Using GPS-data to determine optimum electric vehicle ranges: A Michigan case study

Fuel-switching personal transportation from gasoline to electricity offers many advantages, including lower noise, zero local air pollution, and petroleum-independence. But alleviations of greenhouse gas (GHG) emissions are more nuanced, due to many factors, including the car’s battery range. We use GPS-based trip data to determine use type-specific, GHG-optimized ranges. The dataset comprises 412 cars and 384,869 individual trips in Ann Arbor, Michigan, USA. We use previously developed algorithms to determine driver types, such as using the car to commute or not. Calibrating an existing life cycle GHG model to a forecast, low-carbon grid for Ann Arbor, we find that the optimum range varies not only with the drive train architecture (plugin-hybrid versus battery-only) and charging technology (fast versus slow) but also with the driver type. Across the 108 scenarios we investigated, the range that yields lowest GHG varies from 65 km (55+ year old drivers, ultrafast charging, plugin-hybrid) to 158 km (16–34 year old drivers, overnight charging, battery-only). The optimum GHG reduction that electric cars offer – here conservatively measured versus gasoline-only hybrid cars – is fairly stable, between 29% (16–34 year old drivers, overnight charging, battery-only) and 46% (commuters, ultrafast charging, plugin-hybrid). The electrification of total distances is between 66% and 86%. However, if cars do not have the optimum range, these metrics drop substantially. We conclude that matching the range to drivers’ typical trip distances, charging technology, and drivetrain is a crucial pre-requisite for electric vehicles to achieve their highest potential to reduce GHG emissions in personal transportation.     

Electric vehicle charging station locations: Elastic demand,station congestion,and network equilibrium

Battery-only electric vehicles (BEVs) generally offer better air quality through lowered emissions, along with energy savings and security. The issue of long-duration battery charging makes charging-station placement and design key for BEV adoption rates. This work uses genetic algorithms to identify profit-maximizing station placement and design details, with applications that reflect the costs of installing, operating, and maintaining service equipment, including land acquisition. Fast electric vehicle charging stations (EVCSs) are placed across a congested city's network subject to stochastic demand for charging under a user-equilibrium traffic assignment. BEV users’ station choices consider endogenously determined travel times and on-site charging queues. The model allows for congested-travel and congested-station feedback into travelers’ route choices under elastic demand and BEV owners’ station choices, as well as charging price elasticity for BEV charging users.Boston-network results suggest that EVCSs should locate mostly along major highways, which may be a common finding for other metro settings. If 10% of current EV owners seek to charge en route, a user fee of $6 for a 30-min charging session is not enough for station profitability under a 5-year time horizon in this region. However, $10 per BEV charging delivers a 5-year profit of $0.82 million, and 11 cords across 3 stations are enough to accommodate a near-term charging demand in this Boston-area application. Shorter charging sessions, higher fees, and/or allowing for more cords per site also increase profits generally, everything else constant. Power-grid and station upgrades should keep pace with demand, to maximize profits over time, and avoid on-site congestion.     

基于RFID电子车牌数据的公交行程时间预测方法

为了给公交优先信号配时系统提供足够的"思考"时间和准确的控制依据,基于重庆市RFID电子车牌数据提出了一种采用自适应渐消卡尔曼滤波和小波神经网络组合模型动态预测公交行程时间的方法。综合分析公交行程时间的动态和静态影响因素,选取的模型输入参量为标准车流量、路段车辆平均行程时间、平均车速离散性和前班次公交行程时间。利用RFID电子车牌系统采集重庆市鹅公岩大桥路段车辆行驶数据,选取3 000组实际运行数据完成公交行程时间预测模型的训练,另筛选50组数据验证模型的有效性和准确性。研究结果表明：组合模型可动态自适应预测公交行程时间,预测值平均相对误差为3.23%,绝对误差集中在8 s左右,明显优于2种单一模型和基于传统GPS数据的公交行程时间预测模型,可认为选择RFID电子车牌数据作为组合模型的输入,能够明显改善模型预测精度;组合模型预测值的残差分布更为集中、鲁棒性较好,泛化能力强。选择平均绝对误差值、均方根误差值和平均绝对百分比误差作为模型评价指标,结果进一步表明,组合模型的综合预测效果明显优于单一的自适应渐消卡尔曼滤波和小波神经网络。研究方案可为先进公交信息化系统提供良好的技术支撑。     

汽车排放污染及净化对策研究

阐述汽车排放污染物的成分及其危害,介绍新排放法规Ⅰ型、Ⅲ型、Ⅳ型试验限值,重点分析汽车的5项排放影响因素及其净化措施。     

适于TBM施工的HSP法实时预报技术设计与实现

为实现TBM施工隧道的实时地质预报,以TBM刀盘滚刀破岩震动作为震源的HSP法地质预报技术为基础,通过分析TBM施工工艺与机身结构特点,对HSP系统硬件和软件进行优化设计,使其小型化、自动化和智能化,并搭载于TBM上进行智能控制。在TBM掘进过程中,首先,通过隧道轮廓位置的检波器连续或高频次地采集地震反射波信号; 然后,经系统软件对数据的自动处理,实时获取掌子面前方地层反射特征参数图谱; 其次,通过智能识别技术完成对不良地质反射界面的有效拾取与判识; 最后,实现不良地质的探测。通过对适于TBM施工的HSP法实时预报技术进行优化设计,实时探查前方地层不良地质(体)位置、规模与性质,为TBM的高效施工起到一定的推助作用。     

