智能小车外文翻译

1、窗体顶端 2015届毕业设计（论文） 外文翻译 院 、 部： 电气与信息工程学院 学生姓名： 指导教师： 职 称： 讲师 专 业： 通信工程 班 级： 学 号： 2015年 6 月车辆动态避障控制器的发展窗体顶端窗体底端Geraint Paul Bevan美国俄亥俄州立大学摘 要安全在汽车行业依然占据着越来越重要的地位，有了重要意义的研究和进展在封闭线路控制系统领域。为了防止车轮因急刹车或低摩擦转向失控,最先开始使用防抱死制动系统（ABS）。车辆动态控制进一步发展包括牵引力控制：系统即最佳分配牵引力，并防止过度车轮打滑。最近的发展已经在电子稳定控制（ESC）的区域得到应用。如今汽车技术已经发展

2、了多年，ABS和ESC正在成为对大多数车辆的标准，不仅汽车制造商，还有各国政府和监管机构的标准有专门的程序，以确保标准和了解这些系统的局限性。其结果是，所做出的努力已经完成开发测试系统和测试机动量化动态属性。这项研究的重点是研究标准试行、开发新的战略评估和配备了现代车辆动态控制系统。 在过去十年里，另一个有重要意义的发展是自主（或无人）车辆。自主车辆的一个重要应用是自动化无人车辆测试，它代替了人类进行车辆测试。这增加可靠性和测试试行的可重复性，这是及其重要的在一些专门的试行中。大多数车辆动态测试包括精确动方向盘或刹车/油门踏板，转向控制器和制动机器人被设计努力做到这一点。SEA有限责

3、任公司设计出这样的系统和被OSU研究人员广泛的应用，自动化无人车辆测试已经被证明可以准确地执行各种标准测试，还有适用范围广的车辆，也可用于由各种组织世界各地。车辆动态控制和自主车辆在这一研究领域结合在一起;自动化测试驱动程序开发应用于执行路径跟踪军事试行评估车辆动态控制器的性能，包括那些使用ESC的逃避驾驶状况的汽车。 在回避演练的轮胎力不再打滑的线性函数角和所述车辆的响应是非线性的和潜在不稳定的，其中一个条件活性稳定系统被设计为减轻。不足梯度的线性范围的定义不适合于非线性动态范围的分析。这项研究的另一个重点是基于估计轮胎力，以评估稳定性和可控性。车辆观察员要专为检测和测量转向不足的动态试行。

4、该方法可用于基准不论被动或主动控制的车辆。 作为自主转向控制问题的延伸，该项目涉及研究中的应用主动转向系统的车辆稳定性控制的。控制算法开发使用信息从轮胎力估计和驾驶意图车型得到由主动转向系统线性和可预测的车辆侧向响应。 本研究汇集自动化测试驱动程序的开发，活性车辆运动控制系统和检测动态稳定性通过使用轮胎力估计。第1简介1.1简介与动机 自主车在汽车技术上的重大进步技术。大量的无人地面车辆研究方案已经在各级政府，研究机构以及学院展开研究。这些研究包括自动公路研究，其中自主公路主要应用于乘用车铺设道路和无人驾驶越野驾驶，如DARPA地面大挑战。自主车中另一个非常重要的应用是自动化无人驾驶测试，这是

5、无人车代替人类进行车辆测试，无人测试得到的可靠的结果是提高了可靠性和测试试行的重复性。安全在汽车设计中占据了非常重要的地位，动态测试受到了很多人的关注。 大多数车辆动态测试都涉及到方向盘或刹车/油门踏板的动作准确性。转向系统控制器和制动机器人被设计来做到这一点。SEA有限责任公司设计出这样的系统和被OSU研究人员广泛的应用，已经被证明准确地执行各种标准测试，适用范围广的车辆，也可用于由各种组织世界各地。这项研究的重点是自动化测试驱动开发（ATD）（转向控制和制动，油门机器人（BTR），以及延长ATD的适用性进行动态路径跟踪试行和变速测试。窗体底端窗体顶端1.2目的和范围 如今汽车技术已经发展了

