运输节能“利器”风行

说起来重要,干起来次要,忙起来不要。交通部公路科学研究院汽车运输研究中心副主任蔡凤田在调研中听到了一句节能工作顺口溜。这说明,前些年,尽管节能减排在我国宣传力度很大,但落实到具体工作中,依然没有一个合适的抓手。     

基于节能减排理念的公路工程施工工艺

目前,由于环境污染问题日益严重,各行各业的发展逐渐趋于环保低碳的方向,因此,在公路工程建设施工的过程中,节能减排逐渐成为其工作中的重要任务.本文通过对公路施工中节能减排的影响因素进行分析,探究出基于节能减排理念的公路工程施工工艺建设,在公路工程建设的同时,能够降低施工成本,做好节能减排工作,从而有效提高公路工程建设的综合效益.     

浅析公路养护新技术在节能减排中的应用

公路养护工作的开展,要能发挥较高的管理能力,做好可靠化技术控制,重视消除汇总节能减排现状问题,目前主要使用性能预测检测、养护路段划分、养护效果评价,不断提升节能减排管理能力.节能减排技术在公路养护中具有较高的应用价值,目前主要有沥青路面再生养护技术、柔性基层养护技术、微表处理养护技术、雾封层养护技术.提升公路养护新技术在节能减排应用的措施,实现政策引导与技术同步发展,因地制宜合理选择再生方式,提升作业人员的节能减排意识.     

交通行业节能减排指标体系建立研究

交通行业节能减排指标体系建设需要运用系统工程理论,当前需要对交通运输行业进行全面的节能减排综合分析,通过动态分析可以更好的发现节能减排过程中产生的问题。交通行业节能减排受到多种因素的影响,节能减排工作需要在一定的原则下积极稳妥的实施。当前情况下需要根据国家和地方交通主管部门颁发的相关法规和文件精神,构建完善的节能减排评价指标体系,交通运输行业节能减排工作需要按照层次分析法,确定交通运输业节能减排的相关指标体系,通过对各个指标进行权重分析,对交通运输业节能减排工作的顺利实施产生重要的意义。     

宇通：节能减排走亲民路线

众所周知，节能减排主体在企业．重点在基层．因为节能减排工作要落实到每一个客运站，每一辆车．每一位驾驶员。     

山东省水运节能工作的发展对策

对山东省水运节能工作进行了总结、剖析.考虑省情和存在问题,提出了山东省水运节能工作建议和措施.     

GPS全球定位系统和行车记录仪系统

作为近年来迅速发展起来的技术,全球卫星定位系统GPS已经广泛地运用在各个领域,有着广阔的前景。文章阐述了该系统的工作流程;介绍了汽运集团结合自身的特点,将该系统有效地运用到促进和改善车辆技术和运行管理上所取得的显著节能效果;并提出了现存的问题和努力方向。     

节能技术在供热系统中的应用

为了实现经济的可持续发展,开展节能降耗工作,特别是运用科技创新手段做好节能工作是非常必要的.     

基于节能减排的沥青路面养护技术研究

随着我国道路交通事业的不断发展,公路建设规模逐渐增大.目前各行各业都在逐渐贯彻节能减排理念,在建设工程中应用节能减排新技术已经成为行业发展的必然要求,公路工程也应在当前低碳经济时代满足节能减排的要求,提高沥青路面的养护效果.这就需要采取行之有效的节能减排沥青路面养护技巧,减少能耗,为公路工程建设事业的可持续发展打下坚实的基础.本文就沥青路面在节能减排的基础上的养护技术进行了简单论述.     

李盛霖部长主持召开部节能减排工作领导小组会议

11月26日,交通运输部部长、部节能减排工作领导小组组长李盛霖主持召开部节能减排工作领导小组会议,全面总结今年以来的交通运输节能减排工作,研究部署明年的节能减排重点工作.李盛霖强调,要进一步提高思想认识,加强组织协调,坚持不懈地深入抓好交通运输节能减排工作.     

Real-time energy-efficient traffic control via convex optimization

This article proposes a macroscopic traffic control strategy to reduce fuel consumption of vehicles on highways. By implementing Greenshields fundamental diagram, the solution to Moskowitz equations is expressed as linear functions with respect to vehicle inflow and outflow, which leads to generation of a linear traffic flow model. In addition, we build a quadratic cost function in terms of vehicle volume to estimate fuel consumption rate based on COPERT model. A convex quadratic optimization problem is then formulated to generate energy-efficient traffic control decisions in real-time. Simulation results demonstrate significant reduction of fuel consumption on testing highway sections under peak traffic demands of busy hours.     

