Evaluation of odometry algorithm performances using a railway vehicle dynamic model

In modern railway Automatic Train Protection and Automatic Train Control systems, odometry is a safety relevant on-board subsystem which estimates the instantaneous speed and the travelled distance of the train; a high reliability of the odometry estimate is fundamental, since an error on the train position may lead to a potentially dangerous overestimation of the distance available for braking. To improve the odometry estimate accuracy, data fusion of different inputs coming from a redundant sensor layout may be used. Simplified two-dimensional models of railway vehicles have been usually used for Hardware in the Loop test rig testing of conventional odometry algorithms and of on-board safety relevant subsystems (like the Wheel Slide Protection braking system) in which the train speed is estimated from the measures of the wheel angular speed. Two-dimensional models are not suitable to develop solutions like the inertial type localisation algorithms (using 3D accelerometers and 3D gyroscopes) and the introduction of Global Positioning System (or similar) or the magnetometer. In order to test these algorithms correctly and increase odometry performances, a three-dimensional multibody model of a railway vehicle has been developed, using Matlab-Simulink?, including an efficient contact model which can simulate degraded adhesion conditions (the development and prototyping of odometry algorithms involve the simulation of realistic environmental conditions). In this paper, the authors show how a 3D railway vehicle model, able to simulate the complex interactions arising between different on-board subsystems, can be useful to evaluate the odometry algorithm and safety relevant to on-board subsystem performances.     

Odometric estimation for automatic train protection and control systems

The paper summarises the main features concerning the definition of an efficient odometry algorithm to be used in modern automatic train protection and control (ATP/ATC) systems. The availability of a reliable speed and travelled distance estimation is essential for the efficiency and the safety of the whole system. The first essential step in odometric subsystem design is the choice of the sensors, whose output signals will be used for velocity estimation. Then a suitable procedure fusing sensor signals has to be defined as a function of number and type of sensors and accuracy and safety targets. In the paper, the main features of an innovative solution will be summarised and its performance will be presented, in terms of precision in speed and travelled distance estimation.     

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.     

Development of a new time domain-based algorithm for train detection and axle counting

This paper presents an innovative train detection algorithm, able to perform the train localisation and, at the same time, to estimate its speed, the crossing times on a fixed point of the track and the axle number. The proposed solution uses the same approach to evaluate all these quantities, starting from the knowledge of generic track inputs directly measured on the track (for example, the vertical forces on the sleepers, the rail deformation and the rail stress). More particularly, all the inputs are processed through cross-correlation operations to extract the required information in terms of speed, crossing time instants and axle counter. This approach has the advantage to be simple and less invasive than the standard ones (it requires less equipment) and represents a more reliable and robust solution against numerical noise because it exploits the whole shape of the input signal and not only the peak values. A suitable and accurate multibody model of railway vehicle and flexible track has also been developed by the authors to test the algorithm when experimental data are not available and in general, under any operating conditions (fundamental to verify the algorithm accuracy and robustness). The railway vehicle chosen as benchmark is the Manchester Wagon, modelled in the Adams VI-Rail environment. The physical model of the flexible track has been implemented in the Matlab and Comsol Multiphysics environments. A simulation campaign has been performed to verify the performance and the robustness of the proposed algorithm, and the results are quite promising. The research has been carried out in cooperation with Ansaldo STS and ECM Spa.     

Terrain-based road vehicle localisation using particle filters

This work develops a particle filter algorithm to localise a vehicle in the direction of travel without the use of GPS. The inputs to the algorithm include a terrain map of road grade, pitch measurements from an in-vehicle pitch sensor, and wheel odometry. Simulations and experiments at The Thomas D. Larson Transportation Institute test track are used to demonstrate the algorithm, observe the speed of convergence, and to determine key parameters for practical implementation. The results indicate that the method can quickly localise a vehicle with 1 m accuracy or better. Experiments over 5 km along Highway 322 in State College, Pennsylvania, were also used to demonstrate the algorithm.     

