Estimation of vehicle sideslip, tire force and wheel cornering stiffness

This paper presents a process for the estimation of tire–road forces, vehicle sideslip angle and wheel cornering stiffness. The method uses measurements (yaw rate, longitudinal/lateral accelerations, steering angle and angular wheel velocities) only from sensors which can be integrated or have already been integrated in modern cars. The estimation process is based on two blocks in series: the first block contains a sliding-mode observer whose principal role is to calculate tire–road forces, while in the second block an extended Kalman filter estimates sideslip angle and cornering stiffness. More specifically, this study proposes an adaptive tire-force model that takes variations in road friction into account. The paper also presents a study of convergence for the sliding-mode observer. The estimation process was applied and compared to real experimental data, in particular wheel force measurements. The vehicle mass is assumed to be known. Experimental results show the accuracy and potential of the estimation process.     

Evaluation of a sliding mode observer for vehicle sideslip angle

This paper presents a sliding mode observer of vehicle sideslip angle, which is the principal variable relating to the transversal forces at the tire/road interface. The vehicle is first modelled, and the model is subsequently simplified. This study validates the observer using both a validated simulator and real experimental data acquired by the Heudiasyc laboratory car, and also shows the limitations of this method. The observer requires a yaw rate sensor and data about vehicle speed are required in order to estimate sideslip angle. Some properties of the nonlinear observability matrix condition number are discussed, and relations between this variable and observation error, vehicle speed and tire cornering stiffness are presented.     

轮式移动机器人滑移量重建与滑移补偿控制

为解决轮式移动机器人的滑移补偿控制问题,首先推导出车体侧滑角的表达式,然后将时变侧滑角的重建问题转化为对地面特性参数的辨识问题.利用Luenberger观测器设计出自适应辨识律,并证明了当控制输入满足持续激励条件时,可以准确辨识出地面特性参数.基于链式系统模型设计出滑移补偿控制器,在滑移角精确已知的条件下,可以保证位置误差收敛,姿态误差有界.仿真结果表明,基于所设计的自适应辨识律,可以准确地重建出滑移角,提高滑移控制精度.     

非结构道路环境下的智能汽车质心侧偏角估计

车辆质心侧偏角是描述车辆侧向运动状态的重要参量之一,其估计的精度直接影响车辆的安全控制,传统的质心侧偏角估计方法不能满足非结构道路环境下的智能汽车质心侧偏角估计的要求。通过建立3自由度智能汽车动力学模型,采用CarSim和MATLAB构建智能汽车整车参数化模型;基于扩展kalman滤波(EKF)算法,设计非结构道路环境下的状态观测器对智能汽车质心侧偏角进行估计。在高、低附着系数路面双移线工况和蛇形工况下,对状态观测器的估计效果进行联合仿真验证。仿真结果表明:该方法能较精确地估计出非结构道路环境下智能汽车的质心侧偏角。     

Tire–road friction coefficient and tire cornering stiffness estimation based on longitudinal tire force difference generation

A sequential tire cornering stiffness coefficient and tire–road friction coefficient (TRFC) estimation method is proposed for some advanced vehicle architectures, such as the four-wheel independently-actuated (FWIA) electric vehicles, where longitudinal tire force difference between the left and right sides of the vehicle can be easily generated. Such a tire force difference can affect the vehicle yaw motion, and can be utilized to estimate the tire cornering stiffness coefficient and TRFC. The proposed tire cornering stiffness coefficient and TRFC identification method has the potential of estimating these parameters without affecting the vehicle desired motion control and trajectory tracking objectives. Simulation and experimental results with a FWIA electric vehicle show the effectiveness of the proposed estimation method.     

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.     

