长春市冬季公共汽车主干路典型行驶工况研究

文章以长春市的城市规划、不同道路特征、不同路段的交通流特性等因素为依据,选取具有代表性典型路段,即主干线306路为调查样本进行取样试验;依据严寒及寒冷地区分类的国家标准,确定冬季试验时间为2013年1月;通过公共汽车的行驶条件确定试验方法为平均车流法;所用试验车辆为中国第一汽车集团公司所产的解放牌CA6120URH2型公共汽车。试验将采集到的数据根据不同行驶状态划分为若干行程片段,并分别计算出每个片段的对应特征值,进而对所有数据片段进行了主成分分析和聚类分析,在相关性及有效性验证之后通过数据拟合构建成主干路典型行驶工况。     

成品油顺序输送实验环道设计

成品油顺序输送过程中对混油的处理会增加管道运营成本,因此需要研究混油的形成机理和复杂边界条件对其影响机理以改进混油切割和处理工艺。文中在相关环道实验的基础上设计了一个采用多种环道元件和管道结构以及不同运行工况的实验环道。设计从实验室规格、实际工况和实验流程出发,根据相似准则及水力条件计算确定环道管径、可行流速、运行压力等参数,并据此完成泵和传感器等仪器的选型。最后设计了2个代表性实验供参考。     

基于t检验的车辆行驶阻力及相关系数可信度分析

通过车辆道路滑行试验及数据处理方法,建立不同的数学模型,采用回归分析法得出滑行阻力的方程式,并用t检验法对相关参数进行了可信度分析,确定了较为准确的滚动阻力和空气阻力,同时验证了GB/T18352.3-2005和GB/T12545.1-2008中经验公式的局限性,从而为底盘测功机标定提供更为准确的行驶阻力。     

传动轴上下跳动极限位置校核

车辆传动轴结构不同,传动系统布置形式不同,影响传动轴长度校核因素各有所异,车辆在不同工况上下跳动时,正确的校核传动轴长度至关重要,若校核方法不当,车辆在不同工况下行驶易使传动轴顶死或脱出,它会直接影响驾乘人员的生命财产安全.对不同结构传动轴的不同布置形式校核方法进行了阐述.     

定靖复线停输再启动过程研究

综合定靖复线管道基础数据及油品物性参数,借助于计算机仿真软件,通过模拟计算确定了定靖复线在不同月份时的最优运行方案。同时,基于定靖复线管道基础参数及安全经济运行方案,对处于夏、冬季环境的管道全线进行了停输再启动过程模拟,分析停输再启动过程中管线运行参数的变化规律,为管道稳态工况运行及停输再启动操作提供参考。     

不同通风口参数下自然通风隧道试验研究

为了对比不同通风口参数下的隧道通风效率及通风口风速,文章通过比例模型试验,使用亚克力板搭建比例尺为1∶15的模型隧道。试验设置4个工况来比较不同通风口数量、长度和高度下隧道通风情况。试验结果表明,不同通风口数量、长度和高度下隧道内风速变化分布以及通风效率发生显著变化。基于试验结果 ,文章建议了最佳通风口的设置形式。     

公路几何形状快速测量的实现

探讨采用快速方式测量公路的几何形状,并通过仪器上传感器的合理配置提高测量精度,用独立测量车的形式制作仪器,来提高测量时外界因素变化带来的测试车辆参数改变所造成的测试精度变化.     

主动悬架系统模式切换控制策略研究

针对在不同工况下车辆行驶时对于主动悬架系统的性能需求,本文设计出一种可切换悬架工作模式的悬架控制策略,可以提高车辆在不同工况下行驶时的动力学性能。通过对控制策略进行建模仿真,结果得出相较于未进行模式切换的悬架,所设计的模式切换控制策略可以有效改善悬架工作时的性能,为后续控制参数的优化提供了研究基础。     

隧道通风设计中火灾释热量的取用

1 引言 隧道通风设计中,一般均简单的按隧道内通行车辆的种类来确定相应的火灾规模、释热量（汽车释热量）。但试验证实,在隧道封闭环境内火灾工况下,所产生的释热量还受到火灾现场环境条件、隧道断面大小、通风方式等影响。所以在实际工程设计中还须考虑相应的释热量增大系数。国外对此旱已开展了多样的试验研究,并取得了一些有价值的数据,它有助于对隧道通风设计中火灾释热量的合理取用,及通风、消防系统科学的有针对性的设计。     

城市道路汽车行驶工况及排放污染物的测试和分析研究

为了适应欧Ⅲ排放法规的需要,针对西安市区城市道路上正常行驶汽车的工况及排放情况进行研究,通过采用GPS测速系统和IPEXD便携式排放测量仪,快速、准确的获取汽车正常行驶过程中的即时速度及瞬间排放污染物等客观数据,进而具体分析汽车在城市道路上的行驶工况及排放情况,最终计算得出西安市城市道路上行驶汽车的相应工况、即时速度与瞬间排放之间的关系。其中,本文主要研究以汽油为燃料的车辆在城市道路条件下行驶时尾气排放中的HC、CO、NOX三种污染物,客观分析并确定日常城市道路条件下汽车行驶工况对其排放的相关影响。     

