汽车风能应用前景及方法探讨

本文从汽车风能应用的性质、原理、储量、价值、经济性、空气动力学特性等方面出发,探讨了风能在汽车工业上的应用理论及方法,对汽车风能应用的关键设备--车用风力发电机的结构、工作原理及应用方法等做了说明.结合汽车外形进行了数值计算,计算结果表明:车辆前部开进风口是助于风阻的减少.     

浅析中国汽车物流业的发展现状

近年来,随着中国汽车产业的迅猛发展,汽车整车及零配件运输开始逐渐显现规模,与之关系密切的汽车物流业也开始启动。一、汽车物流的概念及现状1.汽车物流汽车物流是集现代运输、仓储、保管、搬运、包装、产品流通及物流信息于一体的综合性管理,是沟通原料供应商、生产厂商、批发商、零件商、物流公司及最终用户满意的桥梁,更是实现商品从生产到消费各个流通环节的有机结合。对汽车企业来说,汽车物流包括生产计划制订、采购订单下放及跟踪、物料清单维护、供应商的管理、运输管理、进出口、货物的接收、仓储管理、发料及在制品的管理和生产线…     

公路客运领域推广应用新能源汽车研究

针对公路客运量不断下滑及新能源汽车在公路客运领域推广应用尚未形成规模的问题,本文首先从公路交通网络建设情况、载客汽车数量及客运量两个方面分析公路客运发展现状和公路客运运营特点;其次,在分析公路客运领域新能源汽车推广应用现状的基础上,总结其发展制约因素;最后,综合分析公路客运转型升级需求和新能源汽车技术特点,认为新能源汽车未来可在中短途公路客运以及旅游客运领域推广应用,以解决公路客运目前发展面临的困境和新能源汽车在公路客运领域推广应用进度缓慢的问题。     

基于SWOT分析的我国汽车物流发展对策研究

以我国汽车物流作为研究对象,研究我国汽车物流的发展对策问题。应用SWOT分析方法,从发展的优势、劣势、机遇和挑战4个方面对我国汽车物流进行了分析。在此基础上,从国家和地方政府的政策扶持、汽车物流标准化体系的建设、汽车物流企业发展模式、汽车物流复合型人才培养4个方面提出了相关的发展战略,为我国未来的汽车物流发展提供科学指导。     

西藏林拉高等公路太阳能混合动力汽车运营可行性分析

文章通过分析当前混合动力汽车的发展技术,结合对西藏林拉路段丰富的太阳能资源以及路况分析,提出了引入太阳能的混合动力汽车新车型在林拉路段运营的可行性探讨。重点从方案提出及分析、经济效益分析、节能环保分析三个方面说明了林拉高等级公路运营太阳能混合动力汽车确实具有可行性。发展太阳能混合动力汽车在理论和技术已基本成熟,而且有一定的经济效益,还具有节能环保作用,可以为将来西藏发展新能源汽车提供科学依据。     

我国新能源汽车技术发展现状及对策研究

为促进我国新能源汽车领域高质量发展,从纯电动技术、混合动力技术以及燃料电池技术三个方面介绍我国新能源汽车技术的发展现状,分析新能源汽车发展面临的创新能力不足、资金支持不足、消费者认可度低及专业人才不足等问题。在此基础上,提出产业链优化、技术创新、构建专业人才团队等对策,以期为相关领域的工作人员提供参考。     

略论汽车的油耗与管理

文章从汽车管理者的角度探讨如何实现节约车辆油耗。根据汽车的工作原理,分析造成汽车油耗增大的机械因素,从驾驶员不良驾驶习惯分析,由于驾驶员自身的因素造成汽车油耗增大,最后从燃油的正确使用分析造成汽车油耗增大的又一因素,针对造成汽车油耗增大的三个主要因素,从车辆的保养制度的建立与保养质量的监督,到专职驾驶员考核与奖罚制度,逐层分析如何制订有效的管理措施,落实管车、管人的管理手段,通过具体的考核与监督,最终实现车辆油耗有效节约的管理目标。     

汽车租赁春意闹

由于市场需求和宏观政策支持,我国目前汽车租赁发展迅速且形势良好,其中汽车短期租赁呈现由东南经济发达地区向西北欠发达地区、从大城市向中小城市扩展和普及的趋势,已初步形成由全国主要城市构成的网络化经营模式,几乎所有县级城市及经济发达地区的城镇都有汽车租赁经营活动.单从发展态势上看,业内人士认为我国汽车租赁的春天已然来临.     

