车辆侧倾状态估计的研究

针对复杂行驶工况下车辆侧倾状态无法准确测取,因而对车辆侧倾无法有效控制的问题,本文中利用车辆耦合动力学与模糊T-S理论,设计了基于模型的T-S状态观测器算法,实现了复杂工况下车辆侧倾状态的实时有效观测。首先,构建了不同路面激励与转向盘转角工况下的车辆垂向与横向运动学模型;接着,在考虑轮胎受力具有强非线性特点的基础上,提出了基于T-S理论的轮胎T-S模型,并采用"魔术公式"对其进行了仿真验证;然后,基于轮胎T-S模型与整车动力学模型,利用贝叶斯理论,设计整车T-S观测器算法;最后,利用Car Sim软件对标准A/C级路面激励工况下整车T-S观测器实时估计的车辆侧倾角与侧倾率进行仿真验证。结果表明,所设计T-S观测器可有效估计车辆侧倾状态,最大标准偏差不超过12%。     

基于MPC的独立驱动电动汽车稳定性集成控制

针对独立驱动电动汽车在高附着系数路面高速急转时易发生侧翻事故,在低附着系数路面急转易发生侧滑失稳事故,且单一控制器在不同附着系数路面适应性较差等问题,根据独立驱动电动汽车特点设计了基于分层式结构的稳定性集成控制器。建立了整车动力学模型,并进行了车辆状态参数估计;设计了稳定性集成控制器的控制策略,对车辆的侧倾、横向稳定性状态判定条件和协调策略的制定进行了研究,分别设计了侧倾稳定性控制器和横向稳定性控制器;设置了路面附着系数0.9到0.2的对接路面仿真工况,并在此工况下对所设计的控制器的控制性能进行了仿真测试。结果表明,所设计的稳定性集成控制器相比于单一控制器具有更好的适应性,可有效降低车辆高速行驶过程中的横向载荷转移系数、质心侧偏角等状态量,提高车辆行驶的稳定性和安全性。     

基于增广卡尔曼滤波并考虑车辆加速度的路面不平度识别

为实现车辆在实际加减速行驶工况下路面不平度的准确识别,提出了一种考虑车辆加速度、基于增广卡尔曼滤波算法的路面识别方法.以车辆纵向加速度作为已知输入,车身垂向振动和俯仰振动响应作为观测向量,设计增广卡尔曼滤波观测器估计路面不平度信息;求取固定位移窗长度内的国际平整度指数,实现了对路面的等级分类.仿真结果表明在典型非匀速工...     

重型商用车载荷状态动态检测方法及试验研究

基于车辆悬架垂向变形量与车辆垂向载荷的相关关系,通过位移传感器搭建了具有过载保护功能的车辆载荷状态实时动态检测装置,采用经验模态分解法设计开发了用于车辆静态载荷和动态载荷分离的数据处理算法。为了分析构建的车辆状态实时动态检测系统在车辆行驶工况下检测结果的准确性和可靠性,以中国第一汽车厂赛龙载货汽车为试验车,分别在B级平直路面和3种不同的强化路面18种不同运行工况下进行了实车道路对比试验,试验结果表明:车辆在B级平直路面行驶时系统对车辆动态载荷检测误差小于5%;车辆在3种强化路面行驶时系统对车辆动态载荷检测误差小于8%。该系统为车辆载荷状态动态检测提供了一种新方法。     

基于扩展卡尔曼滤波的轮毂电机驱动电动汽车状态估计

以非线性八自由度车辆模型为基础,利用轮毂电机驱动电动汽车四轮转矩容易获得的独特优势,将车轮转角、各个车轮驱动力矩、侧向加速度及横摆角速度作为算法输入,采用扩展卡尔曼滤波(Extended Kalman Filter,EKF)理论设计了轮毂电机驱动电动汽车行驶中状态估计算法。CarSim和Matlab/Simulink联合仿真结果表明,该算法能有效估计轮毂电机驱动电动汽车行驶中的纵向车速、侧倾角、侧倾角速度等状态。     

基于LO-EKF算法的分布驱动电动汽车状态估计的研究

本文中对分布式驱动电动汽车的状态估计进行研究。首先利用龙伯格状态观测器实时观测对车辆的状态估计影响较大的路面坡度,接着,提出了采用扩展卡尔曼滤波算法,以车辆ESP传感器所获取的数据信息作为观测值,对分布式驱动电动汽车的动力学状态变量进行估计。最后进行Carsim和MATLAB联合仿真。结果表明,基于扩展卡尔曼滤波和龙伯格观测器的车辆状态估计算法能较好的估算出车辆的相关动力学状态值,算法可行,收敛速度较快。     

