自主网联车辆时滞反馈预测巡航控制

考虑车联网环境下的车辆自适应巡航控制问题,提出一种针对前车信息传输存在有界长时延的自主车辆时滞反馈预测巡航控制策略.首先建立自主网联车辆自适应巡航系统的增量控制时滞模型,再考虑车辆行驶安全性、舒适性和燃油经济性等指标,结合滚动优化原理定义时滞反馈预测巡航控制器.进一步,利用Lyapunov稳定性定理和线性矩阵不等式技术...     

车辆多模式多目标自适应巡航控制

为增强量产ACC对前车驾驶意图的预判与自适应能力,发展了一种多目标自适应巡航控制算法,建立闭环纵向跟驰模型。基于模型预测控制理论,综合协调巡航过程中驾驶员期望响应、跟驰安全性、车辆自身物理限制等控制目标,并引入松弛向量以确保滚动在线优化存在可行解。采用待优化目标与控制输入权重调校以及控制器工作域边界松弛的策略,将ACC系统划分出6种工作模式,同时采用模糊推理与加速度加权平均策略,以实现工作模式最佳匹配与平稳过渡。仿真结果表明,多模式设计策略与多目标控制算法能够一定程度上提升ACC系统的适应性与友好性。     

考虑驾驶员行驶特性的双模式自适应 巡航控制设计

为了设计一个能够模拟驾驶员行驶行为的汽车自适应巡航控制(ACC)系统,通过分析驾驶员的日常行驶特性,在模型预测控制的框架基础上提出一个双模式的自适应巡航控制策略：当远离前车时,ACC系统采取快速接近模式,在满足安全舒适的前提下以尽量短的时间减小两车间距;一旦车间距调整至期望值附近时,ACC系统切换到平稳跟车模式,使车辆安全、平稳、舒适地对前车进行跟车;为使2种模式切换时能平滑过渡,利用模糊理论设计了2个模式的切换规则来模拟驾驶员的决策过程.通过仿真试验,证实了该双模式ACC控制策略在满足行驶过程中的安全性以及舒适性的同时,有效地反映了驾驶员的日常行驶习惯,更易于被驾驶员接受,有利于提高ACC系统的使用率.     

汽车自适应巡航线性参变间距控制算法

为满足驾驶员对汽车自适应巡航控制系统的个性化安全车间距设计的需求,采用H∞理论设计了线性参变间距控制算法。考虑到驾驶员自主设定车头时距带来的控制系统动态不确定性问题,采用线性参变模型描述本车与前车间的相对运动学特性,并通过加速度限值抑制了控制输入饱和且改善了乘坐舒适性。基于H∞控制理论并根据时距动态变化实现了对控制器参数的实时调整和汽车纵向动力学的非线性控制。典型仿真工况及其与动态面控制算法的性能对比性分析表明,本文算法可实现驾驶员对车头时距的个性化设定,同时也避免了时距和车辆状态离散变化甚至跳变带来的瞬态跟随性能恶化。     

混有CACC车辆和ACC车辆的混合交通流驾驶舒适性

为了探索协同自适应巡航控制(cooperative adaptive cruise control,CACC)车辆对交通系统的潜在影响,分析了CACC车辆市场普及过程中存在的CACC车辆、自适应巡航控制(adaptive cruise control,ACC)车辆与人工驾驶车辆混合交通流驾驶舒适性.应用加州伯克利PATH实车验证的ACC模型和CACC模型进行数值仿真实验,采用国际ISO-2631-1标准评价混合交通流舒适性,并对ACC和CACC期望车间时距进行参数敏感性分析.最后,从交通流稳定性的角度,对舒适性仿真结果进行了讨论.结果表明:随着CACC市场率的增加,舒适性呈现先恶化、再逐渐提升的趋势.较大的ACC车间时距有利于抑制舒适性的恶化程度,CACC车辆对舒适性的提升作用不受其车间时距取值的影响.混合交通流稳定性定性地决定了舒适性的变化趋势,人工车辆安装车车通信设备,有助于舒适性的逐渐提升.     

基于DMPC的多车协同自适应巡航控制研究

针对多车协同自适应巡航控制系统(CACC)中车辆跟驰距离波动大的问题,提出了一种分布式模型预测控制(DMPC)策略。采用分层控制的思想对CACC系统进行控制。控制器分为上位控制器和下位控制器。上位控制器根据车队状态计算车辆的期望加速度,下位控制器根据期望加速度控制车辆的节气门开度和制动系统压力。首先,建立了车队的纵向动力学模型。其次,根据控制目标设计目标函数,使车队能够获得当前时刻的最优控制量。然后基于逆发动机模型和逆制动模型设计了下位控制器。最后,通过Carsim和MATLAB/Simulink的联合仿真,验证了所设计控制策略的有效性。结果表明,DMPC可以减小车辆跟驰距离误差的峰值、标准差和均方根值,提高跟驰稳定性。     