电动助力转向系统回正控制算法研究

提出了一种电动助力转向系统回正控制算法以提高转向盘的回正性。开发了一种基于转向盘转角估计的PID控制算法，该控制算法不需要转向盘转角或者电动机转速传感器，降低了控制系统的成本。同时，对提出的控制算法进行了仿真，并与其它回正控制算法的试验进行对比，结果证实此算法可提高转向盘的回正性和稳定性。     

基于免疫遗传算法的铁路列车运行调整研究

列车运行调整是铁路调度部门的重点研究对象,而自动调整是衡量铁路调度指挥自动化水平的核心。因此,以偏离运行图最小为优化目标,考虑了区间运行时分、追踪间隔时间、车站停车时分、越行约束等6个约束条件,建立了列车运行调整模型;在算法方面,针对遗传算法的缺陷,如收敛速度较慢,易于早熟收敛,提出了1种效果较好的免疫遗传算法,并对编码方案、适应度函数、抗体浓度、变异算子等进行设计改进。仿真结果表明该算法与遗传算法相比,在收敛速度,最优值以及试验成功率方面都具有更为优越的特性,可为调度人员提供1个较好的调整方案。     

基于列车运行时间偏差惩罚的高速列车节能优化方法

合理的安排列车在区间的运行方式能够有效的降低列车运行能耗。采用基于区间限速的列车工况确定策略确定列车区间运行工况, 以列车运行能耗为优化目标, 以列车运行距离、时间和列车限速等为约束条件, 在目标函数中加入列车运行时间偏差惩罚项, 建立基于列车运行时间偏差惩罚的高速铁路列车运行节能优化数学模型, 采用基于高斯变异和混沌扰动的改进人工蜂群算法对优化模型进行求解。以CRH3-350型动车组数据为例对模型与算法进行验证, 求解结果显示: 考虑列车运行时间偏差惩罚比不考虑列车运行时间偏差惩罚能耗可节省2.5%, 改进人工蜂群算法与基本人工蜂群算法、粒子群算法相比, 在目标值方面分别提高了4.2%和4.1%。采用基于区间限速的列车运行工况确定策略结合能耗优化模型能够满足不同限速和不同区间运行时分要求下的列车运行情况。表明所建模型和设计的算法有良好的求解效率和优化质量。     

基于多传感信息融合的智能车辆定位方法

针对高精度定位系统中地图的重要性问题,将定位问题分为无地图定位与基于地图定位,分别对智能车辆的定位问题进行探索.对研究的智能车辆、传感器及其定位问题进行建模分析,再对该平台实施传感器校准以减小系统误差.对于无地图定位问题,利用扩展卡尔曼滤波算法将里程计与惯性测量单元(IMU)数据相融合,通过试验证明航迹推测法存在累计误...     

Active yaw damper for the improvement of railway vehicle stability and curving performances: simulations and experimental results

To further increase passenger train comfort and handling performances, a mechatronic approach to the design of railway vehicles is necessary. In fact, active systems on board a railway vehicle allow to push design barriers beyond those encountered with just passive systems. The article deals with the development of an electro-mechanical actuator to improve the running behaviour of a railway vehicle, both in straight track and curve. The main components of the active system are a brushless motor and a mechanical transmission, used to apply a longitudinal force between the carbody and the bogie of the vehicle. The actuator is operated in force control. Different control strategies were developed for straight track running, where the aim is to increase the vehicle critical speed, and for curve negotiation, where the goal is to reduce the maximum values of track shift forces. A mathematical model of the railway vehicle incorporating the active control device has been developed and used to optimise control strategies and hardware set-up of the active device and to estimate the increase in operating performances with respect to a conventional passive vehicle. The active control device has then been mounted on an ETR470 railway vehicle, and its performances have been evaluated during in-line tests in both straight and curved tracks.     

Active yaw damper for the improvement of railway vehicle stability and curving performances: simulations and experimental results

To further increase passenger train comfort and handling performances, a mechatronic approach to the design of railway vehicles is necessary. In fact, active systems on board a railway vehicle allow to push design barriers beyond those encountered with just passive systems. The article deals with the development of an electro-mechanical actuator to improve the running behaviour of a railway vehicle, both in straight track and curve. The main components of the active system are a brushless motor and a mechanical transmission, used to apply a longitudinal force between the carbody and the bogie of the vehicle. The actuator is operated in force control. Different control strategies were developed for straight track running, where the aim is to increase the vehicle critical speed, and for curve negotiation, where the goal is to reduce the maximum values of track shift forces. A mathematical model of the railway vehicle incorporating the active control device has been developed and used to optimise control strategies and hardware set-up of the active device and to estimate the increase in operating performances with respect to a conventional passive vehicle. The active control device has then been mounted on an ETR470 railway vehicle, and its performances have been evaluated during in-line tests in both straight and curved tracks.     

