线控转向系统的主动转向控制策略研究

线控转向系统取消了转向盘和转向轮之间的机械连接,可以对前轮进行主动转向控制以增强操纵稳定性和主动安全性.通过使前轮线控转向系统的期望横摆角速度跟踪稳态质心侧偏角为0的四轮转向车辆的横摆角速度,设计线控转向系统的变传动比,主动控制前轮转角.通过时域响应、转向增益、开环总方差等指标对其进行了性能分析.结果表明:采用提出的主动转向控制策略时稳态质心侧偏角大大降低,开环总方差大大降低,从而提高了汽车的操纵稳定性.     

线控转向系统全状态反馈控制策略的研究

为了根据车况和驾驶员喜好实现最优的操纵特性(不足转向、过度转向和中性转向),需要主动控制前轮转角.线控转向系统利用车辆全状态(横摆角速度和质心侧偏角)反馈控制策略优化驾驶员的转向输入,主动控制前轮转角来优化车辆的转向特性,高速时具有适当的不足转向特性,低速时具有适当的过度转向特性,从而在反应快速和安全性之间很好的权衡.其中通过状态观测器估计侧偏角.结果表明,在紧急操纵时可以代替驾驶员协调使车辆保持稳定,正常操纵时补偿物理参数或操纵条件的变化而保持操纵特性的一致.     

基于模糊控制的汽车直接横摆力矩研究

为防止汽车产生测滑,针对汽车直接横摆力矩控制,提出了横摆角速度与质心侧偏角联合控制的模糊控制方法.横摆力矩控制采用分层控制方法,设计了模糊控制器和规则制动力分配方法.模糊控制器根据期望值和车辆状态决策出所需的附加横摆力矩,并通过规则制动力分配方法进行主动差动制动实现.采用Matlab/Simulink与CarSim联合仿真对控制方法进行了仿真验证.结果表明:横摆角速度与质心侧偏角联合控制的横摆力矩模糊控制方法使汽车能够较好地跟踪期望,有效提高汽车极限工况下的行驶稳定性.     

主动前轮独立转向系统分析与研究

为了提高车辆的操稳性,提出了新型主动前轮独立转向系统,介绍了主动前轮独立转向的工作原理和结构形式,建立了系统数学模型;提出了主动前轮独立转向的控制策略,上层控制器采用PI控制,由横摆角速度偏差得出总控制转角,下层控制器负责内外侧转向轮的判断以及计算内外侧转向轮具体的转角;在仿真软件MATLAB/Simulink里进行了控制策略有效性仿真,仿真结果说明对于不足转向车辆,主动前轮独立转向系统能比传统的主动前轮转向系统更有效地提高车辆操纵稳定性。     

四轮线控转向系统的转向控制策略研究

为了控制汽车的质心侧偏角,同时保持汽车的转向增益不变,研究了四轮线控转向系统的后轮转向控制策略和前轮转向控制策略.首先建立了四轮转向整车二自由度模型,然后基于稳态质心侧偏角为零得到两种后轮转向控制策略:与前轮转角成比例型和横摆角速度反馈型,前者不改变系统极点,后者改变系统极点.基于转向增益不随车速改变得到二者的前轮转向控制策略.仿真表明,提出的前轮转向控制策略可以保持固定转向增益,降低驾驶员负担;后轮转向控制策略可以实现零质心侧偏角稳态值,控制车辆姿态,改善操纵稳定性.     

提高车辆安全性的输出反馈自适应控制

研究含有时变参数的车辆动力学模型的输出跟踪控制问题.控制目标是使车辆的横摆角速度和质心侧偏角分别跟踪理想的设定值,通过反推方法设计输出反馈自适应控制器.控制器的输出为主动横摆力矩,通过控制主动横摆力矩来控制车辆的输出响应跟踪理想的输出信号,从而提高车辆的安全性.仿真结果表明,该控制器能更好地适应车速和路况的变化,鲁棒性强.     

轮毂驱动电动车辆动力学稳定性滑模控制策略研究

为了提高轮毂驱动电动车辆的操纵稳定性,理论分析了车辆横摆角速度和质心侧偏角对于车辆稳定性的影响.设计了基于滑模变结构控制理论和直接横摆力矩控制的双层控制器.在Carsim中搭建了四轮轮毂电机驱动车辆仿真实验平台,并进行了Carsim/Simulink联合仿真,在标准换道工况下,分别验证了基于质心侧偏角的滑模变结构控制和基于横摆角速度的滑模变结构控制策略的效果,验证了双层车辆稳定性控制策略的有效性和稳定性.     

