车辆横摆角速度估计方法的研究

总结和归纳了车辆横摆角速度估计的方法。给出了基于运动学模型和动力学模型的横摆角速度估计的基本算法，并分析了各种方法的优缺点。指出了横摆角度估计研究的重要实际意义，同时也为开展车辆横摆角速度估计的理论研究提供了方法和思路上的指导。     

基于路面识别的汽车稳定系统滑模控制

深入分析了质心侧偏角、横摆角速度和路面附着系数与汽车稳定性之间的关系,根据汽车线性2自由度模型获得了汽车期望质心侧偏角和期望横摆角速度的稳定值,并提出了基于递归最小二乘法的路面附着系数识别算法。在此基础上,基于滑模控制理论采用指数趋近律分别设计了横摆角速度、质心侧偏角和两者联合为控制变量的汽车稳定滑模控制器,获得附加横摆力矩。Car Sim/Simulink仿真验证了所提出的路面附着系数估算算法的正确性和对应路面附着系数下汽车稳定控制策略的有效性。同时,基于Car Sim/Lab VIEW RT的硬件在环仿真试验,验证了所提出控制策略的可行性。     

基于横摆角速度的汽车ESP系统的仿真研究

横摆角速度是控制汽车横向稳定性的主要控制变量.基于横摆角速度对汽车ESF,系统进行仿真研究,首先在建立ADAMS/CAR中建立汽车整车模型,然后建立汽车理想二自由度参考模型,设计横摆角速度反馈控制PID控制器.仿真结果表明,基于横摆角速度控制的ESP系统控制的汽车明显改善汽车横向稳定性,提高了汽车行驶安全性能.     

基于整车模型的PEV理想横摆角速度确定方法

四轮独立驱动的纯电动汽车(Pure Electric Vehicle,PEV)的理想横摆角速度确定方法不同于传统汽车。为了使电子稳定程序(Electronic Stability Program,ESP)控制系统介入的时机更为恰当,提高车辆对驾驶员意图的响应性能以及避免系统介入不适当对驾驶员正常行驶意图的干扰,针对一种由4个轮毂电机独立驱动的PEV,在线性二自由度模型确定车辆理想横摆角速度的基础上,利用Matlab/Simulink建立七自由度整车模型,考虑不同路面附着系数和各轮垂直载荷的影响,提出了适用于四轮独立驱动PEV理想横摆角速度的修正算法。通过对固定前轮转向角的纯电动汽车在纯路面、对接路面以及分离路面上理想横摆角速度随车速变化的仿真结果进行分析,得出了PEV理想横摆角速度的变化规律,为四轮独立驱动PEV理想横摆角速度的确定提供了理论基础。     

四轮转向汽车虚拟样机闭环控制操纵动力学仿真

运用ADAMS软件建立了新型四轮转向(4WS)汽车整车虚拟样机模型,利用该模型对比了基于横摆角速度多状态最优控制的4WS汽车同前轮转向(FWS)汽车及其它不同控制算法的阴轮转向汽车(后轮比例于前轮转角算法及后轮转角比例于横摆角速度算法)的操纵稳定性。仿真结果表明,基于横摆角速度多状态最优控制的4WS汽车,其各项评价指标优于FWS汽车以及采用另外两种控制方法的4WS汽车。     

车身侧倾时前轮主销后倾角对转向稳定性的影响

为了提高4×4越野车弯道高速行驶的稳定性,计及前轮定位参数的影响,建立了转向行驶时整车4自由度动力学模型;计算了车辆在不同车速下,不同前轮主销后倾角时的横摆角速度瞬态响应.结果表明,车速提高时,横摆角速度超调量增大,稳定时间延长;而在适当范围内增大主销后倾角,可减小横摆角速度超调量和稳定时间,改善高速行驶车辆的转向稳定性.同时说明主销后倾角对横摆角速度超调量有阻尼作用.     

引入悬架K&C参数二自由度模型的建立及验证

横摆角速度是影响操纵稳定性的重要因素。在汽车行驶过程中，给其施加角阶跃输入，分析横摆角速度响应是评价汽车操纵稳定性的重要方法。文章简化汽车模型，利用牛顿第二定律建立经典二自由度线性模型及引入K&C参数的数学模型。输入整车参数、K&C试验参数，将两模型MATLAB横摆角速度响应结果与Carsim仿真结果进行对比，验证模型的可靠性，可利用二自由度模型快速获取车辆操纵稳定性的大致情况。     

线控转向车辆前轮转角控制算法研究

以线性二自由度车辆模型为基础,以中性转向时的横摆角速度作为控制目标,提出了两种线控转向车辆前轮转角控制算法,即前馈补偿控制算法和横摆角速度反馈控制算法,并通过仿真试验对两种控制算法进行了研究。     

A Study on the Variable-gain Tracking Control for the Four Wheel Steering System of Vehicles

在分析车身侧倾对转向系统影响的基础上,对转向系统通常采用的参考模型进行修改,并探讨了轮胎侧偏刚度和车速对参考模型横摆角速度的影响.得出结论为,轮胎侧偏刚度对参考模型的横摆角速度增益有较大影响:前轮侧偏刚度的降低使横摆角速度大致成比例地减小.利用最优前馈和反馈控制方法,提出了四轮转向变增益跟踪控制策略.采用非线性半经验轮胎模型的仿真结果表明,所提出的变增益跟踪控制策略对车辆的操纵稳定性有重大改善.     

