自适应巡航控制系统的设计及硬件在环仿真

为提高自适应巡航控制系统模式切换平稳性,并对算法的实时性和稳定性进行硬件在 环仿真测试。首先基于最优控制和逆纵向车辆动力学模型设计了由上、下位控制器组成的自适应巡航控制系统,其次采用 dSPACE 公司 SCALEXIO 实时仿真模拟器搭建硬件在环仿真平台,最后对典型自适应巡航控制工况进行控制器硬件在环仿真测试。测试结果表明,硬件在 环测试平台运行良好,适合自适应巡航控制器的开发和测试,并可以进一步地应用于其他驾驶辅助系统;当目标车辆信息跳变、目标车辆行驶速度变化时,设计的自适应巡航控制器可 以适应复杂多变的交通场景,实现自车在保证安全跟车距离的同时稳定跟随前车,并在满足设定条件时在距离控制模式和速度控制模式之间平稳切换,提升车内乘员的乘坐舒适性。     

车速控制系统自适应油门控制器设计

在分析非线性车辆纵向动力学模型及简化模型基础上，采用一种简化非线件模型设计自适应油门控制器，并应用李亚谱诺夫理论证明了传动系统存在动态过程时控制系统的稳定性。通过对基于简化线性和非线性模燃的自适应控制器的仿真研究，结果表明后者具有更好的收敛性。试验结果也进一步表明，基于非线性模型的自适应控制器可以通过自适应调节减小参数不确定造成的干扰，当传动系统存在动态过程时可以保证车速跟踪误差有界。     

基于驾驶员行为模拟的ACC控制算法

基于驾驶员最优预瞄加速度模型建立了一种适用于多种典型行驶工况的ACC控制算法。该算法采用基于多目标模糊决策方法的驾驶安全性、工效性、轻便性与合法性评价指标以及基于预瞄跟随理论的微分校正函数,描述了ACC控制系统对自由工况、跟随工况和切入工况等不同行驶条件及汽车动力学系统强非线性特性的考虑。     

基于自适应 LQR 的智能汽车横纵向控制

针对自动驾驶横纵向控制换道问题,并考虑到车辆转向不足,提出了一种带有前馈控制的自适应线性二次型调节器（LQR）控制算法。首先,通过油门刹车表的制作搭建了纵向双比例-积分-微分（PID）控制器,然后,基于路径跟踪误差的车辆二自由度动力学模型设计了 LQR 横向控制器,并使用前馈反馈的方法给予车辆一个额外的转角,消除了稳态误差。再分析 LQR 控制器参数并考虑车辆稳定性和乘坐舒适性二项关键评价指标,提出了一种考虑路径曲率和路径跟踪误差的权重参数计算方法,从而保证了车辆轨迹跟踪误差在一定范围内。最后,通过 MATLAB/Simulink 和 CarSim 联合仿真验证所设计的自适应 LQR 控制器。结果表明,该控制器可以较精确地跟踪该换道路径,最大横向误差为 0.027 m,最大航向误差为 0.041 rad。     

混合动力汽车智能巡航系统驾乘舒适性研究

文章针对辅助驾驶自适应巡航功能纵向控制车辆减速时车辆行驶顿挫的问题进行分析,通过上层控制器增加负扭矩请求判断逻辑来优化驾驶舒适性。车辆在跟车过程中纵向控制车辆减速时前后方向的直线运动平顺性得到提升,从而达到主观驾驶感受平稳舒适,为后续车型开发辅助驾驶自适应巡航功能调优提供有效的解决方案。随着车辆辅助驾驶功能以及性能的优化和完善,智能驾驶的舒适性感知问题将会得到改善,智能驾驶技术将得到飞速发展。     

Fidelity of using scaled vehicles for chassis dynamic studies

There are many situations where physical testing of a vehicle or vehicle controller is necessary, yet use of a full-size vehicle is not practical. Some situations include implementation testing of novel actuation strategies, analysing the behaviour of chassis feedback control under system faults, or near-unstable situations such as limit handling under driver-assist feedback control. Historically, many have advocated the use of scale vehicles as surrogates for larger vehicles. This article presents analysis and experimental testing that examines the fidelity of using scaled vehicles for vehicle chassis dynamics and control studies. In support of this effort, this work introduces an experimental system called the Pennsylvania State University Rolling Roadway Simulator (the PURRS). In the PURRS, a custom-built scale-sized vehicle is freely driven on a moving roadway surface. While others have used scale-vehicle rolling roadway simulators in the past, this work is the first to attempt to directly match the planar dynamic performance of the scale-sized vehicle to a specific full-sized vehicle by careful design of the scale vehicle. This article explains details of this effort including vehicle dynamic modelling, detailed measurement of model parameters, conditions for dynamic similitude, validation of the resulting experimental vehicle in the time, frequency, and dimensionless domains. The results of the dynamic comparisons between scale- and full-sized vehicles clearly illustrate operational regimes where agreement is quite good, and other regimes where agreement is quite poor. Both are useful to understand the applicability of scale-vehicle results to full-size vehicle analysis.     