6、多年，ABS和ESC正在成为对大多数车辆的标准，不仅汽车制造商，还用各国政府和监管机构的标准有专门的程序，以确保标准和了解这些系统的局限性。其结果是，所做出的努力来已经完成开发测试系统和测试机动量化动态属性。这项研究的重点是研究标准试行和开发新的战略评估和配备了现代车辆动态控制系统。 该项目的目标是开发测试系统，该测试系统用于自主车辆测试。一个测试信号将被设计来评估现代汽车车辆的稳定性和车辆动态控制器的有效性。在不足转向梯度提供有用的信息对车辆方向的稳定性，在线性范围,它并没有提供一个完整的图片,因为它忽略了非线性范围。在规避机动的轮胎力量不再是线性函数滑动角和车辆非线性响应和潜在不稳定,一个

7、条件活跃的稳定系统旨在减轻。 在避让操作的轮胎力不再滑移角的线性函数和该车辆的响应是非线性的和潜在的不稳定性，其中活性稳定系统被设计为减轻的病症。新的参数，提出了研究中定义来衡量汽车的动力不足，转向过度的状态。这项研究的另一个重点是基于估计轮胎力，以评估稳定性和可控性。车辆观测的目的是检测和测量转向不足indynamic试行。这种方法可用于基准不论被动或主动控制的车辆：性能评估将基于在轮胎开发的横向力，而不是仅在车辆的传统的可测量状态。车辆的操控性能将与支配车辆运动轮胎和路面之间的力的知识。方法将开发在试运行的基础比较力量来评估ESC的有效性。第二章2.1 介绍窗体顶端 为了响应严重的交通事故

8、，在过去的几年里，一个新的研究重点出现了，这个研究是关于车辆动态测试的。汽车制造商、政府机构和消费群体已经计划致力于开发和评估车辆稳定性和安全性的优点。 NHTSA包括防碰撞，垃圾再利用和生物力学等领域。防撞类别涉及包括翻车测试，旋转，制动性能等。大多数测试程序都存在有有用的关车辆稳定性的信息。一些操作输入将被称为“开环”。还有一些需要刹车油门驱动纵向动力学研究测试。另一个类别的演练涉及关于路径跟随。一个ATD可以执行不仅是开环测试，也可以在预期的路径和预期的速度测试驾驶车辆。这种演练被称为闭环（相对于到位置和速度），并且是该研究的焦点。2.1.1车辆稳定性 成千上万的互联网短语搜索结果显示“

9、翻车”。翻车事故是被讨论的最多的在车祸报道。不需要太多的数据，一个统计是值得一提的：大约三分之一的美国交通死亡事故涉及单车翻车。侧翻事故通常是基于各种汽车开环测试；J-Turn和NHTSA鱼钩（滚动速度反馈鱼钩机动）1。在演练时必须严格检查车辆的两轮升降（TWL）频率。这些,以及各种ISO试行,消费者联盟的双车道改变和大量的汽车制造商具体操作分为动态测试的范畴。静态类型的翻转是指基于测量的静态稳定性因素,倾斜角度和至关重要的滑动速度可分为静态测试的范畴。一般后者不包括瞬态轮胎行为、悬架的运动效果、顺应性、稳定性控制器的影响。其他侧翻指标已经被调查在侧翻预警和防侧翻预警算法的基础上。陈等人提出了

10、竞技场指标来预测即将发生的翻转。越野车的翻车难以从一个或一个动态试行动作去感知。第三章 本章概述了一些重要的车辆状态和在文献中讨论他们的估计方法。这个卡尔曼滤波器将被解释和应用于估计轮胎强度。进行讨论轮胎强度评估的重要性以及它如何可以用来提供车辆操作状态有用信息。接下来的章节将讨论主动稳定控制和路径跟随算法。 闭环车辆动力学控制的有效性依靠于对车辆的状态准确的了解。一些数据关于偏航率、横向加速度、车轮速度等，可以很容易的被传感器测量。另外的状态车辆侧滑、纵向速度等，被使用其他方法估算着包括测量信号、车辆动态模型和其他复杂的工具。一些状态经常被获得经过直接测量信号的集成-过程中容易出错,对干扰高

11、度敏感。另外的方法获得依赖状态信息包括融合不同的传感器和结合不同个体传感器获得的测量系统。最近的事态发展使用嵌入式处理器已经成为可能，结合使用使用计算密集型的卡尔曼滤波器和各种传感器等方法建立数学模型完成实时状态估计。3.1状态和估计方法 了解车辆状态是稳定控制系统必要的工作。偏航率和横向加速度可以通过便宜的传感器测量。其他参数例如侧滑角、横摇角和轮胎部队等，不容易通过其他方法测量。在当前稳定系统的汽车生产中各种个样的算法已经被讨论和录用。直接集成惯性传感器信号的累积误差时间是不现实的。更复杂的方法包括融合传感器的数据 ，GPS子系统和车辆动力学模型来更好地估计无法估量的状态。接下来是一个简明

