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.     

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.     

Design and evaluation of sideslip angle observer for vehicle stability control

This paper presents a method for estimating the vehicle side slip angle, which is considered as a significant signal in determining the vehicle stability region in vehicle stability control systems. The proposed method combines the model-based method and kinematics-based method. Side forces of the front and rear axles are provided as a weighted sum of directly calculated values from a lateral acceleration sensor and a yaw rate sensor and from a tire model according to the nonlinear factor, which is defined to identify the degree of nonlinearity of the vehicle state. Then, the side forces are fed to the extended Kalman filter, which is designed based on the single-track vehicle model associated with a tire model. The cornering stiffness identifier is introduced to compensate for tire force nonlinearities. A fuzzy-logic procedure is implemented to determine the nonlinear factor from the input variables: yaw rate deviation from the reference value and lateral acceleration. The proposed observer is compared with a model-based method and kinematics-based method. An 8 DOF vehicle model and Dugoff tire model are employed to simulate the vehicle state in MATLAB/SIMULINK. The simulation results shows that the proposed method is more accurate than the model-based method and kinematics-based method when the vehicle is subjected to severe maneuvers under different road conditions.     

极限工况下主动前轮转向汽车稳定性控制

轮胎对汽车稳定性有重要影响,研究和利用轮胎的非线性特性有助于扩展汽车的稳定域。本文基于非线性轮胎模型,提出一种改进型线性时变模型预测控制(LTV-MPC)方法。该方法能扩展主动前轮转向汽车的稳定范围,提高极限工况下主动前轮转向汽车的稳定性。仿真结果表明,该方法比传统的LTV-MPC方法具有更好的稳定性控制效果。     

Tire wear estimation based on nonlinear lateral dynamic of multi-axle steering vehicle

This paper presents a novel nonlinear dynamic model of a multi-axle steering vehicle to estimate the lateral wear amount of tires. Firstly, a 3DOF nonlinear vehicle dynamic model is developed, including dynamic models of the hydropneumatic suspension, tire, steering system and toe angle. The tire lateral wear model is then built and integrated into the developed vehicle model. Based on the comparison of experimental and simulation results, the nonlinear model is proved to be better than a linear model for the tire wear calculation. In addition, the effects of different initial toe angles on tire wear are analyzed. As simulation results shown, the impact of the dynamic toe angle on the tire wear is significant. The tire wear amount will be much larger than that caused by normal wear if the initial toe angle increases to 1° - 1.5°. The results also suggest that the proposed nonlinear model is of great importance in the design and optimazation of vehicle parameters in order to reduce the tire wear.     

基于扩展卡尔曼滤波的汽车质心侧偏角估计

基于二自由度汽车动力学模型和轮胎模型,运用扩展卡尔曼滤波方法建立了汽车质心侧偏角估计器.利用汽车动力学仿真平台,通过仿真对比了线性轮胎模型和非线性轮胎模型的质心侧偏角估计结果.仿真结果表明,轮胎模型对于质心侧偏角估计精度至关重要,而采用非线性轮胎模型能显著提高质心侧偏角估计精度,估计结果能满足ESC控制的要求.     

Estimation of Tire-Road Friction Using Observer Based Identifiers

This paper presents methods for identifying the tire-road friction coefficient. The proposed methods are: an observer-based least square method and an observer/filtered-regressor-based method. These methods were designed assuming that some of the states are not available since physical parameter identification methods developed assuming that the system states are available are not attractive from a practical point of view. The observer is used to estimate signals which are difficult or expensive to measure. Using the estimated states of the system and the filtered-regressor, the parameter estimates are obtained. The proposed methods are evaluated on an eight state nonlinear vehicle/transmission simulation model with a Bakker-Pacejka's formula tire model. Vehicle tests have been performed on dry and wet roads to verify the performance of the methods. It has been shown through simulations and vehicle tests how the RPM sensors can be used with observer based identification methods to estimate the tire-road friction from measurements of engine rpm, transmission output speed and wheel speed. The proposed methods will be useful in the implementation and adaptation of vehicle collision warning/avoidance algorithm since the tire-road friction can be estimated only using the RPM sensors which are currently being used in production vehicles.     

A reduced-order nonlinear sliding mode observer for vehicle slip angle and tyre forces

In this paper, a reduced-order sliding mode observer (RO-SMO) is developed for vehicle state estimation. Several improvements are achieved in this paper. First, the reference model accuracy is improved by considering vehicle load transfers and using a precise nonlinear tyre model ‘UniTire’. Second, without the reference model accuracy degraded, the computing burden of the state observer is decreased by a reduced-order approach. Third, nonlinear system damping is integrated into the SMO to speed convergence and reduce chattering. The proposed RO-SMO is evaluated through simulation and experiments based on an in-wheel motor electric vehicle. The results show that the proposed observer accurately predicts the vehicle states.     

