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.     

Socially optimal electric driving range of plug-in hybrid electric vehicles

This study determines the optimal electric driving range of plug-in hybrid electric vehicles (PHEVs) that minimizes the daily cost borne by the society when using this technology. An optimization framework is developed and applied to datasets representing the US market. Results indicate that the optimal range is 16 miles with an average social cost of $3.19 per day when exclusively charging at home, compared to $3.27 per day of driving a conventional vehicle. The optimal range is found to be sensitive to the cost of battery packs and the price of gasoline. When workplace charging is available, the optimal electric driving range surprisingly increases from 16 to 22 miles, as larger batteries would allow drivers to better take advantage of the charging opportunities to achieve longer electrified travel distances, yielding social cost savings. If workplace charging is available, the optimal density is to deploy a workplace charger for every 3.66 vehicles. Moreover, the diversification of the battery size, i.e., introducing a pair and triple of electric driving ranges to the market, could further decrease the average societal cost per PHEV by 7.45% and 11.5% respectively.     

Heterogeneous hazard model of PEV users charging intervals: Analysis of four year charging transactions data

Public charging infrastructure represents a key success factor in the promotion of plug-in electric vehicles (PEV). Given that a large initial investment is required for the widespread adoption of PEV, many studies have addressed the location choice problem for charging infrastructure using a priori simple assumptions. Ideally, however, identifying optimal locations of charging stations necessitates an understanding of charging behavior. Limited market penetration of PEV makes it difficult to grasp any regularities in charging behavior. Using a Dutch data set about four-years of charging transactions, this study presents a detailed analysis of inter-charging times. Recognizing that PEV users may exhibit different charging behavior, this study estimates a latent class hazard duration model, which accommodates duration dependence, unobserved heterogeneity and the effects of time-varying covariates. PEV users are endogenously classified into regular and random users by treating charging regularity as a latent variable. The paper provides valuable insights into the dynamics of charging behavior at public charging stations, and which strategies can be successfully used to improve the performance of public charging infrastructure.     

Predicting market potential and environmental benefits of deploying electric taxis in Nanjing,China

This paper investigates the market potential and environmental benefits of replacing internal combustion engine (ICE) vehicles with battery electric vehicles (BEVs) in the taxi fleet in Nanjing, China. Vehicle trajectory data collected by onboard global positioning system (GPS) units are used to study the travel patterns of taxis. The impacts of charger power, charging infrastructure coverage, and taxi apps on the feasibility of electric taxis are quantified, considering taxi drivers’ recharging behavior and operating activities. It is found that (1) depending on the charger power and coverage, 19% (with AC Level 2 chargers and 20% charger network coverage) to 56% (with DC chargers and 100% charger network coverage) of the ICE vehicles can be replaced by electric taxis without driving pattern changes; (2) by using taxi apps to find nearby passengers and charging stations, drivers could utilize the empty cruising time to charge the battery, which may increase the acceptance of BEVs by up to 82.6% compared to the scenario without taxi apps; and (3) tailpipe emissions in urban areas could be significantly reduced with taxi electrification: a mixed taxi fleet with 46% compressed-natural-gas-powered (CNG) and 54% electricity-powered vehicles can reduce the tailpipe emissions by 48% in comparison with the fleet of 100% CNG taxis.     

On the variance of recurrent traffic flow for statistical traffic assignment

This paper generalizes and extends classical traffic assignment models to characterize the statistical features of Origin-Destination (O-D) demands, link/path flow and link/path costs, all of which vary from day to day. The generalized statistical traffic assignment (GESTA) model has a clear multi-level variance structure. Flow variance is analytically decomposed into three sources, O-D demands, route choices and measurement errors. Consequently, optimal decisions on roadway design, maintenance, operations and planning can be made using estimated probability distributions of link/path flow and system performance. The statistical equilibrium in GESTA is mathematically defined. Its multi-level statistical structure well fits large-scale data mining techniques. The embedded route choice model is consistent with the settings of O-D demands considering link costs that vary from day to day. We propose a Method of Successive Averages (MSA) based solution algorithm to solve for GESTA. Its convergence and computational complexity are analyzed. Three example networks including a large-scale network are solved to provide insights for decision making and to demonstrate computational efficiency.     

