Low cost design of parallel parking assist system based on an ultrasonic sensor

This paper presents a low cost design and implementation of a parallel parking assist system (PPAS) based on ultrasonic sensors. Generally, a PPAS requires several types of sensors, such as an ultrasonic sensor, camera sensor, radar sensor and laser sensor for parking space detection. However, our proposed PPAS only requires two ultrasonic sensors on the front and lateral sides for parking space detection. Moreover, a steering angle sensor and wheel speed sensor installed in the vehicle are used to obtain vehicle position information for localization in ultrasonic range data. The hardware architecture of the PPAS based on an electronic control unit (ECU) module, sensor modules and a human machine interface (HMI) module was proposed. Moreover, the software architecture of the PPAS is based on system initialization, scheduling, recognition and a control algorithm. In particular, a novel sensor algorithm was proposed to minimize the vehicle corner error of the ultrasonic sensor. A prototype of the PPAS based on the proposed architecture was constructed. The experimental results demonstrate that the implemented prototype is robust and successfully performs parking space detection and automatic steering control. Finally, the low cost design and implementation of the PPAS was possible due to the cheap ultrasonic sensors, simple hardware design and low computational complexity of the proposed algorithm.     

A comparative study on fault detection methods of rail vehicle suspension systems based on acceleration measurements

Reliability of the railway vehicle suspension system is of critical importance to the safety of the vehicle. On-line health condition monitoring for the suspension system of rail vehicles offers a number of benefits such as preventing further deterioration of vehicle performance, enhancing vehicle safety, increasing operational reliability and availability, and reducing maintenance costs. It is desirable to timely detect the fault and monitor the performance degradation of vehicle suspension systems. In this paper, a comparative study on fault detection methods of urban rail vehicle suspension systems is considered. A novel sensor configuration is proposed where the underlying vehicle system is equipped with only acceleration sensors in the four corners of the carbody, the leading and trailing bogie, respectively. A mathematical model is developed for the considered vehicle suspension system. Both model-based and data-driven approaches are studied for the suspension fault detection problem. The robust observer, the Kalman filter combined with the generalised likelihood ratio test method, the dynamical principle components analysis and the canonical variate analysis approaches are applied to the fault detection problem. The simulation is carried out by means of the professional multi-body simulation tool, SIMPACK. In addition, the advantages and disadvantages of these methods are compared. The simulation results show that the data-driven methods outperform the model-based methods.     

Model-based fault detection and isolation in automotive yaw moment control system

This paper presents a model-based fault detection and isolation technique for automotive yaw moment control system. For this purpose, a novel fault detection and isolation algorithm for a class of actuator-plant systems is proposed. Compared with the existing fault detection and isolation techniques that can only isolate a target fault or require multiple observers to isolate multiple faults, a unique strength of the proposed algorithm is its ability to isolate faults at the component level solely based on the residuals generated by a single observer. The validity of the proposed algorithm, applied to automotive yaw moment control system, is investigated via a simulation study based on a realistic vehicle dynamics model. The results suggest that the proposed algorithm can isolate the component subject to fault while effectively handling two perennial nuisances: sensitivity to disturbances and false alarms due to uncertainties.     

Isrss: Integrated side/rear safety system

As driver assistant systems (DAS) and active safety vehicles (ASV) with various functions become popular, it is not uncommon for multiple systems to be installed on a vehicle. If each function uses its own sensors and processing unit, it will make installation difficult and raise the cost of the vehicle. As a countermeasure, research integrating multiple functions into a single system has been pursued and is expected to make installation easier, decrease power consumption, and reduce vehicle pricing. This paper proposes a novel side/rear safety system using only one scanning laser radar, which is installed in the rear corner of the driver’s side. Our proposed system, ISRSS (integrated side/rear safety system), integrates and implements four system functions: BSD (blind spot detection), RCWS (rear collision warning system), semi-automatic perpendicular parking, and semi-automatic parallel parking. BSD and RCWS, which operate while the vehicle is running, share a common signal processing result. The target position designation for perpendicular parking and parallel parking situations is based on the same signal processing. Furthermore, as system functions during running and those during automatic parking operate in exclusive situations, they can share common sensors and processing units efficiently. BSD and RCWS system functions were proved with 13025 and 2319 frames, respectively. The target position designation for perpendicular and parallel parking situations was evaluated with 112 and 52 situations and shows a success rate of 98.2% and 92.3%, respectively.     

