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为确保动车组高级修的安全、有序、高效、优质,结合未来高速铁路检修业务的客观发展需要,提出了面向动车高级修的RFID应用技术方案和智能信息系统框架.首先,提出动车基地在配件物流、人员作业流、动车组车流、检修设备设施中的RFID应用技术方案,以及应用难点的解决对策;四种应用是有机整体,以配件应用为核心.然后,指出了将RFID全面应用于动车检修生产各环节,结合数据集成与语义融合,可以极大强化既有应用系统的性能与功能;并且重点对运用RFID为检修产能的提升进行了量化评估.文中涉及的几类RFID应用已在动车基地投入使用,或者经过试点、试验.     

桥吊智能制动器改造测试

桥吊智能制动器研制成功后,为确保其性能,对其进行测试.介绍测试准备工作和测试做法.测试表明,智能型制动器能有效减小制动冲击,保护传动链,并能有效减小结构晃动.     

城市轨道交通智能车站综合管理平台研究

在深入分析当前城市轨道交通信息化建设中存在问题的基础上,针对建设城市轨道交通智能化车站综合管理平台,从生产运营管理、旅客信息服务、维护维修、安全应急等方面,进行涵盖生产、运营、服务全过程的综合解决方案的研究探讨。     

国产轻轨车辆的主要技术参数特点

国产轻轨车辆采用铰接式、短轴距转向架及大截面铝合金车体等先进技术,实现了3、4、5辆车灵活编组及单辆车的双向运行。简要介绍车体、转向架、主电路、辅助电源、制动等主要系统和部件的特点及其技术参数。     

地铁机电设备故障监测与智能诊断系统

阐述北京地铁线网建设加速后地铁机电设备安全运营和设备维护维修面临的相关问题。为提升机电设备养护水平,提高运营维修维护效率,规避设备运行安全风险,提出利用智能诊断技术和智能信息化技术建立地铁机电设备故障监测与智能诊断系统的思路,并针对目前需求和运营管理模式,对系统的逻辑架构和系统构成方案进行论述。     

A design methodology for mechatronic vehicles: application of multidisciplinary optimization,multibody dynamics and genetic algorithms

A design methodology for mechatronic vehicles is presented. With multidisciplinary optimization (MDO) methods, strongly coupled mechanical, control and other subsystems are integrated as a synergistic vehicle system. With genetic algorithms (GAs) at the system level, the mechanical, control and other relevant parameters can be optimized simultaneously. To demonstrate the feasibility and efficacy of the proposed design methodology for mechatronic vehicles, it is used to resolve the conflicting requirements for ride comfort, suspension working spaces and unsprung mass dynamic loads in the optimization of half-vehicle models with active suspensions. Both deterministic and random road excitations, both rigid and flexible vehicle bodies and both perfect measurement of full state variables and estimated limited state variables are considered. Numerical results show that the optimized vehicle systems based on the methodology have better overall performance than those using the linear quadratic Gaussian (LQG) controller. It is shown that the methodology is suitable for complex design optimization problems where: (1) there is interaction between different disciplines or subsystems; (2) there are multiple design criteria; (3) there are multiple local optima; (4) there is no need for sensitivity analysis for the optimizer at the system level; and (5) there are multiple design variables.     

Fault classification method for the driving safety of electrified vehicles

A fault classification method is proposed which has been applied to an electric vehicle. Potential faults in the different subsystems that can affect the vehicle directional stability were collected in a failure mode and effect analysis. Similar driveline faults were grouped together if they resembled each other with respect to their influence on the vehicle dynamic behaviour. The faults were physically modelled in a simulation environment before they were induced in a detailed vehicle model under normal driving conditions. A special focus was placed on faults in the driveline of electric vehicles employing in-wheel motors of the permanent magnet type. Several failures caused by mechanical and other faults were analysed as well. The fault classification method consists of a controllability ranking developed according to the functional safety standard ISO 26262. The controllability of a fault was determined with three parameters covering the influence of the longitudinal, lateral and yaw motion of the vehicle. The simulation results were analysed and the faults were classified according to their controllability using the proposed method. It was shown that the controllability decreased specifically with increasing lateral acceleration and increasing speed. The results for the electric driveline faults show that this trend cannot be generalised for all the faults, as the controllability deteriorated for some faults during manoeuvres with low lateral acceleration and low speed. The proposed method is generic and can be applied to various other types of road vehicles and faults.     

Real-time model predictive control of connected electric vehicles

ABSTRACT

Electric Vehicles (EVs) motors develop high torque at low speeds, resulting in a high rate of acceleration with the added advantage of being fitted with smaller gearboxes. However, a rapid rise of torque in EVs fitted with central drive powertrains can create undesired torsional oscillations, which are influenced by wheel slip and flexibility in the halfshaft. These torsional oscillations in the halfshaft lead to longitudinal oscillations in the vehicle, thus creating problems with regard to comfort and drivability. The significance of using wheel slip in addition to halfshaft torsion for design of anti-jerk controllers for EVs has already been highlighted in our previous research. In this research, we have designed a look-ahead model predictive controller (LA-MPC) that calculates the required motor torque demand to meet the dual objectives of increased traction and anti-jerk control. The designed LA-MPC will improve drivability and energy consumption in connected EVs. The real-time capability of the LA-MPC has been demonstrated through hardware-in-the-loop experiments. The performance of the LA-MPC has been compared to other controllers presented in the literature. A validated high-fidelity longitudinal-dynamics model of the Rav4EV, which is the test vehicle of our research has been used to evaluate the controller.     

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大数据所涉及的信息量规模巨大,大数据技术使得人类认识世界的思想及方法发生变革。智慧物流是利用集成化、智能化、移动化技术,使物流系统具有思维、感知、学习、推理判断和自行解决物流中的某些问题的能力,它包含了智能运输、自动仓储、动态配送及智能信息的获取、加工和处理等多项基本活动,为供方提供最大化的利润,为需方提供最佳的服务,同时也应实现消耗最少的自然资源和社会资源,从而形成完备的智慧物流综合管控体系。论坛的主题是大数据与智慧物流,面向大数据技术在智慧物流领域的应用问题,着重研讨大数据背景下智慧物流体系、理论和方法,推动我国现代物流行业健康有序协调发展。     

基于稳性实时计算技术的船舶破损智能扶正系统研究

基于船舶稳性实时计算技术研究船舶实时状态三维模型数字化算法用于快速计算船舶的大倾角稳性、破舱稳性和平衡浮态。参考遗传算法研究船舶破损智能扶正方案生成算法来实现智能生成扶正方案功能。然后运用上述两种核心算法设计船舶破损智能扶正系统软件,为船舶在突发破损事故时提供一套包含压载水调拨措施与步骤建议的智能扶正方案,提高船舶破损事故的处理能力。