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。     

基于改进的Sage-Husa自适应扩展卡尔曼滤波的车辆状态估计EI北大核心CSCD

本文中提出了一种基于改进的Sage-Husa自适应扩展卡尔曼滤波的车辆行驶状态估计算法。首先建立了非线性3自由度车辆估算模型和Dugoff轮胎模型。接着通过对纵向加速度、侧向加速度、横摆角速度和转向盘转角等低成本传感器信号的信息融合,实现对车辆行驶状态的准确估计。最后应用CarSim和Matlab/Simulink联合仿真对算法进行验证。结果表明:基于改进的Sage-Husa自适应扩展卡尔曼滤波的估计算法能比扩展卡尔曼滤波算法更准确、稳定地估计车辆行驶状态。     

基于改进的Sage-Husa自适应扩展卡尔曼滤波的车辆状态估计

本文中提出了一种基于改进的Sage-Husa自适应扩展卡尔曼滤波的车辆行驶状态估计算法。首先建立了非线性3自由度车辆估算模型和Dugoff轮胎模型。接着通过对纵向加速度、侧向加速度、横摆角速度和转向盘转角等低成本传感器信号的信息融合,实现对车辆行驶状态的准确估计。最后应用CarSim和Matlab/Simulink联合仿真对算法进行验证。结果表明:基于改进的Sage-Husa自适应扩展卡尔曼滤波的估计算法能比扩展卡尔曼滤波算法更准确、稳定地估计车辆行驶状态。     

基于强跟踪容积卡尔曼滤波的车辆行驶状态估计

针对车辆行驶过程中的状态估计问题,提出了基于强跟踪容积卡尔曼滤波的车辆行驶状态估计算法。建立了采用Dugoff轮胎模型非线性3自由度车辆估算模型,通过对纵向加速度、侧向加速度、横摆角速度、转向盘转角和车轮轮速低成本传感器信号的信息融合以实现对车辆行驶状态的准确估计。应用驾驶员模拟器进行在环试验结果表明,基于强跟踪容积卡尔曼滤波的估计算法能够较准确地对车辆行驶状态进行估计。     

转向盘转角阶跃输入下半挂汽车列车操纵稳定性仿真分析

基于包括任意载荷分布的非线性轮胎模型在内的半挂汽车列车整车模型,应用汽车列车动力学仿真软件Arc Sim,分析了半挂汽车列车在转向盘转角阶跃输入时的转向特性。通过在不同车速、不同结构参数等条件下的仿真计算,揭示了半挂汽车列车的转向特性与车速、结构参数之间的内在联系,给出了半挂汽车列车转向特性在这些条件下的表现特征,为半挂汽车列车操纵稳定性分析提供了参考和借鉴。     

汽车四轮转向非线性系统的神经网络控制

考虑了轮胎的非线性特性，引入Magic Formula建立汽车非线性力学模型，利用前向BP神经网络来辨识该非线性模型，并利用另一个神经网络进行PID参数的整定，进行离散控制系统和控制算法的设计，有效地提高了汽车四轮转向的稳定性。     

汽车响应分析方法的探讨

本文将精细积分算法推广应用到考虑轮胎非线性的驾驶员－汽车－道路闭环系统的运动微分方程组的求解，推广后的算法原则上可用来求在计算机精度范围内的精确解，以转向盘角阶跃为例进行了非线性的仿真计算，对汽车的动态运动特性进行了分析。     

轮胎非稳态转向特性非线性仿真模型

本文以轮与路面之间的滑移速度为出发点，在稳态指数统一模型的基础上，建立了轮胎非稳态转向特性非线性仿真模型。在实验研究中，发现了动态过程回正力臂和附加的回正力矩的滞后特性。仿真和试验结果对比表明，该模型足以反映轮胎非线性转向特性，可用于前轮及汽车操纵动力学仿真方面的研究。     

悬架系统与转向梯形机构的协调设计

建立了汽车双横臂独立悬架与转向梯形机构的非线性空间运动学模型,在此基础上提出一种有效的分析方法,通过求解非线性方程组可以获得梯形机构和整个悬架系统及车轮上的任意一点在空间的运动轨迹,进而探讨了悬架系统与转向梯形机构的协调设计问题。     

基于小波和粒子群算法的HEV行驶状况辨识方法研究

针对混合动力汽车(HEV)行驶状况(道路坡度和整车载荷)变化难以有效识别,导致驱动系统控制策略不能有效满足驾驶员意图问题,以混联式HEV为研究对象,提出了基于小波滤波和粒子群算法的HEV行驶状况辨识方法。首先建立了汽车行驶状况辨识模型,采用最小二乘法确立了优化目标函数,其次研究了基于小波滤波和粒子群算法的HEV行驶状况辨识原理,最后进行了行驶状况粒子群智能算法辨识试验。在采集实车数据的基础上,对实车数据进行小波滤波,并运用行驶状况辨识方法对道路坡度和整车载荷进行了辨识,并对辨识结果进行小波滤波,结果表明,试验工况下整车载荷辨识的相对误差绝对平均值为2.71%,道路坡度辨识的相对误差绝对平均值为3.85%,验证了所提出方法的有效性。     

4WS汽车操纵稳定性建模和仿真研究

从改善汽车操纵稳定性角度出发,全面考虑轮胎载荷、转向系等对四轮转向汽车操纵稳定性的影响,建立4WS（4 Wheel Steering System）整车操纵稳定模型。并用Matalab/simulink进行了模拟仿真研究。比较性地研究汽车在低速和高速时控制方式的特点和不同之处。本模型为4WS汽车设计改进优化提供一种手段和方法,同时,为4WS汽车理论研究和试验校核提供了参考。     

Nonlinear PI front and rear steering control in four wheel steering vehicles

Vehicle steering dynamics show resonances, which depend on the longitudinal speed, unstable equilibrium points and limited stability regions depending on the constant steering wheel angle, longitudinal speed and car parameters.