汽车租赁春意闹

由于市场需求和宏观政策支持，我国目前汽车租赁发展迅速且形势良好，其中汽车短期租赁呈现由东南经济发达地区向西北欠发达地区、从大城市向中小城市扩展和普及的趋势，已初步形成由全国主要城市构成的网络化经营模式，几乎所有县级城市及经济发达地区的城镇都有汽车租赁经营活动。单从发展态势上看，业内人士认为我国汽车租赁的春天已然来临。     

用经济、技术手段为“节能减排”拉下双重闸门 访福建省汽车运输总公司总经理王闽寅

<正>对于汽车运输企业来说,节能减排不仅仅是响应国家的大政方针,还关系着企业的经济效益。如何把利国利民利己的节能减排工作做好,成为各个企业的重点工作。在交通运输行业第二批节能减排典型示范项目中,福建省汽车运输总公司的"严格营运车辆准入,优化车辆技术结构"项目从影响汽车燃料消耗量的主要因素,即车辆技术、运行环境及汽车运用三大方面入手,为汽车运输企业如何降低燃料消耗探索出了一条值得借鉴的途径。     

Influences of the driver’s bounded rationality on micro driving behavior,fuel consumption and emissions

In this paper, we propose an extended car-following model to study the influences of the driver’s bounded rationality on his/her micro driving behavior, and the fuel consumption, CO, HC and NO_X of each vehicle under two typical cases, where Case I is the starting process and Case II is the evolution process of a small perturbation. The numerical results indicate that considering the driver’s bounded rationality will reduce his/her speed during the starting process and improve the stability of the traffic flow during the evolution of the small perturbation, and reduce the total fuel consumption, CO, HC and NO_X of each vehicle under the above two cases.     

Analysis of consumer response to fuel price fluctuations applying sample selection model to GPS panel data: Dynamics in individuals’ car use

The effects of fuel price increases on people’s car use have been widely discussed during the last few decades in travel behavior research. It is well recognized that fuel price has significant effects on driving distance and driving efficiency. However, most of this research assumed that these effects are invariant across individuals and weather conditions. Moreover, intrinsic variability in people’s preferences has not been given much attention due to the difficulty of collecting the necessary data. In this paper, we collected detailed travel behavior data of 276 respondents in the Netherlands, spanning a time period between one week and three months using GPS logs. These GPS data were fused with weather data, allowing us to estimate both exogenous (such as weather and fuel price) and endogenous effects (inertia and activity plans) on individual’s car use behavior. To further understand the effects of fuel price on the environment, we estimated the effects of fuel price fluctuation on CO₂ emissions by car. The results show a significant degree of inertia in car use behavior in response to increased fuel prices. Weather and fuel price showed significant effects on individual’s car using behavior. Moreover, fuel price shows two-week lagged effects on individual’s travel duration by car.     

Fuel demand,road transport pollution emissions and residents’ health losses in the transitional China

In recent years, China’s rapid economic growth resulted in serious air pollution, which caused substantial losses to economic development and residents’ health. In particular, the road transport sector has been blamed to be one of the major emitters. During the past decades, fluctuation in the international oil prices has imposed significant impacts on the China’s road transport sector. Therefore, inspired by Li and Zhou (2005), we propose an assumption that China’s provincial economies are independent “economic entities”. Based on this assumption, we investigate the China’s road transport fuel (i.e., gasoline and diesel) demand system by using the panel data of all 31 Chinese provinces except Hong Kong, Macau and Taiwan. To connect the fuel demand system and the air pollution emissions, we propose the concept of pollution emissions elasticities to estimate the air pollution emissions from the road transport sector, and residents’ health losses by a simplified approach consisting of air pollution concentrations and health loss assessment models under different scenarios based on real-world oil price fluctuations. Our framework, to the best of our knowledge, is the first attempt to address the transmission mechanism between the fuel demand system in road transport sector and residents’ health losses in the transitional China.     

Development of a driving simulator based eco-driving support system

This research developed an eco-driving feedback system based on a driving simulator to support eco-driving training. This support system could provide both dynamic and static feedback to improve drivers’ eco-driving behavior. In the process of driving, drivers could get voice prompts (e.g., please avoid accelerating rapidly) once non-eco-driving behavior appeared, and also could see the real-time CO₂ emissions curves. After driving, drivers could receive an eco-driving evaluation report including their fuel consumption rank, potential of fuel saving and driving advice corresponding to their driving behavior. In this support system, five items of non-eco-driving behavior (i.e., quick accelerate, rapid decelerate, engine revolutions at a high level, too fast or unstable speed on freeways and idling for a longer time) were defined and could be detected. To validate this support system’s effectiveness in reducing fuel consumption and emissions, 22 participants were recruited and three driving tests were conducted, first without using the support system, then static feedback and then dynamic feedback utilized respectively. A reduction of 5.37% for CO₂ emissions and 5.45% for fuel consumption was obtained. The results indicated that the developed eco-driving support system was an effective training tool to improve drivers’ eco-driving behavior in reducing emissions and fuel consumption.     

Relevance of the Northern Sea Route (NSR) for bulk shipping

Some scholars consider that today’s market conditions are in favor of the Northern Sea Route (NSR) rather than the Suez Canal Route (SCR). However, the number of bulk carriers using the NSR remains extremely limited, despite higher fuel prices since 2009 and subsequent significant fuel savings. In 2013, there were 53 transits via the Arctic, out of which 27 by oil tankers and 6 by bulk carriers. In this article we show that this result might be attributable to a factor, which is not considered in most studies: the spot freight rate to fuel ratio which governs ship owners’ decisions regarding the sailing speed. Due to a low ratio since 2011, the speed of vessels on the SCR is at its lowest level, and potential NSR fuel savings are too limited to provide a viable alternative. We further argue that, contrary to most studies, internalizing NSR environmental benefits marginally improves the attractiveness of the NSR.     

