齐齐哈尔市中心城区电动汽车及充电设施需求预测研究

在目前能源危机和环境保护的双重制约下,发展电动汽车已经成为解决能源环境问题的新途径。为适应未来电动汽车快速发展的需要及充电设施的合理规划布局,电动汽车及充电设施的需求预测就显得尤为重要。文中分析了影响齐齐哈尔市电动汽车发展规模的影响因素,结合国内其他省市的经验,考虑齐齐哈尔市实际情况,对齐齐哈尔市中心城区的电动汽车和充电设施发展规模进行了合理预测。     

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.     

大指挥官PHEV充电系统安规测试与案例分析

随着电动汽车市场占有率逐渐增大,电动汽车安全一直是国家和企业关注的焦点。GB18384电动汽车安全要求,从储能系统、车辆操作安全和故障防护,以及人员触电防护3方面做了详细的要求。本文着重阐述非传导充电系统如何做安规测试以及案例分析。     

西津水利枢纽二线船闸下游引航道右岸支流汇入口消能设施设计

西津水利枢纽二线船闸工程是建设"西江亿吨级黄金水道"的重要举措之一。为研究二线船闸下引航道停泊段右岸西竹坑支流的汇入对二线船闸下引航道内通航水流条件的影响,通过水工模型试验研究在支流沟内布置消能设施对支流入汇口处流速、流态的影响,提出斜向导流坝、消力墩和消力池的工程措施,为类似工程提供借鉴。     

基于改进云模型的地铁站行人拥挤辨识方法

为降低城市地铁站内行人拥挤识别时多指标和多等级带来的不确定性和模糊性,采用改进云模型构建行人拥挤状态辨识模型。基于AHP-熵权法标定指标权重和行人拥挤状态等级,以标定的指标权重和各指标等级阈值作为输入,计算云数字特征值,采用正向正态云发生器,建立模板云和待识别云模型,计算两者之间的隶属度,根据最大隶属度原则辨识车站内各服务设施的行人拥挤状态,最后输出各服务设施的拥挤等级辨识结果。以宁波市鼓楼站为实证对象,对辨识结果进行实证分析。结果表明:采用四级行人拥挤状态划分方法合理可行。     

收费公路中相关法律问题的研究

收费公路是我国公路在新的建设环境下的产物,其在我国的发展过程中存在着很多问题,为解决这些问题。就必须提高收费公路制度的法律层次,完善收费公路的法律法规。     

AUV动力电池技术的应用现状及展望

从能量密度、循环寿命和安全性等方面介绍常用动力电池的特点,主要类型包括铅酸电池、锌银电池等传统电池和锂电池、燃料电池等新型电池。结合AUV的发展前景,对AUV对动力电池的发展要求进行分析,对AUV的充电方式进行总结,介绍锂电池管理系统的功能,以期能为新能源驱动的AUV研究提供一定参考。     

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.     

Locating rental stations and bikeways in a public bike system

To determine the spatial distribution of rental stations and bikeways in a public bike system, this paper proposes a facility location and network design model. The model is developed as a multi-objective programing problem that considers four objectives (minimizing cyclist risk, maximizing cyclist comfort, minimizing adverse impacts on traffic and maximizing service coverage) and multiple constraints (monetary budget, network connectivity, station spacing, bikeway types, station number and value ranges of decision variables). The ε-constraint method solves the programing problem for the public bike system in Daan District, Taipei City, Taiwan. The nine non-dominated alternatives generated are all markedly better than existing locations of rental stations and bikeways. Scenario analysis results indicate that increasing the construction budget for bikeways significantly improves cyclist safety and comfort whilst increasing the adverse impact on traffic. Planners can use this model to develop public bike systems that spatially integrate rental stations and bikeway networks.     

The role of volume-delay functions in forecasting and evaluating congestion charging schemes: the Stockholm case

This paper uses observations from before and during the Stockkholm congestion charging trial in order to validate and improve a transportation model for Stockholm. The model overestimates the impact of the charges on traffic volumes while at the same time it substantially underestimates the impact on travel times. These forecast errors lead to considerable underestimation of economic benefits which are dominated by travel time savings. The source of error lies in the static assignment that is used in the model. Making the volume-delay functions (VDFs) steeper only marginally improves the quality of forecast but strongly impacts the result of benefit calculations. We therefore conclude that the dynamic assignment is crucial for an informed decision on introducing measures aimed at relieving congestion. However, in the absence of such a calibrated dynamic model for a city, we recommend that at least a sensitivity analysis with respect to the slope of VDFs is performed.