里海远洋渔船无人机舱系统研究

针对我国远洋渔船装备落后、操纵性差、机舱环境恶劣、电站管理水平低、劳动强度大以及渔船机舱自动化水平低等问题,介绍里海远洋渔船无人机舱系统的设计与组成。通过采用主机遥控系统、电站功率管理系统、机舱监测报警系统以及网络通信等技术,将自动化、电气化、信息化和智能化控制技术等船舶前沿科技应用于实船,构建一个满足法国船级社(BV)机舱自动化最高等级AUT-UMS要求的无人机舱系统,以提高远洋渔船的操控性、安全性和可靠性,提升供电系统自动化管理水平,改善作业人员工作环境。对该自动化系统的效果和特点进行分析,结果可为我国远洋渔船自动化系统的研究提供策略和思路。     

Shared autonomous electric vehicle (SAEV) operations across the Austin,Texas network with charging infrastructure decisions

Shared autonomous vehicles, or SAVs, have attracted significant public and private interest because of their opportunity to simplify vehicle access, avoid parking costs, reduce fleet size, and, ultimately, save many travelers time and money. One way to extend these benefits is through an electric vehicle (EV) fleet. EVs are especially suited for this heavy usage due to their lower energy costs and reduced maintenance needs. As the price of EV batteries continues to fall, charging facilities become more convenient, and renewable energy sources grow in market share, EVs will become more economically and environmentally competitive with conventionally fueled vehicles. EVs are limited by their distance range and charge times, so these are important factors when considering operations of a large, electric SAV (SAEV) fleet.This study simulated performance characteristics of SAEV fleets serving travelers across the Austin, Texas 6-county region. The simulation works in sync with the agent-based simulator MATSim, with SAEV modeling as a new mode. Charging stations are placed, as needed, to serve all trips requested (under 75 km or 47 miles in length) over 30 days of initial model runs. Simulation of distinctive fleet sizes requiring different charge times and exhibiting different ranges, suggests that the number of station locations depends almost wholly on vehicle range. Reducing charge times does lower fleet response times (to trip requests), but increasing fleet size improves response times the most. Increasing range above 175 km (109 miles) does not appear to improve response times for this region and trips originating in the urban core are served the quickest. Unoccupied travel accounted for 19.6% of SAEV mileage on average, with driving to charging stations accounting for 31.5% of this empty-vehicle mileage. This study found that there appears to be a limit on how much response time can be improved through decreasing charge times or increasing vehicle range.     

Historic vehicles: an overview from a transport policy perspective

Historic vehicles (HVs) are the heritage of road transport that have surprisingly received little attention in the academic literature. This study presents an overview of the literature on HVs, focusing on the three topics that dominate the policy debate on transport: environmental, safety and congestion impacts. We observed that polluting emissions of HVs are per kilometre much higher (often a factor 5 or more) than those of moderns vehicles. The annual average mileage per vehicle per year of HVs is much lower than other vehicles. The lower active and passive safety levels of HVs are compensated by the way these vehicles are driven, resulting in the risk factors per kilometre being roughly equal or lower than other vehicles. The contribution of HVs to congestion is negligible. However, the transport policy discourse is divided on the topic of HVs. More comprehensive and effective laws and regulation are needed to protect this aspect of the heritage of road transport whilst concurrently avoiding or limiting the problems caused by them.     

港口高杆灯的无线智能控制系统设计

随着港口建设规模的扩大,港区堆场面积越来越大,配套的高杆灯及其他照明设施的数量也相应增加,需要一个自动化的、科学的管理方式和系统对其进行管理和控制。照明无线智能控制系统采用先进可靠的远距离无线通信技术,将人机操作界面和远程控制环节有机结合起来,实现对高杆灯的远距离无线控制。通过高杆灯无线智能控制系统,合理组合开启灯具数量和安排开启时间,智能调光,以达到高效节能、安全运行的良好效果。     

基于磁流变弹性体的船舶轴系纵振动力吸振器的实验研究

磁流变弹性体是一种新型的智能材料,由微米级的羰基铁粉和聚合物合成.由于它具有弹性模量可调、无需封装、稳定性好、响应快等优点,已被广泛应用于机械振动控制等领域.文中针对船舶推进轴系纵振动力学特性,提出一种固有频率可调的磁流变弹性体动力吸振器用于轴系纵振控制.首先理论分析了安装动力吸振器的推进轴系的动力学模型,其次对动力吸振器进行了移频特性试验,并在1:4的船舶轴系缩比模型上进行了变转速工况下吸振效果试验.实验结果表明,该吸振器具有12.3 Hz的移频范围,并且在不同轴系工作转速下相比于被动式吸振器均有更好的吸振效果.