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为实现商用车线控转向,设计一套新的线控转向系统架构及其转角跟踪控制算法。新的线控转向系统采用丝杠螺母结构中的丝杠直接控制纵拉杆,螺母通过带轮机构被电机驱动。对线控转向系统结构进行运动学分析,推导转向系统可变传动比,采用前轮转角为状态变量,建立线控转向系统二阶动力学模型。基于转角跟踪目标,采用反步控制算法,设计线控转向系统转角跟踪控制器,通过反馈系统线性化处理系统参数不确定和环境干扰问题,实现准确的目标转角跟踪,并建立李雅普诺夫函数,证明了采用反步控制的线控转向系统是渐进稳定的。搭建采用“丝杠螺母+带轮机构”架构的线控转向实车底盘测试台架,选取蛇形和混合工况进行控制算法验证。研究结果表明:与滑模控制算法的测试结果对比可知,反步控制算法绝对平均跟踪误差值降低了71.88%~79.57%,跟踪误差标准偏差值降低了71.32%~78.50%;线控转向系统反步控制转角跟踪算法能够减少系统收敛到原点的时间,抑制系统的抖振,提高车辆线控转向系统转角跟踪的操纵灵活性。  相似文献   
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This paper presents a new steer-by-wire concept using an all-wheel drive vehicle layout with in-wheel motors while completely omitting the application of any dedicated steering device. Steering is based on the so-called differential steering principle which generates the necessary steering moment about the kingpins by a traction force difference between left and right sides of the vehicle. In order to investigate the behaviour of the vehicle and to design the underlying control algorithms, a planar vehicle model is presented, where the vehicle is described as constrained non-holonomic system requiring a special treatment. A state feedback linear controller for controlling of the lateral dynamics of the vehicle at higher speeds and a simple PI angle controller for low-speed manoeuvring are developed. The resulting behaviour of the system is investigated by various simulation experiments demonstrating a comparable steering performance of the new steering concept as that of conventional passenger cars.  相似文献   
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底盘线控技术是实现商用车自动驾驶和辅助驾驶功能的关键基础技术,是当今汽车行业的研发热点。底盘线控技术包括线控执行系统和线控集成控制技术两大部分。分别对商用车的线控转向、线控制动、线控悬架、线控驱动和线控换挡等线控执行系统,以及自动紧急制动 (Autonomous Emergency Braking,AEB) 系统、自适应巡航 (Adaptive Cruise Control,ACC) 系统和车道保持辅助 (Lane Keeping Assist,LKA) 系统等线控集成控制技术的构成、控制原理与研究应用现状进行了概述,重点分析了商用车各类构型的线控转向和线控制动系统及其应用场景。结合最新发布的国家智能底盘技术路线框架图和商用车未来的客户需求,给出了商用车线控底盘各技术方向的发展趋势,为商用车线控底盘技术发展提供了参考。  相似文献   
4.
For steer-by-wire systems, the steering feedback must be generated artificially due to the system characteristics. Classical control concepts require operating-point driven optimisations as well as increased calibration efforts in order to adequately simulate the steering torque in all driving states. Artificial neural networks (ANNs) are an innovative control concept; they are capable of learning arbitrary non-linear correlations without complex knowledge of physical dependencies. The present study investigates the suitability of neural networks for approximating unknown steering torques. To ensure robust processing of arbitrary data, network training with a sufficient volume of training data is required, that represents the relation between the input and target values in a wide range. The data were recorded in the course of various test drives. In this research, a variety of network topologies were trained, analysed and evaluated. Though the fundamental suitability of ANNs for the present control task was demonstrated.  相似文献   
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汽车线控转向技术的现状与发展趋势   总被引:15,自引:1,他引:14  
随着汽车工业与电子工业的不断发展,越来越多的线控类技术正在取代汽车传统的机械装置。汽车线控转向系统由于取消了转向盘和转向轮之间的机械连接装置,彻底摆脱了传统转向系统所固有的弊端,便于和其他系统集成、统一协调控制。描述了线控转向系统的转向盘系统、电子控制系统和转向系统等组成,介绍了线控转向系统的工作原理和主要特点,阐述了线控转向系统的关键技术在于传感器技术、总线技术、动力电源、容错控制技术等,总结了线控转向技术今后良好的应用前景,展望了其研究发展趋势。  相似文献   
6.