某型重卡 ACC 装饰板的设计开发

因卡车前格栅造型复杂,且外形镀铬,若保持造型的完整性,则雷达信号无法有效穿透。为了保证格栅造型特征的完整和美观,拟从格栅装饰板的结构分析、零件选材、制造工艺、信号衰减检测等多维度切入,阐述适用于卡车的自适应巡航控制系统（ACC）装饰板设计开发。     

混合动力电动汽车能量自适应模糊控制研究

为了实现混合动力电动汽车两种能量的最佳分配,确保电机、蓄电池的合理运行,建立了前向并联式混合动力电动汽车动力系统模型,提出了采用自适应模糊控制方法对动力系统进行能量分配,设计了控制器,讨论了自组织控制器的规则自我调整过程。整车循环工况仿真试验表明该控制具有较强的鲁棒性,可使电机、发动机、蓄电池等动力设备工作于最佳工况。     

遗传算法在汽车巡航模糊控制参数优化中的应用

对车辆巡航系统采用模糊控制,并编制了遗传算法优化程序,分别对模糊控制器的量化因子和比例因子(方案1)以及隶属度函数形状(方案2)进行优化,并比较了两种方案对模糊控制效果的影响。仿真结果表明优化量化因子和比例因子(方案1)取得更令人满意的巡航效果。     

行星齿轮结构的混合动力汽车的系统效率

首先分析了一种行星齿轮结构的混合动力电动汽车的纵向动力学方程,并且研究了不同情况下的汽车系统效率,得到了系统效率优化的目标函数和约束条件,随后利用序列二次规划算法对混合动力电动汽车系统效率进行了优化计算,从而确定了每种工况下的最佳蓄电池功率和最佳减速比。     

车辆自适应巡航系统发展现状研究

随着社会经济的不断发展,车辆数量逐渐增加,车辆的长途行驶场景逐渐增多,对此自适应巡航控制系统有助于降低驾驶员长途驾驶负担和提升车辆安全性。文章在介绍自适应巡航系统的组成后,通过对相关文献的阅读和整理,对该系统当前的控制策略和控制算法发展进行总结,并在此基础上对自适应巡航系统未来的发展做出展望,为车辆自适应巡航系统发展研究提供参考。     

Implementation and verification of adaptive longitudinal traction control

Human in the loop (HIL) simulation has experienced a significant increase in popularity in recent years. In this work, a novel approach to traction control is developed and implemented in a HIL environment, exploiting the significant advantages of framing the problem in a manner that more closely matches how a human expert drives a vehicle. An adaptive gradient ascent algorithm is at the heart of the proposed solution to longitudinal traction control. A real-time implementation of the gradient ascent algorithm is developed using linear operator techniques, even though the tyre–ground interface is highly non-linear. The adaptive traction control algorithm is based on two separate, but related, estimation algorithms that estimate both the instantaneous traction force and a unique predictive traction force model. This adaptive control algorithm, the necessary estimation algorithms and their real-time implementation are described in this work. The results, when implemented as a driver assist application on a 6-DOF motion platform, with a HIL, are also presented. This work demonstrates the utility of a 6-DOF motion platform in developing and verifying vehicle control algorithms with a HIL.     

A curving ACC system with coordination control of longitudinal car-following and lateral stability

The paper presents a curving adaptive cruise control (ACC) system that is coordinated with a direct yaw-moment control (DYC) system and gives consideration to both longitudinal car-following capability and lateral stability on curved roads. A model including vehicle longitudinal and lateral dynamics is built first, which is as discrete as the predictive model of the system controller. Then, a cost function is determined to reflect the contradictions between vehicle longitudinal and lateral dynamics. Meanwhile, some I/O constraints are formulated with a driver permissible longitudinal car-following range and the road adhesion condition. After that, desired longitudinal acceleration and desired yaw moment are obtained by a linear matrix inequality based robust constrained state feedback method. Finally, driver-in-the-loop tests on a driving simulator are conducted and the results show that the developed control system provides significant benefits in weakening the impact of DYC on ACC longitudinal car-following capability while also improving lateral stability.     

Model predictive control with constraints for a nonlinear adaptive cruise control vehicle model in transition manoeuvres

A vehicle following control law, based on the model predictive control method, to perform transition manoeuvres (TMs) for a nonlinear adaptive cruise control (ACC) vehicle is presented in this paper. The TM controller ultimately establishes a steady-state following distance behind a preceding vehicle to avoid collision, keeping account of acceleration limits, safe distance, and state constraints. The vehicle dynamics model is for continuous-time domain and captures the real dynamics of the sub-vehicle models for steady-state and transient operations. The ACC vehicle can execute the TM successfully and achieves a steady-state in the presence of complex dynamics within the constraint boundaries.     

汽车ACC毫米波雷达和视觉传感器目标级融合方法研究

自适应巡航控制系统是实现未来智能化汽车辅助驾驶的重要功能之一,以往该系统主要采用毫米波雷达感知周围环境,但是容易出现较多的误识别和漏识别情况.针对现存的问题,文章研究了自适应巡航感知系统,不同于以往单一雷达的方案,本设计采用毫米波雷达和视觉传感器融合的办法改善感知系统的性能.通过搭建电动车传感器数据采集系统,编写CAN...