技术站广义配流问题模型与算法

根据列车解编顺序是否确定,将阶段计划中的广义配流问题分为广义静态配流问题和广义动态配流问题。以阶段内发出配流车数最多和车辆在站平均停留时间最短为目标函数,以列车解体开始时刻、车流分配、车流接续和列车编组开始时刻为约束条件,建立广义动态配流问题的多目标非线性混合整数规划模型。综合考虑优先排空、优先发送较近编组去向车流,模拟车站调度员编制阶段计划时的思维过程,设计搜索算法,解决广义静态配流问题(给定列车解编顺序的广义动态配流问题)。以有7个编组去向的某技术站为例,运用该算法可以在较短时间内得到列车解编方案和配流方案,表明了该算法的实用性和可行性。     

Fast-charging station choice behavior among battery electric vehicle users

This study explores how battery electric vehicle users choose where to fast-charge their vehicles from a set of charging stations, as well as the distance by which they are generally willing to detour for fast-charging. The focus is on fast-charging events during trips that include just one fast-charge between origin and destination in Kanagawa Prefecture, Japan. Mixed logit models with and without a threshold effect for detour distance are applied to panel data extracted from a two-year field trial on battery electric vehicle usage in Japan. Findings from the mixed logit model with threshold show that private users are generally willing to detour up to about 1750 m on working days and 750 m on non-working days, while the distance is 500 m for commercial users on both working and non-working days. Users in general prefer to charge at stations requiring a shorter detour and use chargers located at gas stations, and are significantly affected by the remaining charge. Commercial users prefer to charge at stations encountered earlier along their paths, while only private users traveling on working days show such preference and they turn to prefer the stations encountered later when choosing a station in peak hours. Only private users traveling on working days show a strong preference for free charging. Commercial users tend to pay for charging at a station within 500 m detour distance. The fast charging station choice behavior is heterogeneous among users. These findings provide a basis for early planning of a public fast charging infrastructure.     

CATIA VBA二次开发在装配中批量搜索零件的应用

文章针对汽车开发过程中,经常需要对部分特定的零件进行批量选择用于校核或者作为报告用图,给出了装配中对指定的多个零件进行程序搜索选定的方法。在介绍VB编程语言及CATIA二次开发理论的基础上,给出程序自动搜索零件的基本流程,利用CATIA Automation调用Search方法,实现零件的批量搜索。通过实例验证,证明了CATIA批量搜索的优越性。结果表明,CATIA二次开发可以提高工作效率。     

旅游交通融合发展研究——以福建省为例

为深入落实"交通强国"战略和实现"全域旅游"目标,推动旅游与交通深度融合发展,需做好旅游交通体系发展的顶层设计。通过分析旅游交通面临的问题,提出了旅游交通融合发展的理念。将福建省作为案例,针对福建旅游交通网络面临的问题,提出了"快旅慢游"旅游交通体系的建设目标、实施方案及保障措施。依托高铁、民航、邮轮和公路等综合立体交通网络,提出了"一带三环多放射"旅游交通"快旅"通道的发展思路;通过特色旅游产品开发、旅游服务质量提升等方面,规划了"慢游"微循环旅游交通的发展方案,构建了福建省多层次、综合立体的旅游交通体系发展新格局。以期通过福建省旅游交通融合发展案例研究,为其他省市旅游交通融合发展借鉴参考。     

基于正交设计的船用柴油机燃烧系统参数匹配及优化

为研究柴油机燃烧系统参数匹配对柴油机动力和排放性能的影响,首先分别利用AVL_BOOST和AVL_FIRE仿真软件建立4190ZLC-2型船用柴油机整机模型和缸内燃烧高压循环模型,然后基于已建模型应用正交试验设计方法安排柴油机进气系统、喷油系统和燃烧室结构尺寸参数匹配仿真计算。研究结果表明,通过极差分析可以得出燃烧系统参数对4190ZLC-2型柴油机性能的影响主次顺序。以柴油机指示功率为评价指标时,参数组合0.26 mm-28°CA-160°-0.9-145 mm-2.6 mm-22 mm(喷孔直径-喷油提前角-油束夹角-涡流比-喉口直径-凸台高度-凹坑半径)对应的指示功率为63.40 k W,比原机仿真值高15%;以NOX排放为评价指标时,参数组合0.30 mm-24°CA-140°-0.4-135 mm-6.6 mm-14 mm(喷孔直径-喷油提前角-油束夹角-涡流比-喉口直径-凸台高度-凹坑半径)对应的NOX排放质量分数为0.015 7%,比原机仿真值低30.2%。     