12、的讨论关于感兴趣的各种信号和用于估量他们的系统。3.1.1侧滑 侧滑可以结合惯性导航系统和全球定位系统(GPS)信号进行预测。GPS提供绝对的前进方向标志和速度相对较慢的速度测量，结合惯性传感器。从惯性导航系统得到绝对的GPS航向和速度测量消除错误反之,惯性导航系统的GPS测量传感器可以提供更高的更新的车辆的状态。无论如何，在城市驾驶环境，机械计装故障错误，可能导致GPS信号丢失，最终导致错误的估计。有一种方法研究出来预算侧滑而不需要GPS。而不是一个组合测量值， 3轴陀螺仪,3轴加速度计和车辆数学模型用于估算侧滑。 在生产的电动助力转向系统车辆提供了另一种侧滑估算方法。转矩的绝对测量可以从车

13、辆侧滑角估计。转向力矩直接关系到外侧轮胎强度，轮流依赖侧滑角度和车辆状态。转向角和角速度传感器都是廉价的和结合现已装备好稳定控制系统。一个观察干扰者根据转向系统模型估计轮胎调整的时刻;这个估计成为测量车辆侧滑状态的一部分观测器和偏航率。3.1.2倾侧角和道路倾斜角度 倾侧角和道路倾斜角度作为不良干扰因素破坏于加速度测量仪器和可靠的横向加速度与横向速度(或估计侧滑角)。许多研究人员强调倾侧角和道路倾斜角度对于稳定性控制系统的重要性。基于这些研究，本文提出了一种新的识别倾侧角和汽车摇晃的方法，该方法使用扰动观测器和动态模型。首先,介绍了一个包括车辆摇晃状态和道路倾斜干扰的动态模型。这个扰动观测器的

14、用于扰动观测，侧滑角、偏航率,滚转率和车辆倾斜角(倾侧角和道路倾斜角度的总和）。汽车的偏航率和滚转角速度的很容易使用速率陀螺仪测量。利用GPS和INS可以准确测量车辆侧滑角和倾斜角。从扰动观测器可以分别估计道路倾斜角度和车辆摇晃程度。附件2：外文原文 Development of an Autonomous Test Driver and Strategies for Vehicle DynamicsTesting and Lateral Motion ControlDissertationPresented in Partial Fulfillment of the Requirements

15、 forthe Degree Doctor of Philosophy in theGraduate School of the Ohio State UniversityByAnmol Sidhu, M.S. Mechanical Engineering Graduate ProgramThe Ohio State University2010 As safety continues to take an increasingly important place in the automobile industry, there has been significant research a

16、nd development in the area of closed loop control of vehicle dynamics. It first started with antilock brake systems (ABS) thatprevented loss of steering control due to wheels locking up with hard braking or lowfriction. Vehicle dynamics control further developed to include traction control: a system

17、that optimally distributes tractive forces and prevents excessive wheel slip. The most recent developments have been in the area of electronic stability control (ESC). As vehicle technology has evolved over the years and ABS and ESC are now becoming standard on most vehicles, not only automobile man

18、ufacturers but even governments and regulation bodies have programs dedicated to ensure standards and understand limitations of these systems. As a result, efforts have been made to develop testing systems and test maneuvers to quantify dynamic properties. This research focuses on studying standard

19、maneuvers and developing new strategies to evaluate and rate the performance of modern vehicles equipped with advanced vehicle dynamic control systems. Another significant development of the last decade is autonomous (or unmanned) vehicles. An important application of autonomous vehicles is automate

20、d test drivers, which are systems that replace human drivers in vehicle dynamic testing. This increases the reliability and repeatability of test maneuvers, which is imperative for dependable results in some specialized maneuvers. Most vehicle dynamic tests involve precise actuation of steering whee

21、l or brake/throttle pedals. Steering controllers and braking robots are designed to do just that. One such system designed by SEA, Ltd and used extensively by OSU researchers, has been demonstrated to perform various standard tests accurately for a wide range of vehicles and is also used by various