面向再生制动优化的电动车自适应巡航控制策略

为了提高纯电动车自适应巡航系统的经济性,提出面向再生制动优化的自适应巡航控制策略.分析前轴驱动纯电动车再生制动系统特性,设计自适应巡航(ACC)模式下制动力分配策略.基于该策略得到车速、制动强度与回收能量的关系.以回收能量作为经济性优化指标,将设计跟随性、安全性、舒适性作为自适应巡航优化指标,利用模型预测控制(MPC)理论构建并优化自适应巡航控制策略.将策略在Matlab/Simulink和CarSim平台下仿真,与未优化的控制策略对比验证.结果表明,该策略满足了自适应巡航跟随性、安全性、舒适性的要求,相较于未优化算法,能量回收率提高5.6%.     

自主车辆高效多目标预测巡航控制

考虑自主车辆自适应巡航控制(ACC)多目标优化及快速计算问题,提出了一种高效多目标预测巡航控制算法。首先采用阶梯式控制策略减少模型预测控制在线计算量,参数化预测时域内的控制输入变化量;接着利用(MPC)中QP问题的特殊结构,将变量进行适当重组,使用改进后的内点法来提高系统计算性能,进一步减小计算负担;最后,将该算法应用于本车车辆ACC系统,仿真结果与传统MPC进行了对比,验证了算法的有效性和实用性。     

基于风险评估的自主车辆主动避障预测控制

针对自主车辆的主动避障问题,提出一种基于模型预测控制的车辆轨迹规划与跟踪控制方法.为了评估道路结构及不同障碍物对自主车辆的影响,分析不同障碍物的特性并引入风险评估函数.首先,将风险评估函数加入模型预测控制的优化目标函数中,同时考虑车辆动力学特性、车辆物理约束、燃油经济性及舒适性要求;其次,定义自主车辆紧急避障最小转向点...     

智能电动车辆横纵向协同运动控制

针对车速变化下的车辆轨迹跟随稳定性问题,提出一种基于模型预测控制（MPC）与滑模控制结合的横纵向协同控制策略。建立描述车辆纵向、横向及横摆运动状态的三自由度动力学模型;然后,设计模型预测控制器对车辆期望轨迹进行跟踪,考虑车辆行驶运动过程中横纵向耦合问题,将纵向车速作为横向控制系统的状态量,并利用反馈矫正机制不断更新预测模型;在此基础上,采用滑模控制算法对期望车速及加速度进行跟踪,并采用饱和函数作为指数趋近率以减小抖振;采用基于规则的制动转矩分配方式得到行驶过程中各个车轮的需求转矩。该控制策略考虑了车辆动力学中的横纵向耦合问题,可在线处理车辆动力学约束,将车辆稳定跟踪期望轨迹的问题转化为求解带约束的最优控制问题。仿真结果表明所提出控制策略的有效性。     

行星式混合动力客车的模型预测动态协调控制

行星式混合动力客车在驱动模式切换时会产生较大冲击度,以往基于PID的控制器在模式切换过程中无法有效保证车辆驾驶平顺性.基于此问题,利用模型预测控制(Model Predictive Control,MPC)可以在线滚动优化获得最优控制序列的特点,提出了一种基于MPC的动态协调控制方法,实现发动机的启动控制.依据整车动力学方程和实车历史数据,在Matlab/Simulink平台中搭建基于数据驱动的发动机模型和车辆闭环仿真模型,并将发动机启动过程视为受约束的多目标优化问题,根据系统状态空间方程和优化问题设计基于数据驱动的模型预测控制器,在纯电动模式向混合动力模式切换过程中,与传统基于PID的控制方法以及被动切换展开对比.仿真结果表明,在保证车辆动力性的前提下,相比于PID控制方法和被动切换,在模式切换过程中,基于MPC的动态协调控制方法不仅可以实现发动机的正常启动,还能大幅度降低峰值冲击度,同时使车辆良好地跟随目标车速.本文提出的模型预测控制器可以降低整车冲击度,保证车辆模式切换时的平顺性.     

Longitudinal Control Strategy f or Vehicle Adaptive Cruise Control Systems

A new longitudinal control strategy for vehicle adaptive cruise control (ACC) systems is presented. The running relationship between the ACC vehicle and the detected target vehicle is described by the relative velocity and the deviation between the actual headway distance and the prescribed safety distance. Based on this, two state space models are built and the linear quadratic optimal control theory is used to yield desired velocity for the ACC-equipped vehicle when with the target vehicle detected. By switching among four control modes, the desired velocity profile is designed to deal with different running situations. A velocity controller, which includes a PID controller for throttle openness and a neural network controller for brake application, is developed to achieve the desired velocity profile. The proposed control strategy is applied to a non-linear vehicle model in a simulation environment and is shown to provide the ACC vehicle comfortable ride and satisfying safety.     

