汽车自适应巡航跟车多目标鲁棒控制算法设计

为满足自适应巡航系统跟车模式下的舒适性需求并且兼顾车辆安全性,基于模型预测控制原理提出一种多目标鲁棒跟车控制算法.建立考虑前车加速度干扰的自适应巡航系统车间纵向运动学模型,该模型可全面反映系统的动态演化规律,提高模型的精度和可靠性;针对自适应巡航系统需求进行目标分析,设计一种考虑舒适性和安全性的多目标模型预测控制算法;针对模型预测控制算法鲁棒性较差的问题,引入修正项反馈,提高控制系统鲁棒性,采用向量约束管理法解决模型预测控制算法硬约束造成的控制系统无优化解问题.仿真结果表明:该算法使跟车时车辆加速度及冲击度保持在舒适性范围,同时车间距始终大于最小安全距离,兼顾了舒适性和安全性要求,实现了自适应巡航控制系统跟车目的.     

基于人类驾驶员在跟车高风险情景中的经验轨迹数据优化智能网联车辆纵向控制模型参数（英文）

智能网联车辆(CAV)具有提高驾驶安全性的巨大潜力,CAV的基本性能评估准则之一是其能否在真实的交通情景中比人类驾驶员更安全地行驶。本研究提出了一种基于人类驾驶员在跟车高风险情景中的经验轨迹数据来优化CAV纵向控制模型参数的方法。首先,从经验轨迹数据中提取初始跟车车组(I-CFP)。然后,基于模型默认参数值,采用自适应巡航控制模型(ACC)和协同自适应巡航控制模型(CACC)进行仿真,生成模拟跟车车组(S-CFP)的原始轨迹。最后,应用遗传算法来优化ACC和CACC模型的控制参数,并生成优化后的跟车车组(O-CFP)轨迹。结果表明,S-CFP的安全性优于I-CFP,而O-CFP具有最佳的安全性能。ACC/CACC模型中的优化参数多样且与默认参数不同,表明最佳模型参数会随跟车情景不同而变化,进而为减少追尾碰撞风险提供了有价值的视角。     

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。     

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...     

用于自适应巡航控制的汽车纵向动力学模型的建立

为了实现汽车自适应巡航控制(ACC)的目的,在已有制动系模型的基础上,引入发动机二状态模型,给出了驱动与制动的切换标准,建立了汽车纵向动力学模型,并以Santana轿车参数为例建立了模拟仿真程序,对ACC典型工况进行了仿真。仿真结果表明:模型可实现ACC的控制目的,驱动与制动可顺利切换。     

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。     

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.     

行进中车辆防追尾碰撞的临界安全车距研究

日益增多的交通事故已成为严重的社会问题,降低交通事故的损失和伤害有待解决.车辆在行驶中,前车采取减速行驶操作或出现障碍物等,为了防止发生追尾,后车驾驶员会做出相应的驾驶行为的改变.为了提高车辆在高速行驶状态下的主动安全性能,研究了处于追尾行驶状态的前乍与后乍的运动学特征.针对前车的不同运动状态分别推导出跟车距离的临界安全车距的计算公式,并以此为依据进行了有关论述.     

基于驾驶人风险响应机制的人机共驾模型

提出了一种根据驾驶人对环境风险的实时响应进行控制权切换的智能汽车人机共驾模型。首先,从基于真实道路信息的highD数据集中提取出跟车和并道两类典型驾驶片段。接着,应用行车风险场理论对驾驶片段中的环境风险进行统一量化。然后,通过拟合环境风险作用与驾驶人的行驶加速度,得到安全风险响应策略曲面,并提出了基于策略偏差的人机共驾控制权柔性切换模型(FCTM)。最后,以纵向控制模型(LCM)作为辅助控制模型,在前车紧急制动和旁车切入两类危险场景中进行了人机共驾仿真实验。结果表明:本文FCTM模型可以通过平稳的人机控制权切换,修正驾驶人在危险场景中的驾驶操作,提高行驶安全性。     

基于扩张状态观测器估计的混合动力汽车协调控制

为了提高功率分流式混合动力汽车模式切换的稳定性,提出干扰补偿的转矩协调控制策略. 针对发动机动态响应振荡及车辆行驶工况多变的问题,设计多变量线性扩张状态观测器,从频域角度验证了观测器对于上述2种干扰的估计精确性. 研究不同干扰对基础电机补偿控制稳定性的影响,指出负载干扰对车辆模式切换响应的影响最大,引起的切换冲击最大可至24.5 m/s³. 提出基于干扰补偿的动力源转矩再分配算法,开展仿真验证. 结果表明,该协调控制策略在受到明显的外界干扰时能够保证系统的稳定性及模式切换的平顺性.     

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.     

