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.     

分布式电动车差动驱动与差动制动协调控制

针对分布式驱动电动车稳定性控制问题，提出了一种差动驱动与差动制动协调控制策略。基于模糊控制理论设计的模糊控制器计算附加横摆力矩，并通过二自由度车辆模型计算横摆角速度和质心侧偏角的期望值。基于最优控制中的二次规划理论计算出每个车轮的力矩。选取蛇形和双移线的典型实验工况，通过MATLAB/Simulink与CarSim联合仿真对控制算法进行验证。结果表明：差动驱动与差动制动协调控制策略能够有效提高汽车操纵稳定性和行驶安全性。可见，所提出的控制策略有效可行。     

智能车辆视觉导航横向模糊控制策略仿真研究

针对智能车辆视觉导航横向控制中存在的适应性问题,提出了一种基于横摆角速度与横向偏差的智能车辆横向模糊控制策略。根据车辆于车道内的位置状态信息,建立了横摆角速度预测模型、7自由度车辆操纵动力学模型以及横向模糊推理模型。仿真结果表明,与常规位置偏差控制策略相比较,采用横向模糊控制策略不仅能提高智能车辆横向控制的精确性,并且具有很好的鲁棒性和自适应性。     

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。     

汽车动力学HiL仿真实验平台的搭建及应用

为了便于汽车研发工作,减少开发周期,搭建了基于实时仿真系统xPC-Target的汽车动力学硬件在环仿真实验平台.根据高精度车辆动力学仿真软件veDYNA的Light车辆模型构架,自主开发了红旗HQ430型轿车车辆模型,并嵌入了方向盘、油门踏板、制动踏板和51单片机等硬件实物.最后采用51单片机作为硬件控制器,设计了基于PID控制算法的车辆横摆稳定性控制策略.针对驾驶员在高速紧急转向、低附着路面连续转向和对开路面转向等极限工况,进行了硬件在环仿真实验.实验结果表明,该硬件在环实验平台可以反应汽车动力学特性,能够在线的验证横摆稳定性控制算法的实时性及有效性.     

四轮轮毂电动汽车横摆角速度自抗扰控制

汽车的横摆角速度对汽车稳定性和安全性有较大影响,针对汽车行驶控制时的抗干扰能力,目前还没有特别有效的汽车横摆角速度控制策略;创新性设计了基于自抗扰控制理论的用于四轮轮毂电动汽车横摆角速度的高性能控制策略;首先分析了汽车横摆角速度控制的动态模型,并通过数学变换,将其转换为二阶自抗扰控制器被控对象的标准形式;再设计双层控制结构,包括直接横摆力矩制定层和转矩分配层;在直接横摆力矩制定层,利用二阶自抗扰控制器计算出控制汽车横摆角速度所需的附加横摆力矩;在转矩分配层,设计了转矩分配算法,利用附加横摆力矩得到4个车轮的指令转矩,进而控制电动汽车横摆角速度;最后,通过Matlab/Simulink和汽车动力学仿真软件CarSim联合仿真验证了所设计控制策略的有效性。     

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.     

分布式驱动电动车行驶稳定性控制建模与仿真

针对分布式驱动电动车的行驶稳定性控制问题,利用CarSim和MATLAB/Simulnk软件建立模型并搭建联合仿真平台。设计稳定性控制算法,包括横摆力矩控制、转矩协调控制和驱动防滑控制。以车辆横摆角速度和质心侧偏角作为控制变量,运用滑模变结构控制方法,设计横摆力矩控制器。通过转矩分配算法,对单个车轮施加驱动或制动力,产生稳定横摆力矩,并建立模糊控制器对车轮滑转率进行控制。在仿真平台完成了双移线工况的仿真,结果表明,该算法能提高车辆行驶稳定性。     

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.     

基于信息融合技术的车辆行驶状态估计

针对车辆行驶状态估计问题,基于扩展卡尔曼滤波(EKF)理论设计了汽车横摆角速度、质心侧偏角和纵向车速的估计算法.建立了车辆非线性三自由度估算模型,应用扩展卡尔曼滤波对纵向加速度、侧向加速度和方向盘转角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.选择高速双移线工况,通过CarSim与Matlab/Simulink联合仿真对算法进行仿真验证.结果表明:算法能够准确估计车辆的横摆角速度、质心侧偏角和纵向车速,并具有良好的实时性.     

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.     