Active control strategy on a catenary–pantograph validated model

Dynamic simulation methods have become essential in the design process and control of the catenary–pantograph system, overall since high-speed trains and interoperability criteria are getting very trendy. This paper presents an original hardware-in-the-loop (HIL) strategy aimed at integrating a multicriteria active control within the catenary–pantograph dynamic interaction. The relevance of HIL control systems applied in the frame of the pantograph is undoubtedly increasing due to the recent and more demanding requirements for high-speed railway systems. Since the loss of contact between the catenary and the pantograph leads to arcing and electrical wear, and too high contact forces cause mechanical wear of both the catenary wires and the strips of the pantograph, not only prescribed but also economic and performance criteria ratify such a relevance. Different configurations of the proportional-integral-derivative (PID) controller are proposed and applied to two different plant systems. Since this paper is mainly focused on the control strategy, both plant systems are simulation models though the methodology is suitable for a laboratory bench. The strategy of control involves a multicriteria optimisation of the contact force and the consumption of the energy supplied by the control force, a genetic algorithm has been applied for this purpose. Thus, the PID controller is fitted according to these conflicting objectives and tested within a nonlinear lumped model and a nonlinear finite element model, being the last one validated against the European Standard EN 50318. Finally, certain tests have been accomplished in order to analyse the robustness of the control strategy. Particularly, the relevance or the plant simulation, the running speed and the instrumentation time delay are studied in this paper.     

A railway vehicle multibody model for real-time applications

Hardware in the loop (HIL) techniques are widely used for fast prototyping of control systems, electronic and mechatronic devices. In the railway field, several mechatronic on board subsystems are often tested and calibrated following the HIL approach. The accuracy of HIL tests depends on how the simulated virtual environment approximates the physical conditions. As the computational power available on real-time hardware grows, the demand for more complex and realistic models of railway vehicles for real-time application increases. In past research activities, the authors worked on the implementation of simplified real-time models for several applications and in particular for an HIL test rig devoted to the type approval of wheel slide protection systems. The activity has then been focused on the development of a three-dimensional model of the dynamics of a railway vehicle for more complex applications. The paper summarises the features and the results of the study.     

基于浮动车定位数据的高速公路区间平均速度估计

通过对浮动车定位数据情况的分析,可知大部分速度估计算法仅适用于采样时间间隔不大于行程时间的情况,为在相同浮动车比例以及采样时间间隔的条件下,提高数据利用率,以提高速度估计结果的路网覆盖率,提出两种速度估计算法:车辆跟踪法、速度-距离积分法,并给出路段区间平均速度自适应估计模型.使用真实交通流OD 数据进行仿真,结果表明...     

考虑动力学模型系统误差补偿的智能车GNSS/IMU组合定位算法

为了解决智能车动态组合定位过程中，因动力学模型与实际模型之间存在偏差导致滤波精度下降的问题，针对智能车全球导航卫星系统(GNSS)/惯性测量单元(IMU)组合定位系统，结合非线性预测滤波(NPF)和自适应滤波的优点，提出了一种考虑动力学模型系统误差实时估计和补偿的自适应非线性预测滤波(ANPF)算法。首先，根据NPF算法原理，通过最小化预测观测残差与系统误差的加权平方和，估计动力学模型系统误差；其次，结合自适应滤波原理，利用状态预测残差向量构造自适应因子，设计了一种自适应扩展卡尔曼滤波(AEKF)算法，用于估计系统状态向量，并通过自适应因子抑制动力学模型系统误差和线性化误差对系统状态估计精度的影响，克服NPF对系统状态估计精度有限的缺陷；再次，对动力学模型系统误差的估计误差和由动力学模型系统误差引起的系统噪声的等效协方差阵进行了分析和推导，以补偿动力学模型系统误差对系统状态估计的影响；最后，通过车载GNSS/IMU组合定位系统试验，从算法精度、鲁棒性和实时性方面对提出的算法和其他滤波算法的性能进行了验证和对比分析。研究结果表明:提出的自适应算法继承了NPF算法简易性和高实时性的优点，同时克服了NPF算法估计精度有限的缺陷，具有较好的滤波解算精度，水平定位精度小于1.0 m，算法单次平均执行时间约为0.013 9 ms，在精度和实时性的平衡方面显著优于其他滤波方法。     