多工况适应的车辆质心侧偏角观测算法研究

研究汽车高速运行稳定性优化控制问题,在车辆稳定性控制中,质心侧偏角是衡量稳定性的重要指标,观测对于稳定性控制非常重要。针对目前车载多传感器信息的观测条件,为解决质心侧偏角观测的准确性、快速性和多工况适应性问题,提出了一种融合卡尔曼滤波和信号积分的质心侧偏角观测算法。观测算法充分考虑了车辆动力学特性,采用车辆运行过程的多种工况进行了算法设计及切换。最后在Matlab/Simulink平台上搭建了质心侧偏角观测仿真实验平台,通过多工况下的仿真,对所提出的质心侧偏角观测算法进行了仿真验证,结果表明能快速准确地矫正质心侧偏角,使稳态误差减小。     

Identification of vehicle parameters using stationary driving maneuvers

Using the velocity dependent static gains of the one track model it is shown how special combinations of parameters like cornering stiffness and center of gravity can be estimated. Driving with various speed and a constant cornering radius it is possible to estimate three different gains by measurement of the lateral acceleration, the yaw rate and the vehicle slip angle without knowing the moment of inertia of the vehicle. Results are shown for different measurements of a passenger car.     

Robust anti-sliding control of autonomous vehicles in presence of lateral disturbances

Path following control problem of autonomous vehicles is investigated, concerning both unmeasurable sliding effects and lateral disturbances which lead to some difficulties in designing autonomous control under complex environment. To deal with the sliding effects, sideslip angles are modeled and reconstructed by estimating the tire cornering stiffness, which plays important role in analyzing the sliding effects. To this end, a Luenberger-type observer is designed, which is able to identify the tire cornering stiffness adaptively even in presence of time-varying lateral disturbances. Furthermore, to guarantee high-precision guidance, a sliding mode controller is designed based on chained system theory, and this controller is shown to be robust to both the lateral disturbances and the inaccuracy of the sliding reconstruction. Simulations illustrate that the proposed methods can reconstruct the sliding angles and provide high-accuracy anti-sliding control even in presence of the time-varying lateral disturbances.     

Application of global sensitivity analysis to a tire model with correlated inputs

When a vehicle equipped with tire is manoeuvred on the ground, the tires are submitted to a number of forces – longitudinal force when driving or braking torque is applied to the wheel and/or lateral force when the wheel is steered to turn at a corner. Pacejka model describes these forces that represent the reaction of the road onto the tire. This nonlinear model depends on correlated parameters such as the friction coefficient, the vertical load, and the cornering stiffness, which have to be identified from some measurements. The sensitivity of Pacejka model to these correlated parameters are studied using an approach based on polynomial chaos. It consists in decorrelating the parameters using the Nataf transformation and then, in expanding the model output onto polynomial chaos. The sensitivity indices are then obtained straightforwardly from the algebraic expression of the coefficients of the polynomial expansion.     

Set-membership LPV model identification of vehicle lateral dynamics

Set-membership identification of a Linear Parameter Varying (LPV) model describing the vehicle lateral dynamics is addressed in the paper. The model structure, chosen as much as possible on the ground of physical insights into the vehicle lateral behavior, consists of two single-input single-output LPV models relating the steering angle to the yaw rate and to the sideslip angle. A set of experimental data obtained by performing a large number of maneuvers is used to identify the vehicle lateral dynamics model. Prior information on the error bounds on the output and the time-varying parameter measurements are taken into account. Comparison with other vehicle lateral dynamics models is discussed.     

汽车操纵稳定性稳态响应参数的单位与量纲

针对表征汽车操纵稳定性状态的稳定性因数等参数的单位规定比较混乱的现状,根据角度物理量有单位但无量纲的特点,在轮胎侧偏刚度取两种不同单位的情况下,对汽车转向稳态响应的稳定性因数及稳态横摆角速度增益等重要参数的单位及量纲进行了全面分析.     

A Tire Stiffness Backstepping Observer Dedicated to All-Terrain Vehicle Rollover Prevention

Most active devices focused on vehicle stability concern on-road cars and cannot be applied satisfactorily in an off-road context, since the variability and the non-linearities of tire/ground contact are often neglected. In previous work, a rollover indicator devoted to light all-terrain vehicles accounting for these phenomena has been proposed. It is based on the prediction of the lateral load transfer. However, such an indicator requires the on-line knowledge of the tire cornering stiffness. Therefore, in this paper, an adapted backstepping observer, making use only of yaw rate measurement, is designed to estimate tire cornering stiffness and to account for its non-linearity. The capabilities of such an observer are demonstrated and discussed through both advanced simulations and actual experiments.     