智能四轮转向车辆稳定车道线保持串级控制

为实现四轮前后轮转向车辆的稳定车道线保持控制,提出集成直接横摆力矩和车道线保持的串级控制策略.主控制器实现车道线保持前轮转角控制.副控制器实现车辆稳定性控制.主控制器基于MPC(model predictive control)算法控制车辆前轮转角,通过调整前轮转角使得横向位置偏差和航向角偏差最小.主控制器的车辆前轮转角作为副控制器的输入,计算期望滑移角和期望横摆率.车辆后轮转角和横摆力矩作为副控制器控制输入,基于LQ(linear quadratic)算法计算补偿车辆后轮转角和横摆力矩,实际车辆滑移角和实际横摆率跟踪期望滑移角和期望横摆率.车辆的前轮转角、后轮转角和横摆力矩作为控制输入,在副控制器实现车辆稳定性控制基础上,主控制器实现准确地车道线保持控制,保证智能车辆在车道内自主安全行驶.仿真结果表明,该串级控制策略的有效性,提高了智能车辆车道线跟踪的准确性,也提高车辆的稳定性和操纵性.     

采用2-自由度调节器结构的制动方向稳定性控制算法

结合直接横摆力矩控制和主动前轮转向控制,设计了一种提高制动方向稳定性的复合控制系统.控制器采用2-自由度调节器结构,将前轮转向角视为输入,将作用于车身的外部侧向干扰力视为扰动,通过2-自由度调节器将转向跟随控制和抗扰控制分离,并对制动控制参数进行了优化.文章对有转向输入和路面突变情况下的控制器控制性能进行了仿真研究,并与无方向稳定控制的仿真结果进行了对比.仿真试验证实这种控制方法在提高车辆制动稳定性方面有良好的效果.     

汽车电子稳定程序模糊控制仿真

关于汽车安全和稳定性问题,针对汽车电子稳定程序(Electronic stability program,ESP)是一种主动安全系统.为了提高汽车在转向工况下的侧向稳定性,采用快速控制原型的方法,建立了基于H.B.Pacejka 轮胎模型的三自由度整车模型和车辆参考模型.选取车辆横摆角速度和质心侧偏角作为综合控制变量,设计了模糊控制器,并对某款车型进行了离线仿真和在线实时仿真.结果表明,设计的控制器可以很好的控制汽车的横摆角速度和质心侧偏角.改进后的方法可以提高控制系统的实时性和稳定性,为ESP的快速开发提供了参考依据.     

Yaw Moment Control Strategy for Four Wheel Side Driven EV

When four wheel side driven EV travals in steering or changes lanes in high speed, the vehicle is easy to side-slip or flick due to the difference of wheel hub motor and a direct effect of vehicle nonlinear factors on vehicle yaw motion, which would affect vehicle handling and stability seriously. To solve this problem, a joint control strategy, combined with the linear programming algorithm and improved sliding mode algorithm, which combines the exponential reaching law and saturation function was proposed. Firstly, the vehicle dynamics model and the reference model according with the structure and driving characteristics of four wheel side driven EV were set up. Then, introduced the basic method of the improved sliding mode variable structure control and complete the sliding mode variable structure controller design basic on vehicle sideslip angle and yaw velocity.The controller accomplish optimal allocation of vehicle braking force through a linear programming algorithm, according to yaw moment produced by the vehicle motion state. Single lane driving simulation results show that the proposed control strategy can not only control vehicle sideslip angle and yaw velocity well, but also accomplish good controlling of the vehicle yaw moment, so as to significantly improve the handling and stability of vehicle.     

An MPC-based manoeuvre stability controller for full drive-by-wire vehicles

Aiming at the actuator time delay caused by the drive-by-wire technology, a novel manoeuvre stability controller based on model predictive control is proposed for full drive-by-wire vehicles. Firstly, the future vehicle dynamics are predicted by a two-degree-of-freedom vehicle model with input delay. Secondly, in order to prevent the vehicle from destabilizing due to excessive side slip angles, the determined ideal yaw rate and side slip angle are tracked simultaneously by optimizing the front wheel angle and additional yaw moment. Moreover, in order to improve the trajectory tracking ability, a side slip angle constraint determined by phase plane stability boundaries is added to the cost function. The results of Matlab and veDYNA co-simulation show that the regulated yaw rate can track the reference value well and the side slip angle decreases. Meanwhile, the trajectory tracking ability is improved obviously by compensating the time delay.     

基于模糊控制的分布式电动车辆横摆力矩研究

为提高多轮分布式电驱动车辆在不同工况下的操纵稳定性,设计了一种基于直接横摆力矩控制的分层控制策略。上层以横摆角速度和质心侧偏角为控制变量,采用模糊控制进行目标运动状态跟踪,决策出所需要的横摆力矩。下层按设计的规则进行转矩分配。应用TruckSim和Matlab/Simulink建立车辆和控制器模型,分别在高、低附着等工况下进行联合仿真。仿真结果表明,设计的模糊控制方法能对车辆目标状态进行良好跟踪,相较于无控制状态能够提高车辆的操纵稳定性。     

Integrated vehicle dynamics management for distributed‐drive electric vehicles with active front steering using adaptive neural approaches against unknown nonlinearity

This paper proposes a new integrated vehicle dynamics management for enhancing the yaw stability and wheel slip regulation of the distributed‐drive electric vehicle with active front steering. To cope with the unknown nonlinear tire dynamics with uncertain disturbances in integrated control problem of vehicle dynamics, a neuro‐adaptive predictive control is therefore proposed for multiobjective coordination of constrained systems with unknown nonlinearity. Unknown nonlinearity with unmodeled dynamics is modeled using a random projection neural network via adaptive machine learning, where a new adaptation law is designed in premise of Lyapunov stability. Given the computational efficiency, a neurodynamic method is extended to solve the constrained programming problem with unknown nonlinearity. To test the performance of the proposed control method, simulations were conducted using a validated vehicle model. Simulation results show that the proposed neuro‐adaptive predictive controller outperforms the classical model predictive controller in tracking nominal wheel slip ratio, desired vehicle yaw rate and sideslip angle, showing its significance in vehicle yaw stability enhancement and wheels slip regulation.     

