前照灯电子控制装置种种

为了提高汽车在夜间行驶的速度,确保行车安全,不少汽车上采用了前照灯电子控制装置。常用的前照灯电子控制装置有:前照灯自动变光器、前照灯状态自动调整系统、昏暗自动发光控制系统、前照灯关闭自动延时控制装置。前照灯自动变光器是一种根据对方车辆灯光的亮度自动变远光为近     

一汽大众CC前照灯自适应异常

故障现象:前照灯自适应时,左右两侧前照灯运行模式与正常车辆不同。故障诊断与排除:正常车辆,打开点火开关,开启前照灯,开始进入自适应状态:左右前照灯同时下降后,左右前照灯分别向两侧偏转(左侧前照灯向左偏,右侧前照灯向右偏),然后同时回到原位。车辆在夜间行驶时,左侧前照灯灯光偏左且无法通     

法雷奥已经或即将实用化的汽车新技术

智能化自适应前照灯系统(AFS) 法雷奥智能化自适应前照灯系统能根据车前方道路情况,自动调整前照灯灯光,从而有效提高了汽车行驶安全性。弯道照明是该系统的首要功能,它能根据夜间行驶道路的弯道情况,随时自动调整汽车前灯光束。     

双车道公路平曲线段行车轨迹偏移实验研究

双车道公路弯道处行车轨迹是车辆自由行驶时的重要特征,通过对行车轨迹及运行速度综合效应的分析,得出双车道公路自由行驶的车辆在弯道上行驶时行车轨迹偏移规律,并建立了自由行驶状态下道路线形与行车轨迹和速度之间的相关模型.据此可对弯道处行驶时的驾驶行为及行车安全进行分析,并对道路弯道处线形和断面进行改善.     

智能车路系统中汽车列队行驶控制关键技术与研究进展

通过车路协调技术可以控制车辆实现列队行驶,以提高道路车辆密度,增加道路容量,同时也能增加交通系统的安全性和节约能源.论述了汽车列队行驶控制的关键技术,介绍了车辆纵向、横向自动控制技术、车路信息交互技术以及车队队列控制技术等研究进展,展望汽车列队行驶控制研究方向.     

基于车路协同的车灯自适应控制数学模型研究

为了有效减少夜间弯道中的交通事故,本文提出了基于车路协同的自适应车灯控制系统。以公路的停车视距、弯道曲线长度和弯道曲线转角为基础,建立车灯水平转角与路面情况的数学模型。对该模型进行模拟后,结果表明该系统在国家车路协同技术推广中具有广泛的应用前景。     

汽车AFS照明控制系统设计研究

为解决夜间行车照明带来的困扰,结合汽车电气控制技术上不断创新,文章对传统的汽车AFS照明控制系统设计做出改进,分析控制系统的功能及组成,设计控制系统硬件电路和软件控制程序,实现前照灯自适应智能控制,从而满足驾驶员各种行驶环境的需求。     

雪铁龙C5各电控系统电路图解析(五)——随动转向前照灯系统电路

<正>(接2015年第2期)一、转向前照灯的作用在东风雪铁龙C5轿车上,装备有随动转向前照灯。图1是没有随动转向功能的前照灯照明情况,图2是有随动转向功能的前照灯照明情况。随动转向前照灯的光束具有根据转向盘的转动角度自动调整光束角度的功能,在近光灯或远光灯开启的状态下,汽车转弯时随动转向,使光束紧随行驶道路方向,为转向车辆行进的前方区域提供照明,其可提供双倍的视野照明宽度,大大提高汽     

浓雾天气安全驾驶技巧

<正>一、尽快打开车灯浓雾产生时,能见度降低。此时应尽快减低车速,打开车辆的前照灯及雾灯。这是为了确保我方车辆的驾驶员视野,并告知对向车辆及后方车辆我方车辆的存在。特别需要说明的是:当汽车前照灯向上方照射(远光打开)时,光线的乱反射作用将会影响到驾驶员的视野。因此,请务必将前照灯向下方照射(打开近光)。二、比对道路中线规范行驶     

两种大灯检测仪的异同

为了保证夜间行车的安全．机动车应装备有良好的照明灯具（前照灯）,以便照亮车辆前方的路面．及时发现道路障碍物及其它突发事件。而汽车制造厂出厂质保线的大灯检测仪和汽车检测线的大灯检测仪正是确保车辆前照灯状态良好的有力保证。     

Adaptive Control of Vehicle Suspension

An adaptive control scheme for a two-degree-of-freedom vehicle model with active suspension is proposed. The performance goal is to minimize the variance of vehicle body acceleration under inequality constraints imposed on the variance of either tire or suspension deflection. An active suspension is adapted to the changes in vehicle velocity and the type of road (or terrain) surface which is assumed to be reconstructable from the accelerometer measurements. The control gain factors are obtained by the iterative method taking advantage of stochastic linear control theory. The performance of the system is evaluated and compared to that of an active system with constant gain factors and a passive system with adjustable parameters.     