Vehicle velocity estimation for real-time dynamic stability control

A new approach is proposed for nonlinear asymptotic observers based on the cascade observer system with a fusion of sensor signals. In the observers, the characteristic of the vehicle dynamic system, the nonlinear tire force estimation, load transfer estimation, and road ramp angle compensation are considered. The errors in the observation of vehicle velocity were diminished, and the computation cost was decreased for a real-time microcontroller. Simulation and real vehicle test results validate the higher accuracy of the velocity estimation by the proposed observers under complicated handling maneuver conditions.     

Nonlinear Dynamics of Vehicle Traction

Summary The purpose of this study is to understand the nonlinear dynamics of longitudinal ground vehicle traction. Specifically, single-wheel models of rubber-tired automobiles under straight-ahead braking and acceleration conditions are investigated in detail. Customarily, the forward vehicle speed and the rotational rate of the tire/wheel are taken as dynamic states. This paper motivates an alternative formulation in which wheel slip, a dimensionless measure of the difference between the vehicle speed and the circumferential speed of the tire relative to the wheel center, replaces the angular velocity of the tire/wheel as a dynamic state. This formulation offers new insight into the dynamic behavior of vehicle traction. The unique features of the modeling approach allow one to capture the full range of dynamic responses of the single-wheel traction models in a relatively simple geometric manner. The models developed here may also be useful for developing and implementing anti-lock brake and traction control control schemes.     

汽车油管式动态称重的仿真与分析

介绍了油管式汽车动态称重系统。运用VPG技术、利用动态显式非线性有限元分析软件LS-DYNA对某两轴货车满载驶过油管式称重仪的全过程进行了数值模拟。分析单/双胎、车速、油管内初始油压和管径等因素对传感器输出特性的影响。仿真分析结果与实车试验结果趋势一致,验证了仿真分析方法的正确性。     

Nonlinear Dynamics of Vehicle Traction

Summary The purpose of this study is to understand the nonlinear dynamics of longitudinal ground vehicle traction. Specifically, single-wheel models of rubber-tired automobiles under straight-ahead braking and acceleration conditions are investigated in detail. Customarily, the forward vehicle speed and the rotational rate of the tire/wheel are taken as dynamic states. This paper motivates an alternative formulation in which wheel slip, a dimensionless measure of the difference between the vehicle speed and the circumferential speed of the tire relative to the wheel center, replaces the angular velocity of the tire/wheel as a dynamic state. This formulation offers new insight into the dynamic behavior of vehicle traction. The unique features of the modeling approach allow one to capture the full range of dynamic responses of the single-wheel traction models in a relatively simple geometric manner. The models developed here may also be useful for developing and implementing anti-lock brake and traction control control schemes.     

Analytical Tire Models for Dynamic Vehicle Simulation

Four basic tire models suitable for dynamic vehicle simulation are formulated. The models are compared through a six-degree-of-freedom nonlinear simulation of a cargo truck crossing rough ground. Guidelines are developed for the selection of an optimum tire model for a given dynamic vehicle simulation.     

基于车路系统的事故现场轮胎印迹强度参数化研究

为明确事故现场可视轮胎印迹强度与车辆动力学特性、轮胎橡胶磨损特征及道路表面灰度之间的关联特性,提出基于车路耦合的事故现场轮胎印迹强度参数化研究方法。通过结合动态滑动摩擦因数模型及轮胎非线性模型,建立车辆路面9 DOF非线性系统动力学模型,运用VBOX惯性测量技术验证模型的有效性。运用胎面磨损能量模型,从车路系统角度确定车辆、轮胎和路面特性对轮胎全局摩擦力及胎面磨损特性的影响。结合印迹强度特征模型提出轮胎印迹强度参数研究方法,选取不同制动、转向角工况及3组路面、胎面特性对轮胎路面接地力学特性、胎面橡胶磨损量、可视轮胎印迹特征进行仿真分析。结果表明：印迹强度仅与全局摩擦力大小有关,与轮胎路面滑移方向无关;滑移工况下胎面橡胶磨损量随着全局摩擦力和滑移速度的增大而增大,而印迹强度变化不明显;制动力矩和道路表面灰度对产生可视轮胎印迹起决定作用,转向角主要影响不规则可视轮胎印迹的产生;前轮轮胎最先出现可视印迹,且可视印迹长度和强度均高于后轮轮胎;采取可视印迹起点作为事故车辆速度判定具有一定的误差,应根据具体情况进行具体分析;研究成果能够为基于可视轮胎印迹的交通事故重建提供理论基础。     

Effects of Model Complexity on the Performance of Automated Vehicle Steering Controllers: Controller Development and Evaluation

SUMMARY

Due to increased traffic congestion and travel times, research in Advanced Vehicle Control Systems (AVCS) has focused on automated lateral and headway control. Automated vehicles are seen as a way to increase freeway capacity and vehicle speeds while reducing accidents due to human error. Recent research in automated lateral control has focused on vehicle control during low-g maneuvers. To increase safety, automated lateral controllers will need to recognize and react to emergency situations.

This paper investigates the effects of vehicle and tire model order on the response of automated vehicles to an emergency step lane change using a controller based on linear vehicle and tire models. From these studies it is concluded that control strategies based solely on linear vehicle and tire models are inadequate for emergency vehicle maneuvers.