Total requirements of energy and greenhouse gases for Australian transport

In addition to fuels, passenger and freight transport require vehicles and infrastructure. As with fuels, the provision of goods and services that are needed for the operation of transport involves the consumption of energy and the emission of greenhouse gases. The energy consumed and greenhouse gases emitted due to fuel use by vehicles are referred to as direct requirements, while indirect requirements of energy and greenhouse gases are embodied in the goods and services mentioned before. Indirect requirements form a significant part of the total energy and greenhouse gases required for a given transport task. They depend on the transport mode, ranging from 10% to 50% for freight transport and from 25% to 65% for passenger transport. These indirect requirements have to be taken into account when options for reducing the energy consumption and greenhouse gas emissions of the transport sector are to be evaluated.     

The effect of uncertainty on US transport-related GHG emissions and fuel consumption out to 2050

The future of US transport energy requirements and emissions is uncertain. Transport policy research has explored a number of scenarios to better understand the future characteristics of US light-duty vehicles. Deterministic scenario analysis is, however, unable to identify the impact of uncertainty on the future US vehicle fleet emissions and energy use. Variables determining the future fleet emissions and fuel use are inherently uncertain and thus the shortfall in understanding the impact of uncertainty on the future of US transport needs to be addressed. This paper uses a stochastic technology and fleet assessment model to quantify the uncertainties in US vehicle fleet emissions and fuel use for a realistic yet ambitious pathway which results in about a 50% reduction in fleet GHG emissions in 2050. The results show the probability distribution of fleet emissions, fuel use, and energy consumption over time out to 2050. The expected value for the fleet fuel consumption is about 450 and 350 billion litres of gasoline equivalent with standard deviations of 40 and 80 in 2030 and 2050, respectively. The expected value for the fleet GHG emissions is about 1360 and 850 Mt CO₂ equivalent with standard deviation of 130 and 230 in 2030 and 2050 respectively. The parameters that are major contributors to variations in emissions and fuel consumption are also identified and ranked through the uncertainty analysis. It is further shown that these major contributors change over time, and include parameters such as: vehicle scrappage rate, annual growth of vehicle kilometres travelled in the near term, total vehicle sales, fuel economy of the dominant naturally-aspirated spark ignition vehicles, and percentage of gasoline displaced by cellulosic ethanol. The findings in this paper demonstrate the importance of taking uncertainties into consideration when choosing amongst alternative fuel and emissions reduction pathways, in the light of their possible consequences.     

Modeling the effects of congestion on fuel economy for advanced power train vehicles

Fuel-speed curves (FSC) are used to account for the aggregate effects of congestion on fuel consumption in transportation scenario analysis. This paper presents plausible FSC for conventional internal combustion engine (ICE) vehicles and for advanced vehicles such as hybrid electric vehicles, fully electric vehicles (EVs), and fuel cell vehicles (FCVs) using a fuel consumption model with transient driving schedules and a set of 145 hypothetical vehicles. The FSC shapes show that advanced power train vehicles are expected to maintain fuel economy (FE) in congestion better than ICE vehicles, and FE can even improve for EV and FCV in freeway congestion. In order to implement these FSC for long-range scenario modeling, a bounded approach is presented which uses a single congestion sensitivity parameter. The results in this paper will assist analysis of the roles that vehicle technology and congestion mitigation can play in reducing fuel consumption and greenhouse gas emissions from motor vehicles.     

Low carbon urban transport scenarios for China and India: A comparative assessment

This paper assesses comparable urban transport scenarios for China and India. The assessment methodology uses AIM/End-use model with a detailed characterization of technologies to analyze two scenarios for India and China till the year 2050. The first scenario assumes continuation and enhancement, in both countries, of policies under a typical business-as-usual dynamics, like constructing metros, implementing national fuel economy standards, promoting alternate fuel vehicles and implementing national air quality standards. The alternative, low carbon scenario assumes application, in both countries, of globally envisaged measures like fuel economy standards as well as imposition of carbon price derived from a global integrated assessment modeling exercise aiming to achieve global 2 °C temperature stabilization target. The modeling results for both countries show that decarbonizing transport sector shall need a wide array of measures including fuel economy, low carbon fuel mix including low carbon electricity supply. The comparison of China and India results provides important insights and lessons from their similarities and differences in the choice of urban transport options. India can benefit from China’s experiences as it lags China in urbanization and income. Modeling assessments show that both nations can contribute to, as well as benefit by aligning their transport plans with global climate stabilization regime.     

Transport energy consumption in mountainous roads. A comparative case study for internal combustion engines and electric vehicles in Andorra

This paper analyses transport energy consumption of conventional and electric vehicles in mountainous roads. A standard round trip in Andorra has been modelled in order to characterise vehicle dynamics in hilly regions. Two conventional diesel vehicles and their electric-equivalent models have been simulated and their performances have been compared. Six scenarios have been simulated to study the effects of factors such as orography, traffic congestion and driving style. The European fuel consumption and emissions test and Artemis urban driving cycles, representative of European driving cycles, have also been included in the comparative analysis. The results show that road grade has a major impact on fuel economy, although it affects consumption in different levels depending on the technology analysed. Electric vehicles are less affected by this factor as opposed to conventional vehicles, increasing the potential energy savings in a hypothetical electrification of the car fleet. However, electric vehicle range in mountainous terrains is lower compared to that estimated by manufacturers, a fact that could adversely affect a massive adoption of electric cars in the short term.     