Estimation of vehicle sideslip angle and tire-road friction coefficient based on magnetometer with GPS

This paper presents a method that estimates the vehicle sideslip angle and a tire-road friction coefficient by combining measurements of a magnetometer, a global positioning system (GPS), and an inertial measurement unit (IMU). The estimation algorithm is based on a cascade structure consisting of a sensor fusing framework based on Kalman filters. Several signal conditioning techniques are used to mitigate issues related to different signal characteristics, such as latency and disturbances. The estimated sideslip angle information and a brush tire model are fused in a Kalman filter framework to estimate the tire-road friction coefficient. The performance and practical feasibility of the proposed approach were evaluated through several tests.     

Adaptive backstepping control of train systems with traction/braking dynamics and uncertain resistive forces

Although backstepping control design approach has been widely utilised in many practical systems, little effort has been made in applying this useful method to train systems. The main purpose of this paper is to apply this popular control design technique to speed and position tracking control of high-speed trains. By integrating adaptive control with backstepping control, we develop a control scheme that is able to address not only the traction and braking dynamics ignored in most existing methods, but also the uncertain friction and aerodynamic drag forces arisen from uncertain resistance coefficients. As such, the resultant control algorithms are able to achieve high precision train position and speed tracking under varying operation railway conditions, as validated by theoretical analysis and numerical simulations.     

Dynamic sensor zeroing algorithm of 6D IMU mounted on ground vehicles

The main focus of this paper is to compensate the steady state offset error of the 6D IMU which provides the measurements that include the vehicle linear accelerations and angular rates of all three axes. Additionally, the sensor compensation algorithm exploits the wheel speed data and the steering angle information, since they are already available in most of the modern mass production vehicles. These inputs are combined with the inverse vehicle kinematics to estimate the steady state offset error of each sensor inputs as it is done in a disturbance observer, and the raw sensor measurements are compensated by the estimated offset errors. The stability of the error dynamics regarding the integrated signal processing system is verified, and finally, the performance of the system is tested via experiments based on a real production SUV.     

中欧普速铁路路基设计主要技术标准对比分析

为了提高中国工程师对欧洲普速铁路路基设计规范体系的理解和掌握,分析对比了中欧普速铁路路基设计主要技术标准,收集分析总结中欧普速铁路路基设计规范体系,并就列车荷载、路基结构、填料和压实度进行对比。对比分析表明:中国与欧洲（英、法、德）铁路路基设计标准在设计理念上相通,路基工程应按土工结构物进行设计;列车荷载中欧规范基本相同;路基结构分层中欧规范略有差异;基床厚度中德规范最接近,英法规范取值比中国规范小;中国规范常用瑞典圆弧法,欧洲规范常用简化Bishop法、Janbu法等。     

Certification des automatismes numériques dans les transports guidés : projets européens CASCADE et ACRuDA

This paper presents current work which deals with the certification of automatic train protection systems according to European standards and has three main sections. The first deals with the current situation as regards third party conformity certification on the basis of a reference document. The role of notified assessors and the requirements of European standards such as Cenelec 50126, 128 and 129 are discussed and the essential elements of the European high speed train interoperability directive are given. The second section summarizes the results of the Cascade project (Certification and Assessment of Safety-Critical Application Development) which is part of the Esprit III programme. This project deals with the harmonization of the various evaluation and certification approaches for safety critical software in railway applications. Its aim is to formulate a shared evaluation method to enable safety critical software to be certified by any notified assessor in a State in the European Union with the same criteria and rules, and in accordance with applicable European standards. The third section of the paper presents the Acruda project (Assessment and Certification Rules for Digital Architectures) which supplements the work on software carried out in Cascade. This project concerns the certification of hardware architectures and makes it possible to implement certification rules for the computers used to ensure the safety of train control systems.