Condition monitoring of rail vehicle suspensions based on changes in system dynamic interactions

A novel scheme for the fault detection and condition monitoring of vehicle suspensions is presented in this study. The new technique exploits the dynamic interactions between different vehicle modes caused by component failures in the system, leading to a simple but effective solution. Compared with many model-based fault detection techniques, the proposed technique does not require complex mathematical models of the system and it overcomes potential difficulties associated with nonlinearities and parameter variations in the system. The use of inexpensive inertial sensors and ease of tuning make the practical implementation of the proposed scheme straightforward. A conventional railway vehicle is used in the study to illustrate the basic ideas as well as the effectiveness of the novel fault detection method, although the general principle is applicable to other systems.     

基于预定义几何集的斜列式泊车路径规划方法

目前预定义几何集方法主要用于平行车位和垂直车位2种类型的泊车路径规划,对于未涵盖的停车位种类而言则存在无法规划泊车路径的问题,使得自主泊车系统对于能够泊入的车位种类存在局限性。为了设计斜列式泊车方式用以提高自主泊车系统中车位种类的覆盖率,提出一种基于预定义几何集的斜列式泊车路径规划方法。首先,提出了斜列式C字形泊车路径规划方法,利用几何学设计一种圆弧相切斜线的路径,并通过多项式建模表征任意角度停车位下的斜列式C字形泊车路径;其次,通过分析泊车路径与停车位中可能发生碰撞的关键点之间的距离,构建了泊车路径碰撞约束模型,以此分析不同规格停车位下约束条件的参数,从而获得规划路径安全区域;然后,结合拓扑地图信息与斜列式C字形泊车路径规划的碰撞约束模型,获得合适的泊车路径起始点范围,继而生成与全局路径无缝衔接的安全泊车路径;最后,通过MATLAB/Simulink仿真验证此方法的有效性,并通过实车试验证明实用性。结果表明：所提方法针对任意规格的斜列式停车位,均能有效地规划出无碰撞条件下的斜列式泊车路径;同时,车辆能够良好地跟踪所规划的路径,实现精准泊入停车位,证明所提方法能够提高自主泊车系统中停车位种类的覆盖率,并大幅度提高自主泊车系统的实用性。     

基于自适应神经模糊推理系统的平行泊车路径规划

针对常见的平行泊车场景,提出一种基于自适应神经模糊推理系统的平行泊车路径规划方法。以基于优化算法的泊车路径规划方法得出的泊车路径作为训练样本,利用Python脚本语言建立以自适应遗传算法和拟牛顿法为内核的自动化训练框架,使自动训练后的自适应神经模糊推理系统既可继承基于优化算法的泊车路径规划方法适用范围更广的优势,又有效解决该方法求解过程计算量大的问题。通过仿真分析验证所提出方法的可行性和有效性,结果表明:自动训练后的自适应神经模糊推理系统可依据汽车初始泊车位姿和泊车位信息快速规划出可行的平行泊车路径。     

柴油机转速传感器故障诊断及其失效“跛行”控制

研究了时间控制式电控柴油机转速信号的特点及相位关系;设计了曲轴和凸轮轴传感器失效故障的检测方法及处理算法;开发了由MC68376微处理器和可编程复杂逻辑器件组成的柴油机故障处理系统;在TCD2015V06电控单体泵柴油机上,进行了起动和正常运行时转速传感器失效的试验研究。结果表明,转速传感器出现故障时,系统可识别出相应故障,并进行逻辑切换,使发动机能正常起动和运行。     

基于TOF摄像头的车位检测方案

为了解决目前市场上普遍基于超声波传感器对停车位检测都存在盲区范围大、检测精度低等问题,提出了基于TOF摄像头的停车位检测方案。对多种极限停车位场景进行分析,以广汽新能源GE3车辆为载体,并以安装丘钛科技TOF摄像头为研究对象,对该检测方案在多种场景下进行实车验证。测试结果表明:使用TOF摄像头的停车位检测方案不仅能在更小盲区范围内保证停车安全,而且在满足高精度的情况下适应更多极限车位场景。     