22、organizations worldwide. In this research the areas of vehicle dynamics control and autonomous vehicles come together; the automated test driver is developed to execute path-following maneuvers to evaluate the performance of vehicle dynamics controllers, including those used in ESC, in evasive drivi

23、ng situations. During evasive maneuvers the tire forces are no longer a linear function of slip angles and the vehicle response is nonlinear and potentially unstable, a condition which the active stability systems are designed to mitigate. The definition of understeer gradient in the linear-range do

24、es not lend itself to analysis of nonlinear-range dynamics. Another focus of this research is to assess stability and controllability based on estimation of tire forces. A vehicle observer is designed for the purpose of detecting and measuring understeer and oversteer in dynamic maneuvers. The metho

25、d can be used to benchmark a vehicle regardless of passive or active control.As an extension of the autonomous steering control problem, this project involves the study of application of active steering for vehicle stability control. Control algorithms are developed that use the information from tir

26、e force estimator and driver intent models to yield linearized and predictable vehicle lateral response by an active steering system. This research brings together the development of an automated test driver, active vehicle motion control systems and testing for dynamic stability by using tire force

27、 estimation.1.1 Introduction and Motivation Autonomous vehicles are a major technological advancement in automobiletechnology. Numerous research programs have been undertaken by various governments,research organizations and institutes towards development of unmanned ground vehicles.These include Au

28、tomated highway research where autonomy is applied to passenger carsto drive on paved roads and unmanned off road driving such as the DARPA grand challenge. Another very important application of autonomy in vehicles is automated test drivers which are systems that replace human drivers in vehicle dy

29、namic testing. This increases the reliability and repeatability of test maneuvers which is imperative for dependable results. As safety takes an important place in vehicle design, testing for dynamic response has gained significant attention. Most vehicle dynamic tests involve precise actuation of s

30、teering wheel or brake/throttle pedals. Steering controllers and braking robots are designed to do just that. One such system designed by SEA, Ltd and used extensively by OSU researchers, has been demonstrated to perform various standard tests accurately for a range of vehicles and is also used by v

31、arious organizations worldwide. This research is focused on development of the Automated Test Driver (ATD) (steering control and brake-throttle robot (BTR) as well as extending the applicability of the ATD for dynamic path following maneuvers and variable speed tests. 1.2 Purpose and Scope Vehicle t

32、echnology has evolved over the years and ABS and ESC are now becoming standard on most vehicles. Furthermore, not only automobile manufacturers but even governments and regulation bodies have programs dedicated to ensure standards and understand limitations of these systems. As a result, efforts hav

33、e been made to develop test maneuvers to quantify dynamic properties. This research focuses on studying standard maneuvers and developing new strategies to evaluate and rate the performance of modern vehicles equipped with advanced vehicle dynamic control systems. The goal of this project is to deve

34、lop testing methodologies to test vehicle dynamics using an automated test driver. A test signal will be designed to evaluate vehicle stability and effectiveness of vehicle dynamic controllers of modern vehicles.Where understeer gradient provides useful information about vehicle directional stabilit

35、y in the linear range, it does not provide a complete picture because it ignores the nonlinearrange. During evasive maneuvers the tire forces are no longer a linear function of slip angles and the vehicle response is nonlinear and potentially unstable, a condition which the active stability systems

36、are designed to mitigate. New parameters are proposed in this study defined to measure a vehicles dynamic understeer-oversteer state. Another focus of this research is to assess stability and controllability based on estimation of tire forces. A vehicle observer is designed to detect and measure und

37、ersteer and oversteer in dynamic maneuvers. This method can be used to benchmark a vehicle regardless of passive or active control: evaluation of performance will be based on the lateral forcesdeveloped at the tires and not only on traditional measurable states of the vehicle. Vehicle handling chara

38、cteristics will be related to the knowledge of forces between the tires and road that govern vehicle motion. Methodology will be developed to evaluate effectiveness of ESC by comparing the forces in a test run to the baseline. CHAPTER 2VEHICLE DYNAMICS TESTING2.1 Introduction In response to statisti

39、cs of severe vehicle crashes, a new focus on vehicle dynamic testing has emerged in the past few years. Auto manufacturers, government agencies and consumer groups, have programs dedicated to developing maneuvers to evaluate vehicle stability and safety merits. NHTSA covers the areas of crash avoida

40、nce, crash worthiness,and biomechanics. The category of crash avoidance involves testing for roll-over, spin outs, braking performance, etc. Numerous test procedures exist, which yield useful information about vehicle stability. Some involve steering inputs and will be referred to as “Open loop”. Th

