气体燃料/汽油两用燃料汽车自适应燃料点火器

气体燃料 /汽油两用燃料汽车燃用不同燃料时 ,最佳点火提前角相差悬殊。采用自适应燃料点火器可根据发动机使用燃料的不同自动改变点火提前角。论述了单片机控制自适应燃料点火器的软、硬件结构和工作原理。试验结果表明 ,加装自适应燃料点火器后 ,发动机动力性增加 2 .6%～3.1 % ,燃料消耗率下降 2 .6%～ 3.4%。     

参数自适应DAHLIN调节器

本文提出了一种新的数字控制算法,它是基于Dahlin数字控制算法和递推自适应策略,它能同时辨识和过程时滞,并具有自动整定调节器参数的功能。仿真结呆表明,它具有良好的鲁棒性,克服了由于模型失配时的DDahlin调节器性能的降低,该算法对于大时滞、慢时变的工业过程控制是可行的和有效的。     

基于虚拟信号控制的交叉口群协调方法研究

为降低环形交叉口的平均延误时间,提高交叉口群车辆通行效率,以环形交叉口为研究对象,通过引入"虚拟信号控制环形交叉口"概念,对到达环岛的交通流进行错时分离,其次应用数解法提出主路径车流双向绿波协调控制方案,建立了基于主路径车流双向绿波协调控制的交叉口群相位差模型,最后利用VISSIM仿真软件对云南省曲靖市珠江源大道与建宁东路环形交叉口进行验证.结果表明:虚拟状态下主路径车辆通过环形交叉口数由66.36提高至88.69辆/100 s;车辆在环形交叉口平均停车次数为0.57次,较实际降低了10.9%;车辆平均延误时间较实际降低了23.8%;建立的交叉口群相位差模型能够较好地改善各个交叉口的延误效益.     

大容量RTU系统遥信采集实时性问题研究

本文针对电气化铁道牵引供电运动监控系统中运方数据采集和控制单元，分析了目前影响ＲＴＵ系统遥信采集实时性能的主要原因，指出了对大容量ＲＴＵ系统，缩短遥信采集任务处理时间的必要。本文还提出了四种提高ＲＴＵ系统实时性的改进方案，并对这些方案加以较详细的论述。     

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通过对行人过街的三种情况即自由过街、无控制人行横道过街和信号控制人行横道过街进行研究，分析了不同过街条件下行人与机动车的运行特征。设定行人与机动车到达间距服从负指数分布，给出了不同条件下的机动车延误计算方法。研究结果表明，对行人过街选择合适的过街方式可以有效减少机动车的延误，特别是在行人与机动车交通量比较大时，设置人行横道（包括信号控制与无信号控制）可以大幅度减少机动车的延误。     

延误条件下地铁车站客流的引导需求分析及信息服务对策

在高客流负荷和网络化运营条件下,列车延误会导致短时段内车站滞留客流激增,为防范拥塞导致的安全风险,地铁车站会启动预案及时引导客流。从乘客感知角度出发,调查并分析列车延误条件下乘客的出行计划改变意愿、信息需求偏好,研究表明,在不同程度的列车延误情景下,乘客出行计划改变及决策所需的信息需求存在显著差异。对站内客流引导服务现状进行调查,结果表明,乘客对于人工引导的依赖性最高,现有信息化引导措施与乘客的期望尚存差距。在此基础上,提出延误客流信息服务综合提升对策,以提升延误条件下乘客信息服务满意水平。     

基于混沌理论的铁路客货运量预测研究

应用混沌理论的相空间重构方法,分析与铁路运量相关的12组时间序列,分别计算它们的嵌入延迟时间、嵌入维数、关联维数、最大Lyapunov指数等混沌统计量,并以此为依据判断12组时间序列的混沌特性。结果显示:铁路客货运量及周转量不具有混沌特性,对应的4组时间序列不是混沌的;铁路客货运量、周转量的增量及增长率都具有明显的混沌特性,它们对应的8组时间序列是混沌的。在识别是否混沌的基础上,应用基于最大Lyapunov指数预测方法,对铁路客货运量、周转量进行预测检验及预测结果分析。     

分布式网络控制系统的输出反馈控制

建立了同时具有前向通道传输时延和反馈通道传输时延的线性分布式网络控制系统的数学模型.用该数学模型将系统变换为具有状态与控制时变时滞的线性时滞系统.基于代数Riccati方程方法,提出了H∞鲁棒输出反馈控制方法,以使系统闭环控制稳定.仿真算例结果表明,在t=2.5 s时,系统状态都达到了0,保证了系统具有较快的零状态响应速度.给出了这类系统的H∞鲁棒输出反馈控制器的综合设计示例.     

A methodology for identifying similar days in air traffic flow management initiative planning

This article describes a methodology for selecting days that are comparable in terms of the conditions faced during air traffic flow management initiative planning. This methodology includes the use of specific data sources, specific features of calendar days defined using these data sources, and the application of a specific form of classification and then cluster analysis. The application of this methodology will produce results that enable historical analysis of the use of initiatives and evaluation of the relative success of different courses of action. Several challenges are overcome here including the need to identify the appropriate machine learning algorithms to apply, to quantify the differences between calendar days, to select features describing days, to obtain appropriate raw data, and to evaluate results in a meaningful way. These challenges are overcome via a review of relevant literature, the identification and trial of several useful models and data sets, and careful application of methods. For example, the cluster analysis that ultimately selects sets of similar days uses a distance metric based on variable importance measures from a separate classification model of observed initiatives. The methodology defined here is applied to the New York area, although it could be applied by other researchers to other areas.     

Modeling delay at signalized intersections with channelized right‐turn lanes considering the impact of blockage

This paper presents a probabilistic delay model for signalized intersections with right‐turn channelization lanes considering the possibility of blockage. Right‐turn channelization is used to improve the capacity and to reduce delay at busy intersections with a lot of right‐turns. However, under heavy traffic conditions the through vehicles will likely block the channelization entrance that accrues delay to right‐turn vehicles. If the right‐turn channelization gets blocked frequently, its advantage in reducing the intersection delay is neglected and as a result the channelization lane becomes inefficient and redundant. The Highway Capacity Manual (HCM) neglects the blockage effect, which may be a reason for low efficiency during peak hours. More importantly, using HCM or other standard traffic control methods without considering the blockage effects would lead to underestimation of the delay. To overcome this issue, the authors proposed delay models by taking into account both deterministic and random aspects of vehicles arrival patterns at signalized intersections. The proposed delay model was validated through VISSIM, a microscopic simulation model. The results showed that the proposed model is very precise and accurately estimates the delay. In addition, it was found that the length of short‐lane section and proportion of right‐turn and through traffic significantly influence the approach delay. For operational purposes, the authors provided a step‐by‐step delay calculation process and presented approach delay estimates for different sets of traffic volumes, signal settings, and short‐lane section lengths. The delay estimates would be useful in evaluating adequacy of the current lengths, identifying the options of extending the short‐lane section length, or changing signal timing to reduce the likelihood of blockage. Copyright © 2016 John Wiley & Sons, Ltd.