基于GPS的北京市私人乘用车出行特征研究

发布时间：2018-05-04 03:10

本文选题：GPS + 私人乘用车　；参考：《清华大学》2013年硕士论文

【摘要】：北京市高达500万辆的汽车保有量，导致了车用能源消耗量的大幅增加和尾气排放引发的环境问题加剧。以纯电驱动为代表的新能源汽车具有显著降低传统车用燃料消耗和区域范围内直接污染物排放的优势，成为今后技术研发和产业化发展的重点。在目前车用动力电池较低的能量密度技术水平和较高的生产成本下，根据车辆出行特征优化新能源汽车的关键参数，对于其产业化快速推进具有重要的意义；同时出行特征也是评估电能和液体燃料在车用能源中构成比例的关键影响因素之一。本文旨在通过先进的GPS技术研究北京市私人乘用车的出行特征，包括里程分布和行驶工况两部分内容。首先，搭建了基于GPS的出行特征数据库平台，采用被动式调查方法客观真实的获取志愿车日常出行数据；其次，进行了出行特征的时空分析，包括里程分布、时间分布和频次分布在工作日与非工作日的差异；第三，根据里程分布，进行了电动汽车的里程适用性和平均能耗评价的分析；最后，使用运动学片段合成法完成了北京市不同运行工况的构建和比较。本研究的主要成果：第一，完成了2012年6月至2013年3月间北京市112辆私人乘用车2003车天、4892次出行，总计1×10~5km的出行数据采集和有序储存。第二，北京市私人乘用车的日出行里程服从伽玛分布，工作日和双休日的伽玛分布参数不同，形状参数分别为1.20和1.25，尺度参数分别为3.83×10~(-2)和3.12×10~(-2)；非节假日的出行里程为35.4km，工作日、双休日、节假日分别为31.4km、39.1km和48.0km；日均出行时间为1.6h，，每天平均出行2.4次，每次平均出行14.6km。第三，对于续驶里程为50km的纯电动汽车，单次充电能满足78%的非节假日出行，两次充电提高到93%；同时，基于里程分布完成了北京地区插电式混合动力汽车（PHEV）的效用因子（UF）公式拟合回归，分析了PHEV在北京的实际燃油消耗比在美国低的主要原因。第四，北京三环内区域上下班高峰期和五环外区域非高峰期的工况特征具有显著的差异性，主要参数分别是怠速时间比例为41%和26%、平均行驶速度为26km/h和31km/h、平均加速度为0.7m/s~2和0.6m/s~2等。
[Abstract]:The amount of 5 million cars in Beijing is up to 5 million vehicles, which has led to a sharp increase in energy consumption and the aggravation of environmental problems caused by exhaust emissions. The new energy vehicle driven by YISHION electric drive has the advantage of significantly reducing the consumption of traditional vehicle fuel and the discharge of direct pollutants in the region, and becoming a technology research and development and industry in the future. At present, under the low energy density technology level and high production cost of vehicle power battery, the key parameters of the new energy vehicle are optimized according to the vehicle travel characteristics, and it is of great significance for the rapid industrialization of the vehicle. At the same time, the travel characteristics also evaluate the composition of the power and the liquid fuel in the vehicle energy. One of the key factors affecting the proportion is the study of the travel characteristics of Beijing private passenger car through advanced GPS technology, including two parts of mileage distribution and driving condition.
First, a GPS based travel feature database platform is built, and the passive survey method is used to objectively and objectively obtain the daily travel data of the voluntary vehicle. Secondly, the time and space analysis of the travel characteristics is carried out, including the mileage distribution, the time distribution and the frequency distribution difference between the working day and the non working day. Third, according to the mileage distribution, it is carried out. The suitability of electric vehicle mileage and the evaluation of average energy consumption are analyzed. Finally, the construction and comparison of different operating conditions in Beijing are completed by using the kinematic fragment synthesis method.
The main results of this study are as follows: first, we completed 112 private passenger cars in Beijing from June 2012 to March 2013, with a total of 2003 car days, 4892 trips, a total of 1 x 10~5km travel data collection and orderly storage. Second, the daily trip mileage of the private passenger cars in Beijing is subject to gamma distribution, and the gamma distribution parameters of the working day and the double weekend are different. The parameters are 1.20 and 1.25 respectively, and the scale parameters are 3.83 x 10~ (-2) and 3.12 x 10~ (-2) respectively. The trip mileage of non holiday is 35.4km, working day, and holiday is 31.4km, 39.1km and 48.0km, the average daily travel time is 1.6h, the average trip is 2.4 times a day, the average travel is 14.6km. third, and the driving mileage is 50km pure. The electric vehicle can meet 78% non holiday trip and two charge to 93%. At the same time, based on the mileage distribution, the utility factor (UF) formula regression of the intercalation hybrid electric vehicle (PHEV) in Beijing is completed, and the main reason that the actual burning oil consumption of PHEV in Beijing is lower than that in the United States is analyzed. Fourth, in the third ring of Beijing. There are significant differences between the peak period of regional work and the non peak period of the five rings. The main parameters are 41% and 26%, the average speed is 26km/h and 31km/h, the average acceleration is 0.7m/s~2 and 0.6m/s~2.

【学位授予单位】：清华大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：P228.4;U491

【参考文献】