Adaptive Control of Vehicle Suspension

SUMMARY

An adaptive control scheme for a two-degree-of-freedom vehicle model with active suspension is proposed. The performance goal is to minimize the variance of vehicle body acceleration under inequality constraints imposed on the variance of either tire or suspension deflection. An active suspension is adapted to the changes in vehicle velocity and the type of road (or terrain) surface which is assumed to be reconstructable from the accelerometer measurements. The control gain factors are obtained by the iterative method taking advantage of stochastic linear control theory. The performance of the system is evaluated and compared to that of an active system with constant gain factors and a passive system with adjustable parameters.     

A vehicle ABS adaptive sliding-mode control algorithm based on the vehicle velocity estimation and tyre/road friction coefficient estimations

A sliding-mode observer is designed to estimate the vehicle velocity with the measured vehicle acceleration, the wheel speeds and the braking torques. Based on the Burckhardt tyre model, the extended Kalman filter is designed to estimate the parameters of the Burckhardt model with the estimated vehicle velocity, the measured wheel speeds and the vehicle acceleration. According to the estimated parameters of the Burckhardt tyre model, the tyre/road friction coefficients and the optimal slip ratios are calculated. A vehicle adaptive sliding-mode control (SMC) algorithm is presented with the estimated vehicle velocity, the tyre/road friction coefficients and the optimal slip ratios. And the adjustment method of the sliding-mode gain factors is discussed. Based on the adaptive SMC algorithm, a vehicle's antilock braking system (ABS) control system model is built with the Simulink Toolbox. Under the single-road condition as well as the different road conditions, the performance of the vehicle ABS system is simulated with the vehicle velocity observer, the tyre/road friction coefficient estimator and the adaptive SMC algorithm. The results indicate that the estimated errors of the vehicle velocity and the tyre/road friction coefficients are acceptable and the vehicle ABS adaptive SMC algorithm is effective. So the proposed adaptive SMC algorithm can be used to control the vehicle ABS without the information of the vehicle velocity and the road conditions.     

Level and attitude control of the active suspension system with integral and derivative action

A 7-DOF full-car model with optimal active control suspension is utilized to evaluate the vehicle dynamic performances which are achieved through proposed controllers. The optimal controller, which includes the integral action for the suspension deflection, considerably improves the attitude control of a vehicle because the rolling and pitching motion in cornering and braking maneuvers are reduced, respectively. In the viewpoint of level control, the integral control acting on the suspension deflection results in the zero steady-state deflection in response to static body forces and ramp road input. The dynamic characteristics of the suspension control system are evaluated in terms of time domain and frequency domain. The simulations in the time domain demonstrate the advantages of the active suspension system obtained by penalizing the integral and derivative of suspension deflections and the derivative of roll and pitch angles in the performance index. The frequency characteristic curves obtained by simulations regarding integral action or derivative action show the increase of both ride comfort and road-holding performances by maximizing the use of suspension deflections. The potential of derivative control is shown by the performances of the car traveling over a bump and braking.     

Level and attitude control of the active suspension system with integral and derivative action

A 7-DOF full-car model with optimal active control suspension is utilized to evaluate the vehicle dynamic performances which are achieved through proposed controllers. The optimal controller, which includes the integral action for the suspension deflection, considerably improves the attitude control of a vehicle because the rolling and pitching motion in cornering and braking maneuvers are reduced, respectively. In the viewpoint of level control, the integral control acting on the suspension deflection results in the zero steady-state deflection in response to static body forces and ramp road input. The dynamic characteristics of the suspension control system are evaluated in terms of time domain and frequency domain. The simulations in the time domain demonstrate the advantages of the active suspension system obtained by penalizing the integral and derivative of suspension deflections and the derivative of roll and pitch angles in the performance index. The frequency characteristic curves obtained by simulations regarding integral action or derivative action show the increase of both ride comfort and road-holding performances by maximizing the use of suspension deflections. The potential of derivative control is shown by the performances of the car traveling over a bump and braking.     