车辆转向与驱动综合控制及横向速度观测器的设计

为了实现复杂工况下车辆自动跟踪控制,建立了纵横向耦合车辆模型,研究了车辆在弯道变速行驶工况的动力学耦合控制问题,根据滑模控制以及动态表面控制理论,提出了一种基于车辆转向与驱动控制的综合控制器,并针对横向车速不可测,设计了横向速度观测器。仿真结果表明该综合控制器具有良好跟踪性能,在复杂工况下表现出较好的动、静态特性。     

基于T-S模糊方法的车辆主动悬架多目标控制研究

为了研究因曲线运动引起的车辆侧翻及防测翻控制方法,提升车辆在不平整道路上的平顺性及紧急避障转向操纵下侧倾稳定性,采用Takagi-Sugeno(T-S)模糊建模方法,设计了主动悬架自适应多目标鲁棒控制策略。分析了基于车辆运动状态的模糊隶属度函数选择方法,当车辆直线行驶或动挠度较小时,保证车辆的行驶平顺性,当车辆发生极限转向或动挠度较大时,限制悬架相对运动量,增强对车身的垂向支撑。以优化加速度H_∞性能及悬架动挠度为控制目标,通过使用并行分布补偿方法将结果优化问题转换为线性矩阵不等式求解问题,确定反馈控制增益。采用自适应鲁棒控制(Aaptive Robust Control-ARC)保证系统在非线性、不确定性下,控制力跟踪的鲁棒性。通过SIMULINK~?及CARSIM~?联合仿真对主动悬架平顺性及侧倾稳定性控制效果进行验证,结果表明:该控制方法可以有效提升在良好路面正常行驶工况下车辆的平顺性,和被动悬架相比,小激励工况下,其加速度峰值降低了70%以上,在大激励下动挠度峰值相比被动悬架降低了15%以上。在随机路面输入下,车辆质心加速度均方根值相较被动悬架降低了4%以上,后轴悬架动挠度峰值降低近20%。当车辆发生侧翻危险工况时,基于T-S Fuzzy的主动悬架可以有效地增加车辆悬架支持力,减小车辆侧倾角,避免车辆发生侧翻。     

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HSRI模型的参数自适应质心侧偏角观测器的设计

首先对全维车速观测器进行降维处理,以减少观测器的在线计算量,并设计了非线性级联车速观测器.接着,对路面附着系数和轮胎侧偏刚度进行参数自适应估计,以提高质心侧偏角的估计精度,并基于HSRI轮胎模型设计了参数自适应非线性质心侧偏角观测器.在估算轮胎侧偏刚度时采用无侧向车速的车辆模型,以避免车辆动力学模型与侧向车速观测器的耦合作用,并引入带双重遗忘因子的递推最小二乘法,以保持算法的修正能力和解除不同估计参数之间误差的耦合作用.最后采用Simulink与Carsim动力学仿真软件进行联合仿真验证,结果表明所设计的参数自适应非线性质心侧偏角观测器是有效的,估计精度满足ESC控制的工程要求.     

Vehicle dynamic estimation with road bank angle consideration for rollover detection: theoretical and experimental studies

This article describes a method of vehicle dynamics estimation for impending rollover detection. This method is evaluated via a professional vehicle dynamics software and then through experimental results using a real test vehicle equipped with an inertial measurement unit. The vehicle dynamic states are estimated in the 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 the rollover detection, a new method is proposed in order to compute the time-to-rollover using the load transfer ratio. The used nonlinear model is deduced from the vehicle lateral dynamics and is represented by a Takagi–Sugeno (TS) fuzzy model. This representation is used in order to take into account the nonlinearities of lateral cornering forces. The proposed TS observer is designed with unmeasurable premise variables in order to consider the non-availability of the slip angles measurement. Simulation results show that the proposed observer and rollover detection method exhibit good efficiency.     

Development of an electric active rollcontrol (ARC) algorithm for a SUV

Cornering maneuvers with reduced body roll and without loss in comfort are leading requirements for car manufacturers. An electric active roll control (ARC) system controls body roll angle with motor-driven actuators installed in the centers of the front and rear stabilizer bars. A vehicle analysis model developed using a CarSim S/W was validated using vehicle test data. Two ARC algorithms for a sports utility vehicle (SUV) were designed using a sliding-mode control algorithm based on a nonlinear roll model and an estimated lateral acceleration based on a linearized roll model. Co-simulation with the Matlab simulink controller model and the CarSim vehicle model were conducted to evaluate the performance of two ARC control algorithms. To validate the ARC performance in a real vehicle, vehicle tests were conducted at KATECH proving ground using a small SUV equipped with two ARC actuators, upper and lower controllers and a few subsystems. From the simulation and vehicle validation test results, the proposed ARC control algorithm for the developed ARC actuator prototypes improves the vehicle’s dynamic performance.     