多端点不成对机车周转图模型与算法

针对不成对列车运行图编制,在考虑最优性的要求条件下,本文提出适用于多端点不成对机车周转图的实用三步算法,即,首先确定机车交路成对时部分初始解,再分别确定每一个尚未匹配到达车次初始附挂方案,最后进行结果优化．文末提供一个算例,算例证明算法有效。     

基于近似曲率的铁路既有线纵断面分段算法

纵断面线形的精确分段是后续铁路线路优化调整的基础。针对现有方法自动分段效果差且精度低的缺点,研究一种能够实现线形精确自动分段的算法。首先,在对比各种方法的基础上,提出一种基于测点近似曲率的线形自动分段算法,针对铁路竖曲线弧径比过小易导致的拟合病态问题,采用基于半径确定的最小二乘算法进行圆心精确定位,以提高分段点的精度。经实测数据验证该算法能自动化识别特征点位置,且具有更高的精度。     

水基型沥青清洗剂的研究

采用表面活性剂复配技术,经基质材料的性能对比及正交试验分析,开发出能在常温下迅速除去金属表面沥青且环保的水基型清洗剂;进一步,论文探讨了清洗方式、浸泡温度、清洗剂浓度以及浸泡时间等因素对金属表面清洗效果的影响,证实了该清洗剂良好的净洗力,验证了研发的清洗剂作为道路工程界传统沥青清洗剂替代品的可行性.     

异步电机效率优化算法设计

针对异步电机效率优化问题，提出混合在线式直流最小功率模糊搜索效率优化控制算法（FLSC）。算法利用损耗模型控制（LMC）的研究成果，设计新型比例因子提取策略，可以实时在线获得电机各稳态工况下FLSC输入和输出变量的比例因子，预先规划了算法搜索控制的方向，保证了算法的快速收敛性。根据异步电机的特性及先期的综合实验数据分析，对模糊控制用模糊集合及其隶属度函数进行系统化设计，对输入变量的ZE模糊集进行梯形隶属度函数设计，对输出变量进行正负不对称隶属度函数设计，从而解决了系统在效率最优点处的振荡问题。对小功率异步电机系统的计算机仿真及台架实验表明：针对异步电机的轻载运行工况，FLSC算法能显著提高异步电机系统的控制性能；对于异步电机转子电阻参数变化的工况也具有很好的鲁棒性。     

Experimental design influences on stated choice outputs: An empirical study in air travel choice

Discrete choice experiments are conducted in the transport field to obtain data for investigating travel behaviour and derived measures such as the value of travel time savings. The multinomial logit (MNL) and other more advanced discrete choice models (e.g., the mixed MNL model) have often been estimated on data from stated choice experiments and applied for planning and policy purposes. Determining efficient underlying experimental designs for these studies has become an increasingly important stream of research, in which the objective is to generate stated choice tasks that maximize the collected information, yielding more reliable parameter estimates. These theoretical advances have not been rigorously tested in practice, such that claims on whether the theoretical efficiency gains translate into practice cannot be made. Using an extensive empirical study of air travel choice behaviour, this paper presents for the first time results of different stated choice experimental design approaches, in which respective estimation results are compared. We show that D-efficient designs keep their promise in lowering standard errors in estimating, thereby requiring smaller sample sizes, ceteris paribus, compared to a more traditional orthogonal design. The parameter estimates found using an orthogonal design or an efficient design turn out to be statistically different in several cases, mainly attributed to more or less dominant alternatives existing in the orthogonal design. Furthermore, we found that small designs with a limited number of choice tasks performs just as good (or even better) than a large design. Finally, we show that theoretically predicted sample sizes using the so-called S-estimates provide a good lower bound. This paper will enable practitioners in better understanding the potential benefits of efficient designs, and enables policy makers to make decisions based on more reliable parameter estimates.