A strategy is then proposed to automatically control vehicles through emergency maneuvers. Here the response of a nonlinear vehicle model is used with a linear state model to optimize controller gains for nonlinear maneuvers. An emergency step lane change is used as a preliminary test of the method.     

路面附着系数的自适应衰减卡尔曼滤波估计

为了获得实时、准确的路面附着系数，进一步提高观测路面附着系数算法的精度和收敛速度，结合非线性车辆动力学模型和轮胎力修正模型，搭建分布式驱动电动汽车联合仿真平台，提出一种基于自适应衰减无迹卡尔曼滤波的路面附着系数观测算法。该算法设计与各轮对应的路面附着系数观测器，应用协方差匹配判据对观测器发散趋势进行判别，设计自适应加权系数修正预测协方差，以增强新近观测数据的利用率；同时采用次优Sage-Husa噪声估计器对未知的系统过程噪声进行估计，抑制观测器的记忆存储长度，调整过程噪声和测量噪声的均值与协方差，提高观测器的跟踪能力。利用分布式驱动电动汽车分别进行高、低附着路面和对开路面直线制动试验，并将自适应衰减无迹卡尔曼滤波路面附着系数观测器的观测结果与无迹卡尔曼滤波观测值、参考路面附着系数进行比较和分析。结果表明：高附着路面条件下，所设计的算法估计误差可控制在0.64%以内；低附着路面条件下，所设计的算法估计误差可控制在1.03%以内；对开路面条件下估计误差可控制在1.26%以内；自适应衰减无迹卡尔曼滤波算法相比无迹卡尔曼滤波算法响应速率更快，具有更高的估计精度和较强的自适应能力，估计结果整体上维持稳定，能够适应各种不同路面的估计。     

基于带切换增益模糊调节的滑模控制算法的车辆电液制动系统

针对汽车线控电液制动系统建立了单轮车辆模型,研制了一种新的状态观测器对车速进行估算,试验结果表明该方法正确实用.采用切换增益模糊调节的滑模控制算法对非线性时变的车辆实施基于最佳滑移率的制动控制,在Matlab/Simulink中的仿真结果和验证试验都表明在汽车线控制动系统应用该算法是可行、有效的,在该算法的控制下汽车可获得比一般滑模控制更好的制动性能.     

客车轮胎建模和对侧倾稳定性的影响研究

客车轮胎与客车整车的侧倾稳定性有密切联系,ADAMS是典型的动力学虚拟样机仿真软件。介绍了在ADAMS中建立非线性轮胎的方法,在ADAMS中建立客车整车模型,通过改变整车模型中轮胎的刚度和阻尼,研究客车轮胎对整车侧倾稳定性的影响,从而为设计出符合性能要求的客车轮胎提供一定的理论依据。     

汽车爆胎特性建模与主动制动控制策略

为了提高汽车在突发爆胎事故时的稳定性,对爆胎汽车主动制动控制策略进行了研究。根据车轮爆胎时间与压力变化的关系,在UniTire模型基础上建立了爆胎模型;根据电子稳定性控制系统中横摆角速度及质心侧偏角对汽车稳定性影响的关系,基于二自由度汽车动力学模型,通过计算汽车横摆角速度及质心侧偏角实际值与理想值的偏差,并基于线性二次型调节器最优控制方法决策出最优附加横摆力矩,从而修正爆胎后汽车的运动状态。最后通过计算机仿真对所提策略的有效性进行了验证。结果表明：主动制动控制策略可以保证爆胎过程中汽车的行驶稳定性和安全性。     

基于轮胎-颗粒流动力学模型的避险车道参数匹配方案研究

为了优化山区公路避险车道参数设计方案,基于离散元基本理论与方法,建立轮胎与避险车道集料颗粒流模型。利用自主研发的轮胎性能测试系统对货车轮胎垂直特性进行了室内台架试验研究,通过检测不同输入条件下的响应,标定了轮胎颗粒流模型细观参数。采用漏斗法测量了避险车道集料休止角,结合离散元颗粒流仿真方法,对集料颗粒流模型表面摩擦因数进行了标定。基于所建立的轮胎与避险车道的集料颗粒流模型,仿真分析了轮胎在避险车道中的行驶过程,模拟了车辆在运行过程中的行驶距离、行驶速度与轮胎转速的变化趋势。在甘肃S308省道K209+400处避险车道进行了实车道路试验,试验结果验证了该仿真方法的正确性。通过所建立的轮胎-颗粒流模型对比分析了不同铺设厚度,不同集料大小下的仿真结果。综合考虑减速效果和施工成本,确立了避险车道铺设厚度、铺设长度、颗粒材料等设计技术参数。研究结果表明：离散元法能够很好地模拟车辆在避险车道中的行驶过程;考虑到颗粒固结等因素,建议避险车道铺设厚度不小于0.8 m;针对行驶速度大于90 km·h^-1的载货汽车,避险车道设计长度建议大于130 m;避险车道集料方面,建议选用粒径为1~3 cm且圆度较高的砾石作为路床材料。