非满载液罐半挂汽车列车侧向耦合动力学模型

为方便液罐半挂汽车列车（Tractor Semi-trailer Tank Vehicle,TSTTV）罐-车整体的优化设计匹配,综合提高整车的侧倾稳定性、侧向动力学稳定性及操纵特性,基于Lagrange方法和椭圆规摆等效机械液体晃动模型建立TSTTV的整车侧向耦合动力学模型,其典型特征是实现罐内液体侧向晃动与车辆横摆运动、侧向运动、悬挂质量的侧倾运动及非线性侧向轮胎力的集成一体化建模,贯通液体晃动动力学与车辆侧向动力学稳定性之间的联系。通过开环正弦停滞转向输入操作响应对所建立的模型进行分析评价,考察车辆横摆角速度、质心侧偏角、侧倾角、侧向载荷转移率及液体晃动角等状态量在2种充液比（F_L=40%,80%）及2种罐体椭圆率（Δ=1.0,1.3）下的响应。研究结果表明：所建立的TSTTV模型可以实现液体侧向晃动作用下的车辆侧向耦合动力学仿真分析,能够反映充液比、罐体截面椭圆率等运输条件和罐体几何参数对整车侧倾稳定性、侧向动力学稳定性及操纵特性的影响;基于该模型可以针对液体介质、充液比及道路环境等运输条件因素的影响,研究以提高整车侧向动力学稳定性为目标的TSTTV灌-车整体的优化设计匹配问题,这对提升液罐车的设计性能、提高行驶的安全性和运输效率具有重要意义。     

Roll Dynamics of Commercial Vehicles

An analytical model is developed here for studying the roll dynamics of commercial vehicles. Large displacements and rotations are accounted for in this nonlinear model so that it can be used for the study of roll dynamics well beyond the limits of wheel lift-off. The model is used to illustrate some of the dynamic phenomena in vehicle rollover, especially the interactive coupling between the roll and the vertical modes of motion. The influence of suspension backlash on rollover resistance is demonstrated, and the phenomenon of roll motion resonance is illustrated to suggest new means for evaluating vehicle rollover sensitivity.     

Vehicle dynamics and road curvature estimation for lane departure warning system using robust fuzzy observers: experimental validation

This paper describes a new approach to estimate vehicle dynamics and the road curvature in order to detect vehicle lane departures. This method has been evaluated through an experimental set-up using a real test vehicle equipped with the RT2500 inertial measurement unit. Based on a robust unknown input fuzzy observer, the road curvature is estimated and compared to the vehicle trajectory curvature. The difference between the two curvatures is used by the proposed lane departure detection algorithm as the first driving risk indicator. To reduce false alarms and take into account driver corrections, a second driving risk indicator based on the steering dynamics is considered. The vehicle nonlinear model is deduced from the vehicle lateral dynamics and road geometry and then represented by an uncertain Takagi–Sugeno fuzzy model. Taking into account the unmeasured variables, an unknown input fuzzy observer is proposed. Synthesis conditions of the proposed fuzzy observer are formulated in terms of linear matrix inequalities using the Lyapunov method.     

Lateral load transfer and normal forces estimation for vehicle safety: experimental test

Knowledge of vehicle dynamics data is important for vehicle control systems that aim to enhance vehicle handling and passenger safety. This study introduces observers that estimate lateral load transfer and wheel–ground contact normal forces, commonly known as vertical forces. The proposed method is based on the dynamic response of a vehicle instrumented with cheap and currently available standard sensors. The estimation process is separated into three blocks: the first block serves to identify the vehicle’s mass, the second block contains a linear observer whose main role is to estimate the roll angle and the one-side lateral transfer load, while in the third block we compare linear and nonlinear models for the estimation of four wheel vertical forces. The different observers are based on a prediction/estimation filter. The performance of this concept is tested and compared with real experimental data acquired using the INRETS-MA (Institut National de Recherche sur les Transports et leur Sécurité – Département Mécanismes d’Accidents) Laboratory car. Experimental results demonstrate the ability of this approach to provide accurate estimation, thus showing its potential as a practical low-cost solution for calculating normal forces.     

Road curvature estimation for vehicle lane departure detection using a robust Takagi–Sugeno fuzzy observer

In this paper, a lane departure detection method is studied and evaluated via a professional vehicle dynamics software. Based on a robust fuzzy observer designed with unmeasurable premise variables with unknown inputs, the road curvature is estimated and compared with the vehicle trajectory curvature. The difference between the two curvatures is used by the proposed algorithm as the first driving risk indicator. To reduce false alarms and take into account the driver corrections, a second driving risk indicator is considered, which is based on the steering dynamics, and it gives the time to the lane keeping. The used nonlinear model deduced from the vehicle lateral dynamics and a vision system is represented by an uncertain Takagi–Sugeno fuzzy model. Taking into account the unmeasured variables, an unknown input fuzzy observer is then proposed. Synthesis conditions of the proposed fuzzy observer are formulated in terms of linear matrix inequalities using Lyapunov method. The proposed approach is evaluated under different driving scenarios using a software simulator. Simulation results show good efficiency of the proposed method.     

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。     

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.