汽车稳定性控制系统的研究与仿真

在线性二自由度车辆模型基础上,采用直接横摆力矩控制方法,选取质心侧偏角和横摆角速度作为稳定性控制系统的主控变量,设计了三种具有针对性的基于滑模变结构理论的车辆操纵稳定性控制策略——质心侧偏角、横摆角速度和两者联合的滑模变结构控制。在Matlab,Simulink平台上,对三种汽车稳定性控制策略的具体应用进行仿真分析,验证了所设计稳定性控制算法的有效性和鲁棒性。     

Full-slip kinematics based estimation of vehicle yaw rate from differential wheel speeds

Vehicle yaw rate is a key parameter required for various active stability control systems. Accurate yaw rate information may be obtained from the fusion of some on-vehicle sensors and GPS data. In this study, the closed-form expression of the yaw rate–written as a function of front wheel rolling speeds and steering angle–was derived via kinematic analysis of a planar four-wheel vehicle on the assumption of no longitudinal slip at the both front tires. The obtained analytical solution was primarily verified by computational simulation. In terms of implementation, the 1:10th scaled rear-wheel-drive vehicle was modified so that the front wheel rolling speeds and the steering angle could be measured. An inertial measurement unit was also installed to provide the directly measured yaw rate used for validation. Preliminary experiment was done on some extremely random sideslip maneuvers beneath the global positioning using four recording cameras. Comparing with the vision-based and the gyro-based references, the vehicle yaw rate could be well approximated at any slip condition without requiring integration or vehicle and tire models. The proposed cost-effective estimation strategy using only on-vehicle sensors could be used as an alternative way to enhance performance of the GPS-based yaw rate estimation system while the GPS signal is unavailable.     

Vehicle stability control system for enhancing steerabilty,lateral stability,and roll stability

The Vehicle stability control system is an active safety system designed to prevent accidents from occurring and to stabilize dynamic maneuvers of a vehicle by generating an artificial yaw moment using differential brakes. In this paper, in order to enhance vehicle steerability, lateral stability, and roll stability, each reference yaw rate is designed and combined into a target yaw rate depending on the driving situation. A yaw rate controller is designed to track the target yaw rate based on sliding mode control theory. To generate the total yaw moment required from the proposed yaw rate controller, each brake pressure is properly distributed with effective control wheel decision. Estimators are developed to identify the roll angle and body sideslip angle of a vehicle based on the simplified roll dynamics model and parameter adaptation approach. The performance of the proposed vehicle stability control system and estimation algorithms is verified with simulation results and experimental results.     

Using GPS with a model-based estimator to estimate critical vehicle states

This paper demonstrates a method to estimate the vehicle states sideslip, yaw rate, and heading using GPS and yaw rate gyroscope measurements in a model-based estimator. The model-based estimator using GPS measurements provides accurate and observable estimates of sideslip, yaw rate, and heading even if the vehicle model is in neutral steer or if the gyro fails. This method also reduces estimation errors introduced by gyroscope errors such as the gyro bias and gyro scale factor. The GPS and Inertial Navigation System measurements are combined using a Kalman filter to generate estimates of the vehicle states. The residuals of the Kalman filter provide insight to determine if the estimator model is correct and therefore providing accurate state estimates. Additionally, a method to predict the estimation error due to errors in the estimator model is presented. The algorithms are tested in simulation with a correct and incorrect model as well as with sensor errors. Finally, the estimation scheme is tested with experimental data using a 2000 Chevrolet Blazer to further validate the algorithms.     