41、ere are also tests that require brake-throttle actuation to study longitudinal dynamics. Another category of maneuvers is the one involving pathfollowing. An ATD can perform not only open-loop tests but can drive a vehicle on a desired path at desired speed. Such maneuvers are referred to as closed-

42、loop (with respect to position and speed) and are the focus of this research.2.1.1 Vehicle Roll Stability Hundreds of thousands of results show up on the Internet from the search phrase,“Vehicle rollover”. Rollover accidents are the most discussed in vehicle crash reports.Without getting into much d

43、etail, one statistic is worth mentioning; roughly one-third oftraffic fatalities in the US involve single-vehicle rollovers. Rollover propensity of vehicles is typically rated based on various open loop tests namely; J-Turn and NHTSA Fishhook (Roll rate feedback fishhook maneuver) 1. Severity and fr

44、equency of vehicle Two-Wheel-Lift (TWL) is examined under these maneuvers. These, as well as various ISO maneuvers, Consumer Unions double lane change and a host of auto manufacturers specific maneuvers fall into the category of dynamic testing. The static type of rollover metrics based on measureme

45、nts of static stability factor, tilt table angle and critical sliding velocity fall into the category of static testing. The latter in general do not incorporate the effects of transient tire behavior, effects of suspension motions and compliances, effects of stability controllers and so forth. Othe

46、r rollover metrics have beeninvestigated to form the basis of rollover warning and anti-rollover warning algorithms. Chen et. al. 2, 3 proposed a Time-To-Rollover (TTR) metric to predict an impending rollover. Susceptibility of SUVs to rollovers is difficult to be concluded from one or ahandful of d

47、ynamic maneuvers. CHAPTER 3APPLICATIONS OF OBSERVERS AND ESTIMATORS This chapter outlines some of the important vehicle states and their estimation methods discussed in literature. The Kalman filter method is explained and applied to estimate tire forces. Importance of tire force estimation and how

48、it can be used to supply useful information of vehicle operating conditions is discussed. The use of this knowledge is discussed in later chapters about active stability control and path-following algorithms. The effectiveness of closed loop vehicle dynamics control is dependent onaccurate knowledge

49、 of vehicle states. Some of the states like yaw rate, lateral acceleration, wheel speeds, etc can be easily measured using inexpensive sensors. Other states like vehicle side-slip, longitudinal speed, etc have to be estimated using other means involving measured signals, vehicle dynamic models and o

50、ther sophisticated tools. ome of the states are often obtained by direct integration of measured signals a process which is prone to errors and highly sensitive to disturbances. Other ways to obtain reliable state information include fusion of different sensors and redundancy in measurement systems

51、combining various properties of individual sensors to obtain reliable state estimation. Recent developments in embedded processors has made possiblethe use of computationally intensive methods like Kalman filters to be used to combine various sensor data and mathematical models in real time for stat

52、e estimation. 3.1 States and Estimation Methods Knowledge of vehicle states is necessary for stability control systems to work. Yaw rate and lateral acceleration are easily measured by inexpensive sensors. Other parameters like sideslip angle, roll angle and tire forces, etc. are not readily measure

53、d and must be estimated by other methods. Various estimators have been discussed in the literature and are employed by current stability systems available on production cars that use different methods. Direct integration of inertial sensor signals accumulates error over time and is unpractical to im

54、plement. More sophisticated methods involve sensor fusion in which data is combined from inertial sensors, GPS, subsystems on board and vehicle dynamics models to better estimate immeasurable states. The following is a brief discussion of various signals of interest and the method and systems used i

55、n theirestimation.3.1.1 Sideslip Side slip can be estimated by a method combining inertial navigation system (INS) and Global Positioning Systems (GPS) signals. GPS provides absolute heading and velocity measurements at a relatively slow rate which complements the faster updates of inertial sensors.

56、 Absolute GPS heading and velocity measurements eliminate the errors from INS integration; conversely, INS sensors complement the GPS measurements by providing higher update rate estimates of the vehicle states. However, during periods of GPS signal loss, which frequently occur in urban driving environments, integration errors can still accumulate and lead to faulty estimates. There are methods developed for sideslip estimation without the use of GPS. Instead a combination of measurements from 3 axis rate gyros, 3 axis accelerometers and vehicle ma