A steer-by-wire system, which has no mechanical constraints between steering wheel and front wheel, is expected to improve steering performance. The mechanical resistance torque is not transmitted from the front wheel to the steering wheel, and it is essential to simulate the torque around the steering wheel for better human-machine interface. Previous studies investigated resistance torque control originating from vehicle behaviour variables such as yaw rate and lateral acceleration. However, other variables such as steering wheel angle and front wheel actuation force are also good candidate sources to generate resistance torque. In this paper, first, four general guidelines are introduced to evaluate three types of resistance torques, i.e., the steering wheel angle origin, the steering force origin and the vehicle behaviour origin. First two guidelines are for ‘driver-made’ phase to make a turn, while the third guideline is for ‘vehicle-made’ phase to return to straight driving and the fourth one is the applicability guideline. Satisfaction of these guidelines by each of the three resistance torques is examined by the actual vehicle experiment. A necessity of combining these three types of resistance torques is indicated as a future subject.  相似文献   
7.
为了解决传统固定转向传动比以及鲁棒H控制方法无法很好地改善车辆稳定性的问题,提出全轮线控转向车辆的变传动比和可拓H控制策略。首先,建立八自由度车辆动力学模型和轮胎模型。其次,以车辆方向盘转角和车速为输入信息,基于模糊控制方法设计全轮线控转向车辆的转向传动比,并计算出全轮线控转向车辆的前轮转角。然后,以横摆角速度偏差和偏差微分为特征值,基于可拓控制理论将车辆状态划分为3个区域:经典域、可拓域和非域;在经典域中,采用基于横摆角速度反馈的鲁棒H控制方法,实时获取全轮线控转向车辆的后轮转角;在可拓域和非域中,结合可拓控制和H控制策略,动态调整H控制器的输出信号,在保证控制系统鲁棒性的前提下改善车辆的操纵稳定性。最后,基于MATLAB/Simulink仿真平台和自主研制的全轮线控转向特种消防救援车辆,通过正弦转向、单移线、阶跃转向、双移线等典型工况对所提控制方法进行验证,并以平均绝对误差和均方根误差为评价指标,与无控制和H控制方法进行对比分析。仿真和试验测试结果表明:①变传动比控制方法不仅可以提高车辆低速时的转向灵敏度,也能改善车辆高速时的稳定性;②相比传统鲁棒H控制,可拓H控制策略提高了全轮线控转向车辆的操纵稳定性,改善了车辆全轮线控转向控制系统的鲁棒性。  相似文献   
8.
This study discusses the control effects of the steer-by-wire (SBW) system for motorcycles on the lane-keeping performance by examining computer simulation with a rider-vehicle system which consists of a simplified vehicle model, a rider control model and the controller of the SBW system. The SBW system, which compensates the rolling angle deviation between the desired rolling angle intended by the rider and the actual rolling angle, improves the lane-keeping performance of the rider-vehicle system under the steering torque disturbance. The SBW system is, on the other hand, not effective in the lane-keeping performance under the lateral force disturbance. In addition, the lane-keeping assistance (LKA) system is applied to the SBW system and the cooperativeness of the SBW and the LKA systems is examined. The LKA system improves the lane-keeping performance of the SBW system under not only the steering torque disturbance but also the lateral force disturbance.  相似文献   
9.
线控转向系统通过线控化、智能化可以实现个性驾驶、辅助驾驶、无人驾驶等目标,是智能网联汽车落地的关键技术,其相关动力学控制技术更是影响线控转向系统整体性能的核心技术.该文介绍了线控转向系统的基本结构类型及其动力学建模,分别对线控转向系统的路感控制技术、稳定性控制技术、容错控制技术等关键技术进行了全面概述,分析了线控转向技...  相似文献   
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