基于蚁狮算法的UKF车辆状态参数估计器

为了准确获取分布式驱动电动汽车状态参数信息，满足车辆稳定性控制系统的需求，提出一种基于蚁狮算法的无迹卡尔曼滤波状态参数估计器。针对无迹卡尔曼滤波（UKF）过程中噪声协方差矩阵的不确定性，采用蚁狮优化算法（ALO）对其进行寻优，并引入奇异值分解（SVD）的方法来维持噪声协方差矩阵的正定性，此外，基于指数加权最小二乘法对车辆侧偏刚度进行辨识并将其作为状态参数估计器输入。基于MATLAB/Simulink和CarSim联合仿真平台，建立分布式驱动电动汽车参数估计模型，分别进行双移线工况和正弦迟滞工况仿真，并基于A&D5435快速原型开发平台进行双移线工况实车试验。仿真与试验结果表明：相比于SVDUKF算法估计结果，双移线仿真工况下，基于ALO-SVDUKF算法估计得到的质心侧偏角和横摆角速度的均方根误差分别降低了55.7%、30.7%，正弦迟滞仿真工况下，均方根误差分别降低了58.1%、85.1%，且在车辆处于极限失稳状态时仍能维持较好的估计效果；双移线试验工况下，横摆角速度的估计值与实际测量值之间的均方根误差仅为0.938 4（°）·s^-1；提出的基于ALO-SVDUKF算法的分布式驱动电动汽车状态参数估计器能够有效提高质心侧偏角和横摆角速度的估计精度，可为车辆稳定性控制提供精确的状态信息。     

Modeling and control of an anti-lock brake and steering system for cooperative control on split-mu surfaces

The brake and steering systems in vehicles are the most effective actuators that directly affect the vehicle dynamics. In general, the brake system affects the longitudinal dynamics and the steering system affects the lateral dynamics; however, their effects are coupled when the vehicle is braking on a non-homogenous surface, such as a split-mu road. The yaw moment compensation of the steering control on a split-mu road is one of the basic functions of integrated or coordinated chassis control systems and has been demonstrated by several chassis suppliers. However, the disturbance yaw moment is generally compensated for using the yaw rate feedback or using wheel brake pressure measurement. Access to the wheel brake pressure through physical sensors is not cost effective; therefore, we modeled the hydraulic brake system to avoid using physical sensors and to estimate the brake pressure. The steering angle controller was designed to mitigate the non-symmetric braking force effect and to stabilize the yaw rate dynamics of the vehicle. An H-infinity design synthesis was used to take the system model and the estimation errors into account, and the designed controller was evaluated using vehicle tests.     

Vehicle sideslip estimation and compensation for banked road

The sideslip driving status is of fundamental importance to the stability of a vehicle. This paper presents a practical vehicle sideslip driving status estimation method that uses ESP (electronic stability program) sensors. ESP sensors such as wheel speed, lateral acceleration, yaw rate and steering wheel angle sensors are used to determine the sideslip driving status and distinguish a banked road. This estimation algorithm contains front-rear sideslip and banked road detection methods. The proposed sideslip estimation algorithm was designed to use the analytical redundancy of these sensors and Lagrange interpolation methods. The performance and effectiveness of the proposed estimation and compensation algorithm were investigated using vehicle tests. This paper presents the results of two cases that were used for the experimental verification: a curved flat road and banked road.     

基于横摆角速度的汽车ESP系统模糊反馈控制方法

作为一种先进的车辆主动安全技术,车辆电控稳定系统(ESP)已在国外许多高级轿车上得到应用。它是在ABS和ASR的基础上,增加了车辆转向行驶时横摆速率传感器、侧向加速传感器和方向盘转角传感器,通过这些传感器发出的信号监测车辆的状态和驾驶员的需求。当路面状况改变,使车辆行驶     

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。     

Adaptive Yaw Rate Feedback 4WS with Tire/Road Friction Coefficient Estimator

This paper proposes an adaptive yaw rate feedback control system for a four-wheel-steering (4WS) vehicle which involves a tire/road friction coefficient estimator. The adaptive 4WS system has been developed so that the vehicle possesses desirable lateral characteristics even on slippery roads and in critical driving situations. The friction coefficient is estimated on real time from the yaw rate response of the controlled vehicle with the least squares. The control system adopts a two degree of freedom structure which consists of a feedforward compensator and a feedback control subsystem. The feedforward compensator is determined with the estimated friction coefficient to minimize the steady-state and transient vehicle slip angle in spite of changes in tire/road conditions. The feedback subsystem adopts the Internal Model Control (IMC) structure in order to compensate for nonlinearities and to realize robustness against modelling and estimation errors.     

Slip-based terrain estimation with a skid-steer vehicle

In this paper, a novel approach for online terrain characterisation is presented using a skid-steer vehicle. In the context of this research, terrain characterisation refers to the estimation of physical parameters that affects the terrain ability to support vehicular motion. These parameters are inferred from the modelling of the kinematic and dynamic behaviour of a skid-steer vehicle that reveals the underlying relationships governing the vehicle-terrain interaction. The concept of slip track is introduced as a measure of the slippage experienced by the vehicle during turning motion. The proposed terrain estimation system includes common onboard sensors, that is, wheel encoders, electrical current sensors and yaw rate gyroscope. Using these components, the system can characterise terrain online during normal vehicle operations. Experimental results obtained from different surfaces are presented to validate the system in the field showing its effectiveness and potential benefits to implement adaptive driving assistance systems or to automatically update the parameters of onboard control and planning algorithms.