CTM-2002A汽车综合测试仪扩展功能的研发

通过开发软件扩展CTM-2002A汽车综合测试仪的数据处理功能，提高了汽车测试工作的效率。     

Real-time capable vehicle–trailer coupling by algorithms for differential-algebraic equations

The real-time simulation of vehicle trains requires an accurate and numerically feasible representation of the vehicle–trailer coupling. Although the equations of motion for the chassis instances can be reduced to systems of ordinary differential equations, additional constraints on the relative motion of vehicle and trailer are introduced when considering the hitch. In this article, we present a strategy for the simulation of vehicle–trailer combinations, where the algebraic constraints of the coupling are treated explicitly. Although this approach allows exact modeling of the respective joint geometry and realistic calculation of the coupling forces, a suitable numerical algorithm is required in order to solve the resulting differential-algebraic system of index 3 in real-time. The implementation in a commercial vehicle dynamics program is discussed and real-time simulation results are shown, which prove its feasibility for different coupling joints and demanding driving maneuvers.     

Feebates, footprints and highway safety

This paper presents an analysis of a market-based policy aimed at encouraging manufacturers to develop more fuel efficient vehicles without affecting the car buyer’s choice of vehicle size. A vehicle’s size is measured by its “footprint”, the product of track width and wheelbase. Traditional market-based policies to promote higher fuel economy, such as higher gasoline taxes or gas guzzler taxes, also induce motorists to purchase smaller vehicles. Whether or not such policies affect overall road safety remains controversial, however. Feebates, a continuous schedule of new vehicle taxes and rebates as a function of vehicle fuel consumption, can also be made a function of vehicle size, thus removing the incentive to buy a smaller vehicle. A feebate system based on a vehicle’s footprint creates the same incentive to adopt technology to improve fuel economy as simple feebate systems while removing any incentive for manufacturers or consumers to downsize vehicles.     

Computational model of conventional engine mounts for commercial vehicles: validation and application

In this paper, a computational model of conventional engine mounts for commercial vehicles comprising elastic, viscous and friction functional components, which expresses the nonlinear behaviour of the dynamic stiffness and damping of mounts as functions of both frequency and amplitude of excitation, is developed. Optimisation approach is implemented to identify model parameters using measurement data. The developed model has been validated against measurement data for harmonic excitations with a frequency range of 5–100 Hz and an amplitude range of 0.025–2 mm employing three different engine mounts used in heavy trucks. The model shows good and admissible agreement with measurement data keeping the tolerance of estimation below 11%. Simulations of engine vibration dynamics are presented with both proposed model and commonly applied Kelvin–Voigt model of the mounts. The developed model can be used in complete vehicle advanced dynamic analyses and also in the design of semi-active and active engine mounting systems for commercial vehicles.     

带有逆向物流的城市连锁店运输线路优化

逆向物流越来越受到人们的重视，结合节约里程法和启发式算法，对既有正向物流又有逆向物流的城市连锁商店物流配送的路线选择问题，以运输路线最优（即总运输费用最少）及运输车辆的合理利用为原则，进行优化设计。     

分散自律调度集中试验验收方法探讨

主要介绍了成都铁路局遂渝线FZy-CTC分散自律调度集中系统的试验验收方法、具体内容及步骤，对围绕分散自律调度集中系统本身特点进行的试验及验收内容进行了详细的介绍，为将来新建的分散自律调度集中系统的验收提供了可参考的方法。     

EMS型磁浮列车悬浮力分析

悬浮系统是磁浮列车的重要组成部分,其性能将直接影响车辆的性能。悬浮力是线路桥梁设计和车辆线路动力学分析的基础。根据EMS型磁浮列车的特点,给出了悬浮系统的数学模型,分析了悬浮力的大小及其动态特性。     

智能网联车环境下高速匝道汇入车流轨迹优化模型

为了解决传统匝道控制车流汇入时车辆需要减速至停止,从而造成延误时间过长的问题,提出了一种智能网联车环境下的高速匝道汇入车辆轨迹优化的两阶段优化模型,其中,第1 阶段优化车辆进入匝道口的时序;第2 阶段基于第1 阶段的最优时序,优化车辆轨迹. 根据所构建的模型设计了一种启发式算法优化车辆通过匝道冲突区域的时序,然后结合 GPOPS工具优化车辆的轨迹.为了验证所提出方法的有效性,将所提出的方法应用到20 min 随机到达的车流,进行仿真实验.实验结果表明,与先进先出的方法相比,本文所提出的方法能够使总延误减少59.7%,总油耗减少10.5%,说明该方法能够实现车辆以较高的速度通过匝道冲突区域,有效地减少了车辆汇入延误,同时也节约了油耗.     

Development of driving cycles for electric vehicles in the context of the city of Florence

Strong efforts are spent in automotive engineering for the creation of so called Driving Cycles (DCs). Vehicle DC development has been a topic under research over the last thirty years, since it is a key activity both from an authority and from an industrial research point of view. Considering the innovative characteristics of Electric Vehicles (EVs) and their diffusion on certain contexts (e.g. city centers), the demand for tailored cycles arises. A proposal for driving data analysis and synthesis has been developed through the review and the selection of known literature experiences, having as a goal the application on a EVs focused case study. The measurement campaign has been conducted in the city of Florence, which includes limited traffic areas accessible to EVs. A fleet of EVs has been monitored through a non-invasive data logging system. After data acquisition, time-speed data series have been processed for filtering and grouping. The main product of the activity is a set of DCs obtained by pseudo-randomized selection of original data. The similarity of synthetic DCs to acquired data has been verified through the validation of cycle parameters. Finally, the new DCs and a selection of existing ones are compared on the basis of relevant kinematic parameters and expected energy consumption. The method followed for the creation of DCs has been implemented in a software package. It can be used to generate cycles and, under certain boundary conditions, to get a filtered access to the measured data and provide integration within simulation environment.     

Estimating potential increases in travel with autonomous vehicles for the non-driving,elderly and people with travel-restrictive medical conditions

Automated vehicles represent a technology that promises to increase mobility for many groups, including the senior population (those over age 65) but also for non-drivers and people with medical conditions. This paper estimates bounds on the potential increases in travel in a fully automated vehicle environment due to an increase in mobility from the non-driving and senior populations and people with travel-restrictive medical conditions. In addition, these bounding estimates indicate which of these demographics could have the greatest increases in annual vehicle miles traveled (VMT) and highlight those age groups and genders within these populations that could contribute the most to the VMT increases. The data source is the 2009 National Household Transportation Survey (NHTS), which provides information on travel characteristics of the U.S. population. The changes to light-duty VMT are estimated by creating and examining three possible travel demand wedges. In demand wedge one, non-drivers are assumed to travel as much as the drivers within each age group and gender. Demand wedge two assumes that the driving elderly (those over age 65) without medical conditions will travel as much as a younger population within each gender. Demand wedge three makes the assumption that working age adult drivers (19–64) with medical conditions will travel as much as working age adults without medical conditions within each gender, while the driving elderly with medical any travel-restrictive conditions will travel as much as a younger demographic within each gender in a fully automated vehicle environment. The combination of the results from all three demand wedges represents an upper bound of 295 billion miles or a 14% increase in annual light-duty VMT for the US population 19 and older. Since traveling has other costs besides driving effort, these estimates serve to bound the potential increase from these populations to inform the scope of the challenges, rather than forecast specific VMT scenarios.