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.     

Joint ego-motion and road geometry estimation

We provide a sensor fusion framework for solving the problem of joint ego-motion and road geometry estimation. More specifically we employ a sensor fusion framework to make systematic use of the measurements from a forward looking radar and camera, steering wheel angle sensor, wheel speed sensors and inertial sensors to compute good estimates of the road geometry and the motion of the ego vehicle on this road. In order to solve this problem we derive dynamical models for the ego vehicle, the road and the leading vehicles. The main difference to existing approaches is that we make use of a new dynamic model for the road. An extended Kalman filter is used to fuse data and to filter measurements from the camera in order to improve the road geometry estimate. The proposed solution has been tested and compared to existing algorithms for this problem, using measurements from authentic traffic environments on public roads in Sweden. The results clearly indicate that the proposed method provides better estimates.     

Estimations of previewed road curvatures and vehicular motion by a vision-based data fusion scheme

In this study, a new framework of vision-based estimation is developed using some data fusion schemes to obtain previewed road curvatures and vehicular motion states based on the scene viewed from an in-vehicle camera. The previewed curvatures are necessary for the guidance of an automatically steering vehicle, and the desired vehicular motion variables, including lateral deviation, heading angle, yaw rate, and sideslip angle, are also required for proper control of the vehicular lateral motion via steering. In this framework, physical relationships of previewed curvatures among consecutive images, motion variables in terms of image features searched at various levels in the image plane, and dynamic correlation among vehicular motion variables are derived as bases of data fusion to enhance the accuracy of estimation. The vision-based measurement errors are analyzed to determine the fusion gains based on the technique of a Kalman filter such that the measurements from the image plane and predictions of physical models can be properly integrated to obtain reliable estimations. Off-line experimental works using real road scenes are performed to verify the whole framework for image sensing.     

Vehicle sideslip estimator using load sensing bearings

This paper investigates the potential of load based vehicle sideslip estimation. Different techniques to measure tyre forces have been presented over the years; so far no technique has made it to the market. This paper considers a new technology based on load sensing bearings, which provides tyre force measurements. Based on the features of the sensor, a vehicle sideslip angle estimator is designed, analyzed and tested. The paper shows that direct tyre force sensing has mainly two advantages over traditional model-based estimators: primarily, it avoids the use of tyre models, which are heavily affected by uncertainties and modeling errors and secondarily, providing measurements on the road plane, it is less prone to errors introduced by roll and pitch dynamics. Extensive simulation tests along with a detailed analysis of experimental tests performed on an instrumented vehicle prove that the load based estimation outperforms the kinematic model-based benchmark yielding a root mean square error of 0.15°.     

非独立悬架车辆自激摆振的数值仿真分析

基于一个三自由度的转向系统模型,利用数值仿真方法分析了横拉杆刚度、主销后倾角、转向机刚度、轮胎侧偏刚度、轮胎拖距、转向机阻尼、绕主销当量阻尼等参数对载重汽车自激型摆振的影响.仿真分析的结果表明,上述参数发生变化时,可诱发自激摆振,但车速也是影响摆振的关键因素之一.在确定的系统参数和车速下,初始激励不仅可能诱发稳定的自激摆振,还可能是发散的运动.与受迫型自激摆振不同,自激型摆振的频率变化与车速的变化并不一致.     

Vehicle sideslip estimation: A kinematic based approach

This paper deals with vehicle sideslip angle estimation. The paper introduces an industrially amenable kinematic-based approach that does not need tire–road friction parameters or other dynamical properties of the vehicle. The convergence of the estimate is improved by the introduction of a heuristic based on readily available inertial measurements. The method is tested on a vast collection of tests performed in different conditions, showing a satisfactory behavior despite not using any information on the road friction. The extensive experimental validation confirms that the estimate is robust to a wide range of driving scenarios.     

智能车辆横向控制研究

本文分析了智能车辆横向控制特性，说明了目前一些研究中的不足，并探讨了 模糊控制方法．仿真结果表明，该算法对纵向速度、轮胎侧偏刚度以及载荷等明显影响车辆 横向运动特性的三个关键因素具有良好的适应性能．