城市轨道交通大小交路模式列车开行方案的优化

列车开行方案是城市轨道交通运输组织的基础.大小交路模式列车开行方案规定各时间段内各交路上开行列车对数.分析大小交路模式乘客出行成本和企业运营成本的计算方法,以乘客出行成本及运输企业运营成本最小化为目标,以列车追踪间隔时间、乘客需求和最大可用车底数量为约束,构建城市轨道交通大小交路模式列车开行方案双目标混合整数非线性规划模型.采用理想点法将原模型转化为单目标模型,借助Lingo11.0求解.通过算例验证模型的合理性,并对折返站和小交路区段客流比重进行成本的灵敏度分析,结果表明:小交路折返站的选取对成本影响显著,且小交路区段客流比重越高,开行大小交路模式越有利于降低运输成本.     

国内外经验对北京新机场线规划的启示

在研究总结国内外机场线运营模式及机场航站楼轨道交通车站特点的情况下,结合北京市新机场的选址和规模,提出北京市新机场线的运营模式和车站布置。在总结国际先进机场系统车站分布特征的基础上,阐述对北京新机场线的车站分布要求,最后提出结论和建议。     

城市轨道交通应急管理模式初探

高速发展的城市轨道交通行业已进入到一个突发公共事件频发的时期,如何正确认识和应对这些突发公共事件,是需要城市轨道交通企业高度重视、谨慎对待的问题;指出必须通过建立和健全城市轨道交通应急管理机制,不断提高城市轨道交通企业应急处置能力.     

工程机械底盘液压驱动装置性能分析(1)

液压驱动装置的结构形式与性能是工程机械底盘液压驱动与控制的两大重要组成部分之一。分析讨论了各类结构形式的液压驱动装置及其与行走机构组成不同形式的液压车辆底盘时的性能与特点。对车辆工作所需要的特殊功能，如液压同步、限速、制动以及补油回路等也进行了讨论，有助于工程车辆的理论研究与产品设计。     

发动机冷却风扇温控液力驱动系统

本文介绍了发动机冷却风扇温控系统，这种新型的控制系统具有自动测量，微机控制，液压驱动，无级变速等特点，可以使发动机在最佳温度下工作，文中详细介绍了系统构成，测控元件选择及软件设计。     

接地面部分溶化条件下冰面轮胎摩擦力的研究

综合运用流体动力润滑理论的能量守恒定律，提出了接地面部分溶化条件下冰面上汽车轮胎的摩擦力或牵引力的理论计算模型。证明了正常工作条件下，接地面上冰产生溶化的可能。对不同制动和驱动条件下轮胎摩擦力进行了计算，取得了同试验数据吻合很好的预测结果。并同已有预测模型进行了比较，比较结果表明：本文依据严格的润滑理论所推导出的冰面轮胎牵引力模型比其它已有理论模型更接近试验结果。     

Transport energy consumption in mountainous roads. A comparative case study for internal combustion engines and electric vehicles in Andorra

This paper analyses transport energy consumption of conventional and electric vehicles in mountainous roads. A standard round trip in Andorra has been modelled in order to characterise vehicle dynamics in hilly regions. Two conventional diesel vehicles and their electric-equivalent models have been simulated and their performances have been compared. Six scenarios have been simulated to study the effects of factors such as orography, traffic congestion and driving style. The European fuel consumption and emissions test and Artemis urban driving cycles, representative of European driving cycles, have also been included in the comparative analysis. The results show that road grade has a major impact on fuel economy, although it affects consumption in different levels depending on the technology analysed. Electric vehicles are less affected by this factor as opposed to conventional vehicles, increasing the potential energy savings in a hypothetical electrification of the car fleet. However, electric vehicle range in mountainous terrains is lower compared to that estimated by manufacturers, a fact that could adversely affect a massive adoption of electric cars in the short term.     

Congestion and pollution consequences of driving-to-school trips: A case study in Beijing

Parents compete for high-quality education for their children by enrolling them in good schools. However, in a Chinese mega-city like Beijing, three factors jointly lead to the spatial separation between schools and homes: the centralized public goods provision mechanism, the historical dependency in school location, and the constrained supply of housing in downtown. Without an adequate number of school buses, this spatial separation of schools and homes triggers the numerous long-distance driving-to-school trips by private vehicle during workday morning rush hours in Beijing. We use the start and end dates of “school holiday” as exogenous repeated shocks to the aggregate traffic congestion, and employ the two-stage least squares (2SLS) regression approach to examine the congestion and pollution consequences of such driving-to-school trips in Beijing. We find that, all else being equal, workdays during school holidays have a traffic congestion index 20% lower than that of non-school-holiday workdays. Such a sharp reduction in congestion leads to a significant decrease in PM₁₀ concentration. Policymakers should lower such “extra” congestion and environmental costs via optimizing the spatial balance between school supply and demand.     

Driving cycle prediction model based on bus route features

Bus fuel economy is deeply influenced by the driving cycles, which vary for different route conditions. Buses optimized for a standard driving cycle are not necessarily suitable for actual driving conditions, and, therefore, it is critical to predict the driving cycles based on the route conditions. To conveniently predict representative driving cycles of special bus routes, this paper proposed a prediction model based on bus route features, which supports bus optimization. The relations between 27 inter-station characteristics and bus fuel economy were analyzed. According to the analysis, five inter-station route characteristics were abstracted to represent the bus route features, and four inter-station driving characteristics were abstracted to represent the driving cycle features between bus stations. Inter-station driving characteristic equations were established based on the multiple linear regression, reflecting the linear relationships between the five inter-station route characteristics and the four inter-station driving characteristics. Using kinematic segment classification, a basic driving cycle database was established, including 4704 different transmission matrices. Based on the inter-station driving characteristic equations and the basic driving cycle database, the driving cycle prediction model was developed, generating drive cycles by the iterative Markov chain for the assigned bus lines. The model was finally validated by more than 2 years of acquired data. The experimental results show that the predicted driving cycle is consistent with the historical average velocity profile, and the prediction similarity is 78.69%. The proposed model can be an effective way for the driving cycle prediction of bus routes.