土压平衡盾构施工中泡沫改良砾砂土的试验研究

为了解决土压平衡盾构在砾砂土地层掘进过程中,土体塑流性差、刀盘及螺旋输送机磨损严重和开挖面平衡不易保持等问题,通过自制泡沫发生器发泡,对砾砂土地层的泡沫改良技术进行室内试验研究,分析气液比、含水率和泡沫掺量对塑流性的影响和改良前后土样的渗透系数的变化规律,得出泡沫发生器气液比在30∶1~55∶1、含水率为5%~12.5%、泡沫掺量为20%~40%时,土体具有较好的塑流性,泡沫的"轴承效应"和泡沫剂中表面活性剂的亲水基团与水、砾砂土颗粒形成的氢键是塑流性提高的根本原因;使用泡沫剂改良砾砂土后,渗透系数大幅降低,掺泡沫后在280 min内渗透系数随时间变化较小,能达到10~(-5)cm/s,泡沫剂溶液中高分子化合物的联结和液桥力是土样具有堵水作用的原因。     

基于小波和粒子群算法的HEV行驶状况辨识方法研究

针对混合动力汽车(HEV)行驶状况(道路坡度和整车载荷)变化难以有效识别,导致驱动系统控制策略不能有效满足驾驶员意图问题,以混联式HEV为研究对象,提出了基于小波滤波和粒子群算法的HEV行驶状况辨识方法。首先建立了汽车行驶状况辨识模型,采用最小二乘法确立了优化目标函数,其次研究了基于小波滤波和粒子群算法的HEV行驶状况辨识原理,最后进行了行驶状况粒子群智能算法辨识试验。在采集实车数据的基础上,对实车数据进行小波滤波,并运用行驶状况辨识方法对道路坡度和整车载荷进行了辨识,并对辨识结果进行小波滤波,结果表明,试验工况下整车载荷辨识的相对误差绝对平均值为2.71%,道路坡度辨识的相对误差绝对平均值为3.85%,验证了所提出方法的有效性。     

基于名义应力法的动车组车体净水箱吊装部件疲劳强度分析

针对高速运行动车组车体悬挂设备振动疲劳损伤问题,以某型动车组车顶净水箱吊装结构为研究对象,采用名义应力法对吊装结构的焊缝部位进行疲劳强度评估.根据EN 12663标准确定净水箱的工作载荷工况,采用有限元法计算了各工况下结构的振动响应,并基于BS标准计算了焊缝疲劳评估点的寿命.假定各载荷工况出现频率相同的情况下,构造了工作载荷历程,采用Fe-safe软件对焊缝的疲劳寿命进行了仿真分析.两种方法分析结果均表明:焊缝1与焊缝2寿命最低,是结构最易发生疲劳破坏的位置;焊缝位于筋板表面的焊趾寿命低于位于主支撑板表面的焊趾寿命.     

EA4T车轴钢的超声冲击表面强化

利用超声冲击设备对EA4T车轴钢进行了表面强化处理.采利用金相显微镜和透射电镜表征了车轴钢表面结构的变化,并对超声冲击处理前后试样表面粗糙度和显微硬度进行了分析.结果表明:经超声冲击处理后,试样表面发生了剧烈的塑性变形,晶粒明显细化,显微硬度呈梯度化.随着超声冲击功率的增加,变形层厚度增加,粗糙度减小,表面硬度增大;与未经超声冲击处理的试样相比,在超声冲击功率180瓦作用下,表面粗糙度降低了6.5倍,试样的表面硬度提高了25%,变形层厚度大约为80μm.     

冰区航行船舶电力推进轴系机电耦合的扭振分析

通过螺旋桨桨叶与冰块的相互作用过程,建立单冰块对螺旋桨扭转振动的激励函数;同时建立机电耦合振动数学模型,推导得到机电耦联动力学方程,研究电机电磁激励力对扭转振动的影响。以3500吨科考船电力推进轴系为研究对象,基于冰载荷激励力和电磁激励力对轴系扭转振动进行分析,为复杂的船舶电力推进轴系在冰区航行时的振动研究奠定了基础。