The main contribution of this paper is to show that a combined decentralized proportional active front steering control and proportional-integral active rear steering control from the yaw rate tracking error can assign the eigenvalues of the linearised single track steering dynamics, without lateral speed measurements, using a standard single track car model with nonlinear tire characteristics and a non-linear first-order reference model for the yaw rate dynamics driven by the driver steering wheel input. By choosing a suitable nonlinear reference model it is shown that the responses to driver step inputs tend to zero (or reduced) lateral speed for any value of longitudinal speed: in this case the resulting controlled vehicle static gain from driver input to yaw rate differs from the uncontrolled one at higher speed. The closed loop system shows the advantages of both active front and rear steering control: higher controllability, enlarged bandwidth for the yaw rate dynamics, suppressed resonances, new stable cornering manoeuvres, enlarged stability regions, reduced lateral speed and improved manoeuvrability; in addition comfort is improved since the phase lag between lateral acceleration and yaw rate is reduced.

For the designed control law a robustness analysis is presented with respect to system failures, driver step inputs and critical car parameters such as mass, moment of inertia and front and rear cornering stiffness coefficients. Several simulations are carried out on a higher order experimentally validated nonlinear dynamical model to confirm the analysis and to explore the robustness with respect to unmodelled dynamics.     

Nonlinear PI front and rear steering control in four wheel steering vehicles

Vehicle steering dynamics show resonances, which depend on the longitudinal speed, unstable equilibrium points and limited stability regions depending on the constant steering wheel angle, longitudinal speed and car parameters.

The main contribution of this paper is to show that a combined decentralized proportional active front steering control and proportional-integral active rear steering control from the yaw rate tracking error can assign the eigenvalues of the linearised single track steering dynamics, without lateral speed measurements, using a standard single track car model with nonlinear tire characteristics and a non-linear first-order reference model for the yaw rate dynamics driven by the driver steering wheel input. By choosing a suitable nonlinear reference model it is shown that the responses to driver step inputs tend to zero (or reduced) lateral speed for any value of longitudinal speed: in this case the resulting controlled vehicle static gain from driver input to yaw rate differs from the uncontrolled one at higher speed. The closed loop system shows the advantages of both active front and rear steering control: higher controllability, enlarged bandwidth for the yaw rate dynamics, suppressed resonances, new stable cornering manoeuvres, enlarged stability regions, reduced lateral speed and improved manoeuvrability; in addition comfort is improved since the phase lag between lateral acceleration and yaw rate is reduced.

For the designed control law a robustness analysis is presented with respect to system failures, driver step inputs and critical car parameters such as mass, moment of inertia and front and rear cornering stiffness coefficients. Several simulations are carried out on a higher order experimentally validated nonlinear dynamical model to confirm the analysis and to explore the robustness with respect to unmodelled dynamics.     

Vehicle dynamics integrated control for four-wheel-distributed steering and four-wheel-distributed traction/braking systems

In this article, vehicle dynamics integrated control algorithm using an on-line non-linear optimization method is proposed for 4-wheel-distributed steering and 4-wheel-distributed traction/braking systems. The proposed distribution algorithm minimizes work load of each tire, which is controlled to become the same value. The global optimality of the convergent solution of the recursive algorithm can be proved by extension to convex problems. This implies that theoretical limited performance of vehicle dynamics integrated control is clarified. Furthermore, the effect of this vehicle dynamics control for the 4-wheel-distributed steering and 4-wheel-distributed traction/braking systems is demonstrated by simulation to compare with the combination of the various actuators.     

五轴转向重型汽车转向性能的研究

以多体系统动力学理论为基础,利用ADAMS建立了五轴转向重型汽车的整车虚拟样机模型,对该模型进行了仿真分析.由分析结果可知,转向轮转角越大,轮胎磨损越严重.为提高重型汽车的灵活性,延长轮胎的使用寿命,对该模型进行了优化.通过仿真分析可知,优化后的转向性能明显提高.同时分析比较了五轴转向重型汽车与前两轴转向重型汽车的转向性能,结果表明,五轴转向重型汽车转弯半径小,轮胎磨损小.     

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MPC的分布式驱动越野车辆原地转向控制研究

针对轮毂电机分布式驱动越野车辆在狭小空间快速机动的需求,设计了一种分层结构的原地转向控制策略。基于动力学原理分析了各轮载荷、附着条件对原地转向横摆速度的影响机理,并搭建原地转向运动学模型,上层采用模型预测控制算法设计原地转向理想轨迹以及期望的横摆角速度,开发基于PI滑模控制的横摆运动跟踪算法,通过补偿转向横摆力矩以提高方向角控制的鲁棒性和稳定性,下层以最优轮胎利用率为目标,设计二次规划算法优化分配各轮附加横摆力矩。dSPACE硬件在环测试结果表明,所提出的控制算法可在保证稳定性的前提下实现原地转向,大幅提高了车辆的转向机动性,在方向盘动态输入仿真中,车辆最大转弯半径为0.157 m,转向中心的最大偏移量为3.610 m;同时,驾驶员能对转向过程进行闭环控制,实现了原地转向过程中横摆速度的实时调节。     

汽车主动悬架与电动助力转向系统多目标优化及集成控制

建立了整车主动悬架和电动助力转向系统动力学模型,构建线性控制的主动悬架和PD控制的电动助力转向系统集成控制器,应用遗传算法对集成控制系统的结构参数和控制参数进行多目标优化。结果表明,经过多目标优化后的集成控制系统,既可保证车辆操纵轻便性,又显著提高了整车操纵稳定性、安全性和行驶平顺性。