四轮独立驱动电动汽车单轮失效稳定性控制

为了解决四轮独立驱动电动汽车驱动系统失效时的转矩分配问题,提出了一种基于规则的驱动力控制分配策略以保证车辆在出现单轮失效情况下的稳定性和动力性.控制器采用双层控制,包括上层控制和下层控制.在上层控制中,根据驾驶员的输入与车辆状态,采用滑模控制理论计算出控制横摆角速度和质心侧偏角的附加横摆力矩.在下层控制中,根据驱动电机...     

横摆力矩和主动前轮转向结合的车辆横向稳定性模糊控制仿真

提出一种基于横摆力矩和主动前轮转向相结合的车辆横向稳定性控制方法,以横摆角速度和侧偏角为控制目标,利用前馈补偿和模糊控制产生横摆力矩和附加的前轮转角,通过控制制动力的分配以及对转向角的修正,使车辆转向行驶时的横摆角速度和侧偏角很好地跟踪参考模型.对转向轮阶跃输入和正弦输入两种工况分别进行了仿真研究,采用横摆力矩和主动前轮转向相结合控制方法,车辆转向时的瞬态及稳态响应优于单独的横摆力矩控制,表明该方法能有效地控制车辆横摆角速度和侧偏角,提高车辆转向时的横向稳定性,同时能有效地减轻驾驶员操纵负担.     

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.      

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.     

四轮驱动电动汽车稳定性预测控制器快速实现

为解决四轮驱动电动汽车在高速情况下易发生甩尾失控的安全性问题,针对整车和执行器间的动力学耦合、控制系统非线性、多变量、实时性等问题,本文采用集中式的控制策略,设计了一种车辆横摆稳定的快速非线性预测控制器,实现了整车横摆稳定和电机转矩分配的一体化控制.为了控制系统的实时实现,将非线性规划问题转化为代数方程组求解,通过解耦预测时域间方程组的耦合关系,实现时域间优化问题的并行求解,提高了控制器的计算速度.最后给出了控制器的硬件并行加速实验,完成了控制系统的硬件在环实验,实现了车辆横摆稳定系统的实时控制.实验结果表明该控制器不仅具有良好的控制性能,而且明显提升了系统实时性.     

对开路面制动车辆稳定性的控制方法及仿真

汽车在对开路面上紧急制动是汽车制动非常恶劣的一种工况.文中分析了车辆在对开路面上制动的稳定性问题并提出了相应的解决办法,根据简化车辆模型建立了相应状态空间方程,采用最优控制方法解决车辆稳定性问题.结合制动车辆的ABS(防抱制动系统),调整相应车轮的目标滑移率,通过对车辆的横摆力矩控制和相应的车轮滑移率和附着系数的调节使车辆保持制动稳定性,从而可以在不增加硬件成本的条件下完成车辆的稳定性控制.对车辆在对开路面的制动工况进行了仿真,结果表明,所提出的方法能有效改善对开路面上车辆的制动稳定性.     

汽车横摆的动态模型

建立横摆动态模型是汽车横摆稳定控制的基础．本文根据汽车横摆稳定控制的特点,综合车身横摆动态,车轮动态和轮胎的非线性特性,建立了非线性离散横摆动态模型,其中轮胎摩擦力为时变参数．为了估计本模型中的时变参数,本文进而设计了离散滑模估计器估计轮胎摩擦力．最后,在一个高精度的汽车动力学仿真环境中,证实了本估计方法可有效地估计车轮摩擦力,所建立模型较为准确地反映汽车横摆动态．     

MPC-based compensation control system for the yaw stability of distributed drive electric vehicle

Conventional yaw stability strategy of distributed drive electric vehicle (DDEV) is usually realised by torque distribution strategy. However, the instantaneous variations of four independent tyres slip ratio and the effect of disturbance have not been considered sufficiently. Therefore, it is difficult to realise the robustness of yaw stability for DDEV under various operating conditions. To solve this problem, a novel model predictive controller-based compensation control system (MPC-CCS) is proposed in this paper. The proposed MPC-CCS consists of two parts, an MPC based-feedback controller and a Kalman filter based-feedforward controller. In the feedback controller, a dual torque distribution scheme is adopted to obtain optimal torque values derived from the real-time signals of four independent tyres slip ratio, an MPC is designed to realise optimal torque values for vehicle yaw motion. In the feedforward controller, a Kalman filter is employed to attenuate the effect of the disturbance on yaw performance. In this way, the robustness of yaw stability for DDEV can be guaranteed by the proposed MPC-CCS. The proposed MPC-CCS is evaluated on eight degrees of freedom simulation platform and simulation results of different conditions show the effectiveness of the MPC-CCS.