Fault detection method for electric parking brake (EPB) systems with sensorless estimation using current ripples

A fault detection method with parity equations is proposed in this paper. Due to its low cost implementation, the velocity of the motor is not measurable in electric parking brake (EPB) systems. Therefore, residuals are not reliable when estimating the motor velocity with a low-resolution encoder. In this paper, we propose a fault detection method with sensorless estimation using current ripples that estimates the position and velocity of the motor by detecting periodical oscillations of the armature current caused by rotor slots. In addition, this method can estimate the position and velocity of the motor with less computational effort than a state observer. Moreover, the method is less sensitive to motor parameters than model-based estimation methods. The effectiveness of this method is validated with experimental data, and the simulation results show that various faults have their own residual patterns. Therefore, we can detect the presence of faults by monitoring the residual signals.     

Design and evaluation of sideslip angle observer for vehicle stability control

This paper presents a method for estimating the vehicle side slip angle, which is considered as a significant signal in determining the vehicle stability region in vehicle stability control systems. The proposed method combines the model-based method and kinematics-based method. Side forces of the front and rear axles are provided as a weighted sum of directly calculated values from a lateral acceleration sensor and a yaw rate sensor and from a tire model according to the nonlinear factor, which is defined to identify the degree of nonlinearity of the vehicle state. Then, the side forces are fed to the extended Kalman filter, which is designed based on the single-track vehicle model associated with a tire model. The cornering stiffness identifier is introduced to compensate for tire force nonlinearities. A fuzzy-logic procedure is implemented to determine the nonlinear factor from the input variables: yaw rate deviation from the reference value and lateral acceleration. The proposed observer is compared with a model-based method and kinematics-based method. An 8 DOF vehicle model and Dugoff tire model are employed to simulate the vehicle state in MATLAB/SIMULINK. The simulation results shows that the proposed method is more accurate than the model-based method and kinematics-based method when the vehicle is subjected to severe maneuvers under different road conditions.     

Radar Health Monitoring for Highway Vehicle Applications

Monitoring the health of the radar sensor on a highway vehicle poses a special challenge. This is because the radar measures the distance to other independent vehicles on the highway and the motion of these other vehicles may be completely unknown to the fault detection system. Traditional observer-based approaches to fault diagnostic system design cannot be used. A number of new approaches are therefore explored in this paper in an attempt to create a reliable fault detection system for the radar. These include: (a) Use of inter-vehicle communication; (b) Use of a geographic database of pre-identified roadside radar targets; (c) Detection of abrupt failures using fuzzy logic and a knowledge of vehicle acceleration abilities; (d) Use of a redundant sensor that is inexpensive but of poor quality. The performance of each of these approaches is evaluated. Experimental results indicate that a combination of approaches (c) and (d) would provide the most reliable method for radar health monitoring. This combination would work effectively even in the absence of inter-vehicle communication in a realistic highway environment.     

基于矢量运算和多级阈值判断的地磁车位占用检测算法研究

检测算法解决了现有地磁车位检测中无法排除邻位停车干扰以及所选判断标准无法适应多种车型、停车应用场景的问题.检测算法分析磁偶极子模型,基于矢量运算提取目标车位停车过程产生的地磁扰动矢量,有效排除邻近车位停车过程对目标车位磁场的影响.通过收集大量真实停车产生的地磁扰动信息,统计分析地磁扰动的强度以及方向变化特征,合理选取多级阈值作为算法中车位占用检测的标准,保证检测算法适用于多种车型、停车应用场景.经过3个月实地应用测试,发现检测算法车位占用检测精度达到99.3%,优于强度或者方向单一特征判断算法,并能检测出停车是否规范.研究算法尚未应用于大型客车、货车以及特种车辆车位占用判断.      