基于最优预瞄加速度决策的汽车自适应巡航控制系统

从驾驶员操作汽车的行为特性建模的角度出发,将驾驶员建模理论———稳态预瞄动态校正假说应用于汽车自适应巡航控制系统的理论研究中,构建了基于驾驶员最优预瞄加速度模型的车辆ACC系统结构。并在此基础上建立了相应的ACC系统控制算法。理论分析与仿真计算结果表明:基于驾驶员操纵行为特性的分析,应用驾驶员操纵行为建模理论来研究汽车ACC系统的理论过程为车辆ACC系统的开发提供了一个可行的研究途径。     

基于遗传算法权值优化的汽车悬架最优模糊控制

结合车辆非线性主动悬架系统数学模型,首先设计出悬架系统的线性二次型整定（LQR）最优控制器,其中控制器的加权系数利用遗传算法优化搜索获得,然后设计悬架系统的模糊控制器,进而开展LQR最优控制、模糊控制以及两者并联结合的复合控制方法对比研究．利用遗传算法对加权系数进行搜索优化,可有效解决传统LQR控制器加权系数不易确定的问题．该复合控制方法可获得相比单一控制方法更优的悬架系统控制效果,在车辆不同行驶工况条件下,能进一步降低车身垂直振动加速度、悬架动挠度和轮胎形变,明显提高了汽车的行驶平顺性和操纵稳定性．     

Research on Directly Adaptive Fuzzy Algorithm Based ACC Controller

A directly adaptive fuzzy algorithm is applied in vehicle adaptive cruise control system. The basic principle of the adaptive fuzzy algorithm is analyzed. The initial value of the fuzzy based vector is given by the traditional fuzzy membership. Adaptive law of the adjustable parameters θ is also determined. The directly adaptive fuzzy ACC controller is designed based on Matlab fuzzy toolbox. Matlab-Simulink is adopted to test the function of the adaptive fuzzy ACC controller. The control system is established using a 7 DOF vehicle dynamics model. Simulation results indicate that the principle of the method is correct and it performs well both in cruise and distance keeping.     

Vehicle Active Damping Control with Considering Time Delay

A model predictive control (MPC) based active damping controller for automotive driveline oscillations with time-delay consideration is proposed.A simplified driveline model considering time delay is modeled and converted to a linear parameter varying state space equation.Based on the model and model predictive control theory,an active damping controller is designed for drivability and comfortability improvement.In order to verify the designed controller,a driveline with engine is modeled to simulate the tip-in/out driving operation.An MPC active damping controller without considering time delay is simulated together with the proposed controller.The simulation results show that,by adopting the new MPC active damping controller,the vibration of the vehicle is reduced and the drivability and comfortability are improved.     

Investigation on full vehicle height control algorithm using feedback linearization method

Aiming to improve the control accuracy of the vehicle height for the air suspension system, deeply analyzing the processes of variable mass gas thermodynamics and vehicle dynamics, a nonlinear height control model of the air suspension vehicle was built. To deal with the nonlinear characteristic existing in the lifting and lowering processes, the nonlinear model of vehicle height control was linearized by using a feedback linearization method. Then, based on the linear full vehicle model, the sliding model controller was designed to achieve the control variables. Finally, the nonlinear control algorithm in the original coordinates can be achieved by the inverse transformation of coordinates. To validate the accuracy and effectiveness of the sliding mode controller, the height control processes were simulated in Matlab, i.e., the lifting and lowering processes of the air suspension vehicle were taken when vehicle was in stationary and driving at a constant speed. The simulation results show that, compared to other controllers, the designed sliding model controller based on the feedback linearization can effectively solve the "overshoot" problem, existing in the height control process, and force the vehicle height to reach the desired value, so as to greatly improve the speed and accuracy of the height control process. Besides, the sliding mode controller can well regulate the roll and pitch motions of the vehicle body, thereby improving the vehicle''s ride comfort.     

Multi-constrained model predictive control for autonomous ground vehicle trajectory tracking

A multi-constrained model predictive control (MPC) algorithm for trajectory tracking of an autonomous ground vehicle is proposed and tested in this paper. First, to simplify the computation, an active steering linear error model is applied in the MPC controller. Then, a control increment constraint and a relaxing factor are taken into account in the objective function to ensure the smoothness of the trajectory, using a softening constraints technique. In addition, the controller can obtain optimal control sequences which satisfy both the actual kinematic constraints and the actuator constraints. The circular trajectory tracking performance of the proposed method is compared with that of another MPC controller. To verify the trajectory tracking capabilities of the designed controller at different desired speed, the simulation experiments are carried out at the speed of 3m/s, 5m/s and 10m/s. The results demonstrate the MPC controller has a good speed adaptability.