基于数据驱动的鲁棒反步自适应巡航控制

为了实现高精度的鲁棒自适应巡航控制（ACC）,提出基于数据驱动的鲁棒反步自适应巡航控制算法. 利用反步技术设计虚拟控制器,将车辆间距控制转化为速度控制,避免速度相关型间距策略带来的间距与速度控制耦合;构建基于数据的耦合滑模面并设计状态观测器,补偿车辆复杂的非线性动力学特性、离散误差及外部干扰,提升控制算法的鲁棒性;利用反馈控制及鲁棒控制技术设计数据驱动的ACC鲁棒控制算法;分别选取固定时间间距、变时间间距策略,利用所提ACC算法及基于比例积分（PI）的ACC算法进行车辆自适应巡航控制对比仿真验证. 对比实验结果表明,所提算法在控制精度、鲁棒性方面具有优越性.     

Control allocation algorithm for over-actuated electric vehicles

A control allocation algorithm based on pseudo-inverse method was proposed for the over-actuated system of four in-wheel motors independently driving and four-wheel steering-by-wire electric vehicles in order to improve the vehicle stability. The control algorithm was developed using a two-degree-of-freedom(DOF) vehicle model. A pseudo control vector was calculated by a sliding mode controller to minimize the difference between the desired and actual vehicle motions. A pseudo-inverse controller then allocated the control inputs which included driving torques and steering angles of the four wheels according to the pseudo control vector. If one or more actuators were saturated or in a failure state, the control inputs are re-allocated by the algorithm. The algorithm was evaluated in Matlab/Simulink by using an 8-DOF nonlinear vehicle model. Simulations of sinusoidal input maneuver and double lane change maneuver were executed and the results were compared with those for a sliding mode control. The simulation results show that the vehicle controlled by the control allocation algorithm has better stability and trajectory-tracking performance than the vehicle controlled by the sliding mode control. The vehicle controlled by the control allocation algorithm still has good handling and stability when one or more actuators are saturated or in a failure situation.     

Combined Control Allocation and Sliding Mode Control in the Dynamic Control of a Vehicle with Eight In-Wheel Motors

An eight wheel independently driving steering (8WIDBS) electric vehicle is studied in this paper. The vehicle is equipped with eight in-wheel motors and a steer-by-wire system. A hierarchically coordinated vehicle dynamic control (HCVDC) system, including a high-level vehicle motion controller, a control allocation, an inverse tire model and a lower-level slip/slip angle controller, is proposed for the over-actuated vehicle system. The high-level sliding mode vehicle motion controller is designed to produce desired total forces and yaw moment, distributed to longitudinal and lateral forces of each tire by an advanced control allocation method. And the slip controller is designed to use a sliding mode control method to follow the desired slip ratios by manipulating the corresponding in-wheel motor torques. Evaluation of the overall system is accomplished by sine maneuver simulation. Simulation results confirm that the proposed control system can coordinate among the redundant and constrained actuators to achieve the vehicle dynamic control task and improve the vehicle stability.     

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.     

面向汽车运行工况设计的马氏链非等长交叉进化算法

为解决马尔科夫链和传统遗传算法设计汽车运行工况时效率低、质量差的问题,提出用于设计汽车运行工况的马氏链非等长交叉进化方法.设计子代满足马尔科夫链转移关系的非等长交叉算子,解除等位等长交叉段的限制,使遗传算法更好地适用于汽车运行工况的设计.根据试验数据,应用马氏链非等长交叉进化方法构建非等长初始种群,使用满意准则模型和指数加权平均数设定目标函数,设计三参数汽车运行工况.随机生成3种不同长度的三参数高速公路代表性工况.分析结果表明,期望运行工况与原始数据库特征参数的相对偏差均在设定范围内,速度和加速联合分布相关系数均高于90%,生成工况具有代表性.相比于马尔科夫链和传统遗传算法相结合的设计方法,马氏链非等长交叉进化方法的平均运行工况生成效率提高了66%,运行工况质量更优.     

Nonlinear Derivative and Integral Sliding Control for Tracked Vehicle Steering with Hydrostatic Drive

In the steering process of tracked vehicle with hydrostatic drive,the motion and resistance states of the vehicle are always of uncertain and nonlinear characteristics,and these states may undergoe large-scale changes. Therefore,it is significant to enhance the steering stability of tracked vehicle with hydrostatic drive to meet the need of future battlefield. In this paper,a sliding mode control algorithm is proposed and applied to achieve desired yaw rates. The speed controller and the yaw rat...     

自适应巡航控制新方法

为提高汽车高速行驶的交通安全 ,提出一种新的基于目标安全车距的自适应巡航控制(ACC)方法 .它仅通过调节辅助节气门开度和驱动轮制动力矩即可实现 .论述了测距传感器的选择 ,目标安全车距、目标减速度的确定和实现 ,给出了ACC逻辑框图 ,进行了仿真分析 .探讨了误报现象及其排除方案 .仿真结果表明 ,这种控制方法是简单可行的 ,易于和ABS/ASR形成ABS/ASR/ACC集成化系统