模型预测控制(AMPC),以提高智能汽车在不确定工况下的轨迹跟踪性能。分析了路面附着系数和垂向载荷对轮胎侧向力的影响,基于平方根容积卡尔曼滤波(SCKF)算法,设计了利用侧向加速度和横摆角速度作为测量变量的前后轮胎侧向力估计器。利用轮胎侧向力线性计算值与估计值的差值计算得到侧偏刚度修正因子,设计了前后轮胎侧偏刚度的自适应修正准则,进而提出了一种基于时变修正刚度的AMPC控制方法。基于CarSim与MATLAB/Simulink联合仿真和硬件在环测试平台,对AMPC控制的有效性和实时性进行了验证。研究结果表明：在不同的路面附着情况和车辆行驶状态下,AMPC控制都能够降低横向位置偏差和航向角偏差,有效提高车辆的轨迹跟踪精度,其控制效果明显优于基于恒定侧偏刚度的标准MPC控制。尤其在低附着工况下,标准MPC控制会因为线性轮胎力的计算误差过大而导致车辆在轨迹跟踪时严重失稳,而AMPC控制通过估计轮胎力修正侧偏刚度依然能够保证车辆稳定有效的跟踪参考轨迹。所提出的AMPC控制在保证控制精度的同时具有良好的实时性,对智能汽车控制系统的设计与优化具有重要参考价值。     

Sensitivity analysis of side-slip angle observer based on a tire model

We investigated the sensitivity of an observer based on a tire model using simulation in linear and nonlinear regions. In the linear region, we investigated the influence of vehicle speed by doing the same simulation at three speed levels. In the nonlinear region, the simulation condition was set such that the vehicle became unstable. In the linear region, steering input and cornering stiffness have a relatively large effect on the estimation error because these quantities determine tire side force. In the nonlinear region, the road surface’s friction coefficient becomes a crucial factor. In both the regions, the observer is sensitive to yaw rate and longitudinal speed.     

Sensitivity analysis of side-slip angle observer based on a tire model

We investigated the sensitivity of an observer based on a tire model using simulation in linear and nonlinear regions. In the linear region, we investigated the influence of vehicle speed by doing the same simulation at three speed levels. In the nonlinear region, the simulation condition was set such that the vehicle became unstable. In the linear region, steering input and cornering stiffness have a relatively large effect on the estimation error because these quantities determine tire side force. In the nonlinear region, the road surface's friction coefficient becomes a crucial factor. In both the regions, the observer is sensitive to yaw rate and longitudinal speed.     

Investigation on evaluation of yaw stability for medium commercial vehicles

This paper proposes test scenarios for evaluation of yaw stability for medium commercial vehicles. Maneuvering, speed, longitudinal tire force, tire-road friction coefficient, road slope, and load condition are considerable factors that have effect on the medium commercial vehicle yaw stability. After conducting an analysis on these six factors, effective test scenarios were developed. A sine with dwell test is well known as a test scenario for evaluation of performance of electronic stability control (ESC) on passenger vehicles and heavy commercial vehicles. The SWD test was modified considering medium commercial vehicle dynamics, and the ramp steer maneuver with maximum acceleration test was proposed. Simulation validation has been conducted using field test data. From simulation study, it was shown that the ESC system for medium commercial vehicle is effectively evaluated by the proposed test scenarios.     

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。     

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.     

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.     

智能汽车自动紧急转向避撞的跟踪控制方法对比研究

为了提高智能汽车的主动安全性,提出3种不同的自动紧急转向避撞跟踪控制方法。首先建立汽车避撞简化模型,对制动、转向及两者相结合的3种不同避撞方式进行对比分析。其次,为深入研究汽车避撞过程中的实际响应,建立包含转向、制动及悬架3个子系统耦合特性的底盘18自由度统一动力学模型,并进行相关试验验证。随后构建智能汽车自动紧急转向避撞控制框架,对五次多项式参考路径和七次多项式参考路径的横摆角速度和横摆角加速度进行对比分析。接着以线性2自由度转向动力学模型为参考对象,对最优控制四轮转向、最优控制前轮转向、前馈与反馈控制相结合的前轮转向3种不同的跟踪控制系统分别进行设计。最后,以汽车底盘18自由度统一动力学模型为研究对象,对上述3种避撞控制系统进行仿真试验对比分析。研究结果表明：与制动避撞相比而言,转向避撞所需的纵向距离有较大降低,随着车速的增加和路面附着系数的越低,效果越明显;七次多项式参考路径比五次多项式参考路径的避撞过渡过程更为平缓,当实际车速与控制器所用车速不一致时,前者避撞性能表现更优;最优四轮转向控制系统在高、低2种不同附着路面都具有较好的避撞效果,最优前轮转向控制系统次之,而前馈与反馈相结合的前轮转向控制系统在低附着路面上则表现出严重的失稳。     

Comparison of Feedforward and Feedback Control for 4WS

A system incorporating feedforward plus feedback control was configured such that it would follow the target yaw rate found by calculation. Selection of optimum values for the control system constants made it possible to separate control of the steering input response characteristic from control of vehicle stability against external disturbances. The former is controlled by the feedforward control function and the latter by the feedback control function; the values of the two functions can be set independently.