A New Approach for Vehicle Lateral Velocity and Yaw Rate Control with Uncertainty

In order to attain excellent stability and maneuverability to ensure safety and ride‐comfort, the lateral velocity and yaw rate of a vehicle are expected to be controlled at any desired values simultaneously. A basic manipulation model of a vehicle with two degrees of freedom which requires two independent control inputs (front and rear steering angle) is constructed. In this model, we consider the mass and the moment of inertia of the vehicle are the uncertain parameters which are (possibly) fast‐varying. However, no further information, except that the uncertainties are bounded, is assumed. Furthermore, the bound is unknown. An adaptive robust control methodology based on the Udwadia and Kalaba approach which guarantees uniform boundedness and uniform ultimate boundedness is proposed to drive the system to follow the pre‐specified constraints approximately. The adaptive law is of leakage type which can adjust itself based on the tracking error. The numerical simulation results conducted by MATLAB demonstrate the ease and effectiveness of implementation.     

Disturbance Observer Based Control for Four Wheel Steering Vehicles With Model Reference

This paper presents a disturbance observer based control strategy for four wheel steering systems in order to improve vehicle handling stability. By combination of feedforward control and feedback control, the front and rear wheel steering angles are controlled simultaneously to follow both the desired sideslip angle and the yaw rate of the reference vehicle model. A nonlinear three degree-of-freedom four wheel steering vehicle model containing lateral, yaw and roll motions is built up, which also takes the dynamic effects of crosswind into consideration. The disturbance observer based control method is provided to cope with ignored nonlinear dynamics and to handle exogenous disturbances. Finally, a simulation experiment is carried out, which shows that the proposed four wheel steering vehicle can guarantee handling stability and present strong robustness against external disturbances.      

后轴双电机扭矩矢量控制研究

车辆的横摆响应受到转向系统、悬架系统、制动系统及驱动系统影响,传统车辆主要以转向输入进行主动控制,随着线控底盘的发展,ESC、后轮转向、扭矩矢量等技术逐步参与到车辆横摆的主动控制中;相对于ESC以制动力差产生横摆力矩,扭矩矢量可在不降低总驱动力的前提下产生横摆力矩,不会引起车辆的制动效应;通过后轴双电机扭矩矢量控制（TVC）产生主动横摆力矩,旨在改善车辆横摆响应,TVC采用前馈与反馈结合控制,基于二自由度车辆模型、目标稳态增益K及横摆角速度-速度修正因子K1建立目标横摆角速度;利用车辆模型逆函数计算横摆力矩前馈值,PID计算横摆力矩反馈值,总横摆力矩转换得到左右车轮纵向力调整量;纵向力调整量与驱动力分量叠加获得左右轮总纵向力;左右轮驱动力过大时可能会受到滑移率、电机扭矩等限制,为保证横摆力矩偏差在要求范围内,需要根据限制情况对左右轮纵向力进行调整;通过仿真验证,TVC可明显改变车辆横摆响应     

四轮转向车辆操纵稳定性仿真分析

对四轮转向车辆的转向特性进行了理论分析,并对某控制策略的四轮转向车辆为例进行了仿真.建立了四轮转向车辆操纵动力学模型,分析了前轮角阶跃输入下四轮转向车辆的稳态响应和瞬态响应与传统前轮转向车辆的主要区别;在四轮转向车辆状态方程的基础上二求解出横摆角速度和侧向加速度与前轮转角的传递函数,与前轮转向车辆对比分析了传递函数零、极点位置对响应特性的影响.借助Matlab/Simulink,对四轮转向车辆进行仿真,发现仿真结果与理论分析吻合.将仿真结果与前轮转向车辆进行比较,阐明了四轮转向车辆的性能优势.研究结果可为评价四轮转向车辆的系统设计提供理论依据.     

汽车操纵稳定性的自适应控制策略研究

针对汽车系统的非线性和参数不确定性,设计了一种“前馈+反馈”自适应神经模糊控制器,通过ESP和AFS的协调控制来提高汽车操纵稳定性.ESP反馈控制器采用模糊控制策略,以横摆角速度和质心侧偏角为控制目标;AFS前馈控制器采用径向基神经网络控制,以反馈控制器的输出作为误差进行学习,从而实现自适应控制.仿真结果表明,上述控制策略是可行和有效的,能显著改善汽车在高速或湿滑路面上的操纵稳定性.