基于碳平衡原理的天然气汽车燃料消耗量检测方法研究

文章通过分析天然气组份及天然气发动机的燃烧特性,基于碳平衡原理建立了天然气汽车燃料消耗量计算模型。对比分析了闭式和开式碳平衡检测系统的结构工作原理及适用范围,确定采用开式稀释采样方式进行天然气燃料消耗量检测系统开发。结合天然气汽车燃料消耗量计算模型中的技术参数需求,设计开发了碳平衡气耗仪。为了分析设备工作的可靠性和测量的准确性,选用LNG宇通客车和东风危险品运输车作为试验样车,利用科里奥利质量流量计对其进行标定。通过对比试验可知,碳平衡气耗仪与科里奥利质量流量计相对误差为5%,基本满足在用天然气汽车燃料消耗量检测的需求。     

Exhaust emissions and fuel consumption of a triple-fuel spark-ignition engine powered passenger car

This paper examines the influence of compressed natural gas, liquefied petroleum gas and gasoline fuel on the exhaust emissions and the fuel consumption of a spark-ignition engine powered passenger car. The vehicle was driven according to the urban driving cycle and extra urban driving cycle speed profiles with the warmed-up engine. Cause and effect based analysis reveals potential for using different fuels to reduce vehicle emission and deficiencies associated with particular fuels. The highest tank to wheel efficiency and the lowest CO₂ emission are observed with the natural gas fuelled vehicle, that also featured the highest total hydrocarbon emissions and high NO_x emissions because of fast three way catalytic converter aging due the use of the compressed natural gas. Retrofitted liquefied petroleum gas fuel supply systems feature the greatest air-fuel ratio variations that result in the lowest TtW efficiency and in the highest NO_x emissions of the liquefied gas fuelled vehicle.     

Development a new power management strategy for power split hybrid electric vehicles

Reduction of greenhouse gas emission and fuel consumption as one of the main goals of automotive industry leading to the development hybrid vehicles. The objective of this paper is to investigate the energy management system and control strategies effect on fuel consumption, air pollution and performance of hybrid vehicles in various driving cycles. In order to simulate the hybrid vehicle, the combined feedback–feedforward architecture of the power-split hybrid electric vehicle based on Toyota Prius configuration is modeled, together with necessary dynamic features of subsystem or components in ADVISOR. Multi input fuzzy logic controller developed for energy management controller to improve the fuel economy of a power-split hybrid electric vehicle with contrast to conventional Toyota Prius Hybrid rule-based controller. Then, effects of battery’s initial state of charge, driving cycles and road grade investigated on hybrid vehicle performance to evaluate fuel consumption and pollution emissions. The simulation results represent the effectiveness and applicability of the proposed control strategy. Also, results indicate that proposed controller is reduced fuel consumption in real and modal driving cycles about 21% and 6% respectively.     

Eco-driving: An economic or ecologic driving style?

In this work the trade-off between economic, therefore fuel saving, and ecologic, pollutant emission reducing, driving is discussed. The term eco-driving is often used to refer to a vehicle operation that minimizes energy consumption. However, for eco-driving to be environmentally friendly not only fuel consumption but also pollutant emissions should be considered. In contrast to previous studies, this paper will discuss the advantages of eco-driving with respect to improvements in fuel consumption as well as pollutant gas emissions. Simulating a conventional passenger vehicle and applying numerical trajectory optimization methods best vehicle operation for a given trip is identified. With hardware-in-the-loop testing on an engine test bench the fuel and emissions are measured. An approach to integrate pollutant emission and dynamically choose the ecologically optimal gear is proposed.     

The effect of uncertainty on US transport-related GHG emissions and fuel consumption out to 2050

The future of US transport energy requirements and emissions is uncertain. Transport policy research has explored a number of scenarios to better understand the future characteristics of US light-duty vehicles. Deterministic scenario analysis is, however, unable to identify the impact of uncertainty on the future US vehicle fleet emissions and energy use. Variables determining the future fleet emissions and fuel use are inherently uncertain and thus the shortfall in understanding the impact of uncertainty on the future of US transport needs to be addressed. This paper uses a stochastic technology and fleet assessment model to quantify the uncertainties in US vehicle fleet emissions and fuel use for a realistic yet ambitious pathway which results in about a 50% reduction in fleet GHG emissions in 2050. The results show the probability distribution of fleet emissions, fuel use, and energy consumption over time out to 2050. The expected value for the fleet fuel consumption is about 450 and 350 billion litres of gasoline equivalent with standard deviations of 40 and 80 in 2030 and 2050, respectively. The expected value for the fleet GHG emissions is about 1360 and 850 Mt CO₂ equivalent with standard deviation of 130 and 230 in 2030 and 2050 respectively. The parameters that are major contributors to variations in emissions and fuel consumption are also identified and ranked through the uncertainty analysis. It is further shown that these major contributors change over time, and include parameters such as: vehicle scrappage rate, annual growth of vehicle kilometres travelled in the near term, total vehicle sales, fuel economy of the dominant naturally-aspirated spark ignition vehicles, and percentage of gasoline displaced by cellulosic ethanol. The findings in this paper demonstrate the importance of taking uncertainties into consideration when choosing amongst alternative fuel and emissions reduction pathways, in the light of their possible consequences.     