An efficient recursive least square-based condition monitoring approach for a rail vehicle suspension system

A model-based condition monitoring strategy for the railway vehicle suspension is proposed in this paper. This approach is based on recursive least square (RLS) algorithm focusing on the deterministic ‘input–output’ model. RLS has Kalman filtering feature and is able to identify the unknown parameters from a noisy dynamic system by memorising the correlation properties of variables. The identification of suspension parameter is achieved by machine learning of the relationship between excitation and response in a vehicle dynamic system. A fault detection method for the vertical primary suspension is illustrated as an instance of this condition monitoring scheme. Simulation results from the rail vehicle dynamics software ‘ADTreS’ are utilised as ‘virtual measurements’ considering a trailer car of Italian ETR500 high-speed train. The field test data from an E464 locomotive are also employed to validate the feasibility of this strategy for the real application. Results of the parameter identification performed indicate that estimated suspension parameters are consistent or approximate with the reference values. These results provide the supporting evidence that this fault diagnosis technique is capable of paving the way for the future vehicle condition monitoring system.     

宝马X6轿车电子驻车制动系统结构及维修

介绍宝马X6轿车电子驻车制动系统结构、基本功能和保养维护方法,并通过对具体故障的分析诊断,提出故障检测和排除方法。     

基于扩展卡尔曼滤波算法的智能泊车航位推算研究

针对智能泊车系统对高精度车辆航位估计的要求,设计了基于轮速及方向盘转角信号的扩展卡尔曼滤波航位推算算法.离线仿真实验将本算法与传统航位推算算法进行了对比,结果显示本算法具有更高的精度;实车试验进一步验证了本算法的实际应用价值.     

独立式EPB结构设计与仿真分析

本文通过计算汽车在不同坡度上驻车时所需要驻车力的大小,设计独立式EPB结构,并通过对独立式EPB结构中主要部件螺栓和卡钳嵌体的受力仿真分析,验证整个结构最大应力位置及所选用的材料满足设计要求,总结出独立式EPB卡钳钳体可以进行轻量化设计,适应现今汽车轻量化的发展趋势。     

Diagnosis Methods for Electronic Controlled Vehicles

The development of automotive systems shows an increasing number of sensors, actuators and microelectronic controllers, partially for active driver assistance. However, electronic and electrical components have quite different failure behavior and in general lower reliability than mechanical components. On the other side microcomputers can also be used for fault detection and diagnosis. The contribution therefore shows how model-based fault detection and diagnosis methods together with few available measurements can be applied for automobiles. After an introduction, a short summary is given for fault detection and diagnosis methods, especially for model-based methods. Then some research results are shown, like the fault detection and diagnosis of an electromechanical throttle actuator, a suspension system and the lateral behavior of a passenger car. Finally, methods for fault-tolerant sensors and actuators are discussed which are required for drive-by-wire systems.     

Diagnosis Methods for Electronic Controlled Vehicles

The development of automotive systems shows an increasing number of sensors, actuators and microelectronic controllers, partially for active driver assistance. However, electronic and electrical components have quite different failure behavior and in general lower reliability than mechanical components. On the other side microcomputers can also be used for fault detection and diagnosis. The contribution therefore shows how model-based fault detection and diagnosis methods together with few available measurements can be applied for automobiles. After an introduction, a short summary is given for fault detection and diagnosis methods, especially for model-based methods. Then some research results are shown, like the fault detection and diagnosis of an electromechanical throttle actuator, a suspension system and the lateral behavior of a passenger car. Finally, methods for fault-tolerant sensors and actuators are discussed which are required for drive-by-wire systems.     

Literature review and fundamental approaches for vehicle and tire state estimation*

ABSTRACT

Most modern day automotive chassis control systems employ a feedback control structure. Therefore, real-time estimates of the vehicle dynamic states and tire-road contact parameters are invaluable for enhancing the performance of vehicle control systems, such as anti-lock brake system (ABS) and electronic stability program (ESP). Today's production vehicles are equipped with onboard sensors (e.g. a 3-axis accelerometer, 3-axis gyroscope, steering wheel angle sensor, and wheel speed sensors), which when used in conjunction with certain model-based or kinematics-based observers can be used to identify relevant tire and vehicle states for optimal control of comfort, stability and handling. Vehicle state estimation is becoming ever more relevant with the increased sophistication of chassis control systems. This paper presents a comprehensive overview of the state-of-the-art in the field of vehicle and tire state estimation. It is expected to serve as a resource for researchers interested in developing vehicle state estimation algorithms for usage in advanced vehicle control and safety systems.