【作者】 张富兴；

【导师】 乔维高； 李孟良；

【作者基本信息】 武汉理工大学 ， 车辆工程， 2005， 硕士

【摘要】 随着汽车环保节能技术的深入研究，新能源汽车不断出现。为了满足新型车辆开发或认证以及检查维护制度的需要，迫切要求具有能体现本地区车辆行驶特征的代表性工况。本文以科技部863课题“典型城市车辆实际行驶工况的研究”为依托，阐述城市车辆行驶工况的开发方法及相关研究。 行驶工况的研究历时两年的时间，对我国北京、上海和广州三个典型城市的乘用车和公交车分年度各进行了两轮共六次车辆实际行驶状况的调查，获得了大量的城市车辆行驶数据，依据统计学相关理论专门编写了解析程序进行数据的处理和分析并构建出所需代表性工况。同时对研究成果与国际上常用工况进行对比分析。 试验线路的确定是行驶工况调查的关键环节。乘用车城市工况调查是以城市道路级别划分、交通流量调查为主要依据确定试验路段；公交车是根据城市公交调查资料，运用交通研究领域的“路段频度和覆盖率”的概念规划试验线路。车辆行驶状况路上调查采用分时段交错法进行，并使用具有高精度的可跟踪滤波的非接触式速度传感器等先进设备采集数据。 数据分析处理以主成分分析、聚类分析等多元统计分析理论为工具，先将试验数据划分为一系列运动学片段，并求取各片段的36个特征值(如行程、速度、加速度、速度标准偏差、加速度标准偏差等)，形成片段数据库；然后据此进行主成分分析从众多特征值中提取关键因素，按照主成分聚类；城市代表性工况按相应类的比例提取运动学片段，按设定条件组建行驶工况，并以图形的形式显示。以上过程由基于MATLAB自主开发的专用工况解析软件VDCAP来完成。 不同城市的数据解析结果表明：不同城市车辆行驶状况存在一定的差异，其平均速度、怠速比例等均有所不同，但差异不大；不同季节车辆行驶也存在差异。总体趋势来看，具备形成我国统一的城市行驶工况的基础。 行驶工况的研究结果表现为速度—时间曲线，鉴于目前存在的模态和瞬态两种型式各有优缺点，本文结果采用局部模态化的处理方法，使工况曲线即符合实际情形又便于试验操作。对曲线特征分析表明我国城市车辆行驶具有自己的特征，其特征参数居于国际常用工况(如FTP75、ECE+EUDC和Japan10.15以及国外大城市公交车行驶工况)之间。更多还原

【Abstract】 Along with the advanced study of environment protection and saving energy technology, vehicles with nontraditional energy come up. We need deeply representative driving cycles witch can describe regional vehicle driving character, in order to develop or certificate new automobile or take inspection/maintenance. The paper describes development method and relative research of vehicle driving cycle, according to 863 project-study of vehicle real driving cycles of typical city.Driving cycles research took two years to investigate passenger car and bus driving data of three typical city: Beijing, Shanghai and Guangzhou. As a result, we took investigation six times and obtained enough driving data. Representative driving cycles are formed after data processing, according to correlative statistical theory and using special program. At the same time, our research result is compared with international driving cycles.Confirming test routes is crucial step of driving investigation. Routes of city passenger car are confirmed by city street grade and traffic flow; witch of bus are decided by bus investigating information, beside with "route frequency and covering rate" that from traffic area. Vehicle real driving investigation comes up with time section cross method, and uses advanced instruments such as non-contacted speed sensor with tracking filter etc.Data analyses processing takes the multivariate statistical analysis tools such as principal composition analysis and clustering analysis etc. Firstly the processing partitions driving data into kinetic sequences, and calculates 36 eigenvalue of every sequence (such as driving distance, average speed, acceleration, speed standard deviation, acceleration standard deviation etc. ), and comes into being sequence database. Secondly several principal composition are drawn out from much eigenvalue, in this way, clustering analysis comes out according to several principal composition. Finally city driving cycles are formed by special sequences witch are drawn out by cluster rate and in accord with expected condition, at the same time, the cycles figure show. The special program VDCAP carry above function out that program with MATLAB.Result from different city show that vehicle driving condition belong to different city is diverse, and average speed and idle rate are not uniform, but their difference is small; and that every seasonal driving condition has their character. Generally speaking, we can establish uniform test cycles for our country.Speed-time curve is the showing result of driving cycles result. Because present cycles have two type: transient and modular type, this paper adopts theiradvantage and use local modular processing, in order that driving curve is true of real-world and operate expediently. Analyzing to our domestic curve shows that our driving cycles have private character, and that their eigenvalue are among international driving cycles(such as FTP75, ECE+EUDC and JapanlO. 15 as well as abroad other major city bus driving cycles).更多还原