Towards connected autonomous driving: review of use-cases

Connected autonomous vehicles are considered as mitigators of issues such as traffic congestion, road safety, inefficient fuel consumption and pollutant emissions that current road transportation system suffers from. Connected autonomous vehicles utilise communication systems to enhance the performance of autonomous vehicles and consequently improve transportation by enabling cooperative functionalities, namely, cooperative sensing and cooperative manoeuvring. The former refers to the ability to share and fuse information gathered from vehicle sensors and road infrastructures to create a better understanding of the surrounding environment while the latter enables groups of vehicles to drive in a co-ordinated way which ultimately results in a safer and more efficient driving environment. However, there is a gap in understanding how and to what extent connectivity can contribute to improving the efficiency, safety and performance of autonomous vehicles. Therefore, the aim of this paper is to investigate the potential benefits that can be achieved from connected autonomous vehicles through analysing five use-cases: (i) vehicle platooning, (ii) lane changing, (iii) intersection management, (iv) energy management and (v) road friction estimation. The current paper highlights that although connectivity can enhance the performance of autonomous vehicles and contribute to the improvement of current transportation system performance, the level of achievable benefits depends on factors such as the penetration rate of connected vehicles, traffic scenarios and the way of augmenting off-board information into vehicle control systems.     

基于LQR控制的现代客车自适应空气悬架

长期在不良工况的道路上驾驶会降低驾驶员的乘坐舒适性。随着人们对乘坐舒适性需求不断提升,空气弹簧的优势尤为明显。文章提出了一种基于LQR控制策略的自适应空气悬架系统的创新设计方案,提出的LQR控制器采用粒子群算法进行优化。以客车空气悬架为研究对象,采用MATLAB软件对空气悬架系统的被动和自适应动力学模型进行了设计和仿真。仿真结果表明,自适应空气悬架系统在保证车辆稳定性的同时,降低了车辆在随机道路上的最大位移幅值,从而提高了车辆的平顺性。     

汽车主动悬架的单神经元自适应控制

在1/4汽车动力学模型的基础上,设计了汽车主动悬架的自适应神经元控制器。以车辆的行驶平顺性为主要控制目标,车身垂直加速度、悬架动挠度、车轮动位移为具体评价参数,研究了系统在随机路面激励条件下的时域响应,计算了振动响应的均方根值,考察了在变参数条件下控制器的鲁棒性。仿真结果表明,该控制器能有效改善车辆的综合性能,尤其是平顺性和舒适性,并且具有较好的鲁棒性,对模型参数的变化有一定的适应性。     

Using the lead vehicle as preview sensor in convoy vehicle active suspension control

Both ride quality and roadholding of actively suspended vehicles can be improved by sensing the road ahead of the vehicle and using this information in a preview controller. Previous applications have used look-ahead sensors mounted on the front bumper to measure terrain beneath. Such sensors are vulnerable, potentially confused by water, snow, or other soft obstacles and offer a fixed preview time. For convoy vehicle applications, this paper proposes using the overall response of the preceding vehicle(s) to generate preview controller information for follower vehicles. A robust observer is used to estimate the states of a quarter-car vehicle model, from which road profile is estimated and passed on to the follower vehicle(s) to generate a preview function. The preview-active suspension, implemented in discrete time using a shift register approach to improve simulation time, reduces sprung mass acceleration and dynamic tyre deflection peaks by more than 50% and 40%, respectively. Terrain can change from one vehicle to the next if a loose obstacle is dislodged, or if the vehicle paths are sufficiently different so that one vehicle misses a discrete road event. The resulting spurious preview information can give suspension performance worse than that of a passive or conventional active system. In this paper, each vehicle can effectively estimate the road profile based on its own state trajectory. By comparing its own road estimate with the preview information, preview errors can be detected and suspension control quickly switched from preview to conventional active control to preserve performance improvements compared to passive suspensions.     

Cooperative control of the motor and the electric booster brake to improve the stability of an in-wheel electric vehicle

A cooperative control algorithm for an in-wheel motor and an electric booster brake is proposed to improve the stability of an in-wheel electric vehicle. The in-wheel system was modeled by dividing it into motor and mechanical parts, and the electric booster brake was modeled through tests. In addition, the response characteristics of the in-wheel system and the electric booster brake were compared through a frequency response analysis. In the cooperative control, the road friction coefficient was estimated using the wheel speed, motor torque, and braking torque of each wheel, and the torque limit of the wheel to the road was determined using the estimated road friction coefficient. Based on the estimated road friction coefficient and torque limit, a cooperative algorithm to control the motor and the electric booster brake was proposed to improve the stability of the in-wheel electric vehicle. The performance of the proposed cooperative control algorithm was evaluated through a hardware-in-the-loop simulation (HILS). Furthermore, to verify the performance of the proposed cooperative control algorithm, a test environment was constructed for the anti-lock braking system (ABS) hydraulic module hardware, and the performance of the cooperative control algorithm was compared with that of the ABS by means of a HILS test.