A methodology for assessing eco-cruise control for passenger vehicles

This paper compares and assesses fuel consumption models, cost functions, and solution methods, as they all have an influence on the resulting profile and associated fuel savings of an eco-cruise control system for passenger vehicles. An eco-cruise control system uses road topographical data obtained from a high-resolution digital map to control the vehicle velocity to optimize its fuel consumption. The optimal velocity profile is the result of an optimal control problem.     

Incentivizing alternative fuel vehicles: the influence of transport policies,attitudes and perceptions

This paper aims to evaluate the influence of policies, attitudes and perceptions when incentivizing alternative fuel vehicles. The impact of possible policies such as gasoline taxes increases, purchase price subsidies, tax exemptions, and increases in fuel recharging station availability for alternative fuelled vehicles is evaluated using hybrid choice models. The models also allow assessing the sensitivity of latent variables (i.e., attitudes and perceptions) in the car purchase behaviour. The models are estimated using data from a stated choice survey collected in five Colombian cities. The latent variables are obtained from the rating of statements related to the transport system, environmental concern, vehicle preferences, and technology. The modelling approach includes regression between latent variables. Results show that environmental concern and the support for green transport policies have a positive influence on the intention to purchase alternative fuel vehicles. Meanwhile, people who reveal to be car-dependent prefer to buy standard fuelled vehicles. The analysis among cities shows similar trends in individual behaviour, although there are differences in attribute sensitivities. The policy scenario analysis revealed high sensitivity to capital cost and the need for extensive investments in refuelling stations for alternative fuel vehicles to become attractive. Nevertheless, all policies should not only be directed at infrastructure and vehicles but also be focused on user awareness and acceptance of the alternative fuel vehicles. The analysis suggests that in an environmentally conscious market, people prefer alternative fuels. However, if the transport policies support private transport, the market shares of alternative fuel vehicles will decrease.     

Vehicle mass as a determinant of fuel consumption and secondary safety performance

One interaction between environmental and safety goals in transport is found within the vehicle fleet where fuel economy and secondary safety performance of individual vehicles impose conflicting requirements on vehicle mass from an individual’s perspective. Fleet characteristics influence the relationship between the environmental and safety outcomes of the fleet; the topic of this paper. Cross-sectional analysis of mass within the British fleet is used to estimate the partial effects of mass on the fuel consumption and secondary safety performance of vehicles. The results confirmed that fuel consumption increases as mass increases and is different for different combinations of fuel and transmission types. Additionally, increasing vehicle mass generally decreases the risk of injury to the driver of a given vehicle in the event of a crash. However, this relationship depends on the characteristics of the vehicle fleet, and in particular, is affected by changes in mass distribution within the fleet. We confirm that there is generally a trade-off in vehicle design between fuel economy and secondary safety performance imposed by mass. Cross-comparison of makes and models by model-specific effects reveal cases where this trade-off exists in other aspects of design. Although it is shown that mass imposes a trade-off in vehicle design between safety and fuel use, this does not necessarily mean that it imposes a trade-off between safety and environmental goals in the vehicle fleet as a whole because the secondary safety performance of a vehicle depends on both its own mass and the mass of the other vehicles with which it collides.     

Mobility and environment improvement of signalized networks through Vehicle-to-Infrastructure (V2I) communications

Traffic signals, even though crucial for safe operations of busy intersections, are one of the leading causes of travel delays in urban settings, as well as the reason why billions of gallons of fuel are burned, and tons of toxic pollutants released to the atmosphere each year by idling engines. Recent advances in cellular networks and dedicated short-range communications make Vehicle-to-Infrastructure (V2I) communications a reality, as individual cars and traffic signals can now be equipped with communication and computing devices. In this paper, we first presented an integrated simulator with V2I, a car-following model and an emission model to simulate the behavior of vehicles at signalized intersections and calculate travel delays in queues, vehicle emissions, and fuel consumption. We then present a hierarchical green driving strategy based on feedback control to smooth stop-and-go traffic in signalized networks, where signals can disseminate traffic signal information and loop detector data to connected vehicles through V2I communications. In this strategy, the control variable is an individual advisory speed limit for each equipped vehicle, which is calculated from its location, signal settings, and traffic conditions. Finally, we quantify the mobility and environment improvements of the green driving strategy with respect to market penetration rates of equipped vehicles, traffic conditions, communication characteristics, location accuracy, and the car-following model itself, both in isolated and non-isolated intersections. In particular, we demonstrate savings of around 15% in travel delays and around 8% in fuel consumption and greenhouse gas emissions. Different from many existing ecodriving strategies in signalized road networks, where vehicles’ speed profiles are totally controlled, our strategy is hierarchical, since only the speed limit is provided, and vehicles still have to follow their leaders. Such a strategy is crucial for maintaining safety with mixed vehicles.