Forecasting light-duty vehicle demand using alternative-specific constants for endogeneity correction versus calibration

We investigate parameter recovery and forecast accuracy implications of incorporating alternative-specific constants (ASCs) in the utility functions of vehicle choice models. We compare two methods of incorporating ASCs: (1) a maximum likelihood estimator that computes ASCs post-hoc as calibration constants (MLE-C) and (2) a generalized method of moments estimator that uses instrumental variables (GMM-IV) to correct for price endogeneity. In a synthetic study we observe significant coefficient bias with MLE-C when the price-ASC correlation (endogeneity) is large. GMM-IV successfully mitigates this bias given valid instruments but exacerbates the bias given invalid instruments. Despite greater coefficient bias, MLE-C yields better forecasts than GMM-IV with valid instruments in most of the cases examined, including most cases where the price-ASC correlation present in the estimation data is absent in the prediction data. In a market study of U.S. midsize sedan sales from 2002 – 2006 the GMM-IV model predicts the 1-year-forward market better, but the MLE-C model predicts the 5-year-forward market better. Including an ASC in predictions by any of the methods proposed improves share forecasts, and assuming that the ASC of each new vehicle matches that of its closest competitor vehicle yields the best long term forecasts. We find evidence that the instruments most frequently used in the automotive demand literature may be invalid.     

船用柴油机12PA6B超负荷性能试验研究

我国船用柴油机功率标准规定柴油机应能够在超负荷功率(即110%标定功率)下连续运转。超负荷工况各参数变化可以反映柴油机的整体性能,是船用柴油机负荷试验的重要工况点。本文通过陕柴重工生产的12PA6B柴油机的负荷试验,研究证实该机型在超负荷工况下能保持较低的燃油消耗率和烟度排放,以及较高的功率和扭矩输出。     

Real-time energy-efficient traffic control via convex optimization

This article proposes a macroscopic traffic control strategy to reduce fuel consumption of vehicles on highways. By implementing Greenshields fundamental diagram, the solution to Moskowitz equations is expressed as linear functions with respect to vehicle inflow and outflow, which leads to generation of a linear traffic flow model. In addition, we build a quadratic cost function in terms of vehicle volume to estimate fuel consumption rate based on COPERT model. A convex quadratic optimization problem is then formulated to generate energy-efficient traffic control decisions in real-time. Simulation results demonstrate significant reduction of fuel consumption on testing highway sections under peak traffic demands of busy hours.     

Platooning for sustainable freight transportation: an adoptable practice in the near future?

ABSTRACT

Platooning is an emerging transportation practice that has the potential to solve the problems of the burgeoning transportation industry. A platoon is a group of vehicles, with vehicle to vehicle communication, that travel closely behind one another such that the platoon can accelerate, brake and cruise together. Platoons can improve road safety, be energy efficient and reduce costs. Its complete socio-economic benefits include congestion mitigation, smoother traffic flow, better lane usage and throughput, incentives for green logistics and driver safety. The long-term effect of platooning on road transportation, if extensively deployed, would be better organised traffic flow and efficient tracking of vehicles on the road ushering a multilevel positive impact on the industry. In this study, we attempt to answer the critical question of whether platooning is an adoptable practice in the near future and discuss an agenda to take platooning closer to implementation on the ground by highlighting the opportunities for future research. We also present a conceptual framework to help researchers, academicians, policy makers and practitioners for the adoption of platooning into the transportation industry.     

Estimating fuel consumption and emissions based on reconstructed vehicle trajectories

Microscopic emission models are widely used in emission estimation and environment evaluation. Traditionally, microscopic traffic simulation models and probe vehicles are two sources of inputs to a microscopic emission model. However, they are not effective in reflecting all vehicles' real‐world operating conditions. Using each vehicle's spot speed data recorded by detectors, this paper provides a new method to estimate all vehicles' real‐world activities data. These data can then be used as inputs to a microscopic emission model to estimate vehicle fuel consumption and emissions. The main task is to reconstruct trajectory of each vehicle and calculate second‐by‐second speed and acceleration from the activities data. The Next Generation Simulation dataset and the Comprehensive Modal Emissions Model are used in this study to calculate and analyze the emission results for both lane‐level and link‐level. The results showed that using the proposed method for estimating vehicle fuel consumption and emissions is promising. Copyright © 2012 John Wiley & Sons, Ltd.