System for assessing Aviation’s Global Emissions (SAGE), Part 1: Model description and inventory results

In early 2001, the US Federal Aviation Administration embarked on a multi-year effort to develop a new computer model, the System for assessing Aviation’s Global Emissions (SAGE). Currently at Version 1.5, the basic use of the model has centered on the development of yearly global inventories of commercial aircraft fuel burn and emissions of various pollutants to serve as the basis for scenario modeling. This paper describes the algorithms and data used in the model as well as the results from initial validation assessments. SAGE results indicate that global fuel burn and nitrogen oxide (NO_x) emissions decreased by over 6% from 2000 to 2001 (fuel burn and NO_x), and then steadily increased to over 12% (fuel burn) and 15.5% (NO_x) above 2000 levels in 2005. Comparisons to the results from previous studies have shown that SAGE tends to agree more closely with fuel burn and NO_x than with CO and HC. Validation assessments have shown that SAGE can predict per flight fuel burn to within 3% on an average basis with no apparent bias, when compared to about 60,000 flight’s worth of data from a major US airline and about 20,000 flight’s worth of data from two major Japanese airlines.     

A volatile relationship: The effect of changing gasoline prices on public support for mass transit

The determinants of public opinion toward public transit is a little-researched topic, though a better understanding of what makes consumers willing to support transit may reveal which attributes of transit consumers value most. One determinant of people’s willingness to support investments in mass transit may be the price of fuel for transit’s principal competition, the private automobile. In this paper, I examine the relationship between the cost of gasoline and stated willingness to invest public money in mass transit improvements. I hypothesize that fuel price volatility—in addition to price itself—is a determinant of support for more mass transit funding, controlling for other factors. As the price of gasoline becomes more uncertain, the public should, all else equal, support investment in mass transportation, a form of transportation that may provide some measure of protection from the price of fuel. Results suggest a strong effect of price volatility on consumers’ willingness to support transit expenditures.     

The endogeneity of OECD gasoline taxes: Evidence from pair-wise,heterogeneous panel long-run causality tests

Despite the current interest in using fuel taxes as an instrument for climate policy, there has been little study of current automotive fuel tax regimes. We expand on two earlier cross-sectional studies on why fuel taxes differ across countries by using OECD panel data and employing heterogeneous panel cointegration and long-run panel Granger-causality techniques. We confirm some of those earlier studies’ conclusions. Further, we find that governments that rely on consumption-based taxes for revenues will have higher gasoline tax rates (than governments that rely on income and wealth/property-based taxes). But more significantly, we determine that higher gasoline demand among consumers “causes” democratic governments to set lower gasoline taxes—a finding with important implications for today’s climate/energy policy debate.     

Fuel economy improvements for urban driving: Hybrid vs. intelligent vehicles

The quest for more fuel-efficient vehicles is being driven by the increasing price of oil. Hybrid electric powertrains have established a presence in the marketplace primarily based on the promise of fuel savings through the use of an electric motor in place of the internal combustion engine during different stages of driving. However, these fuel savings associated with hybrid vehicle operation come at the tradeoff of a significantly increased initial vehicle cost due to the increased complexity of the powertrain. On the other hand, telematics-enabled vehicles may use a relatively cheap sensor network to develop information about the traffic environment in which they are operating, and subsequently adjust their drive cycle to improve fuel economy based on this information – thereby representing ‘intelligent’ use of existing powertrain technology to reduce fuel consumption. In this paper, hybrid and intelligent technologies using different amounts of traffic flow information are compared in terms of fuel economy over common urban drive cycles. In order to develop a fair comparison between the technologies, an optimal (for urban driving) hybrid vehicle that matches the performance characteristics of the baseline intelligent vehicle is used. The fuel economy of the optimal hybrid is found to have an average of 20% improvement relative to the baseline vehicle across three different urban drive cycles. Feedforward information about traffic flow supplied by telematics capability is then used to develop alternative driving cycles firstly under the assumption there are no constraints on the intelligent vehicle’s path, and then taking into account in the presence of ‘un-intelligent’ vehicles on the road. It is observed that with telematic capability, the fuel economy improvements equal that achievable with a hybrid configuration with as little as 7 s traffic look-ahead capability, and can be as great as 33% improvement relative to the un-intelligent baseline drivetrain. As a final investigation, the two technologies are combined and the potential for using feedforward information from a sensor network with a hybrid drivetrain is discussed.     

Customizing driving cycles to support vehicle purchase and use decisions: Fuel economy estimation for alternative fuel vehicle users

Wider deployment of alternative fuel vehicles (AFVs) can help with increasing energy security and transitioning to clean vehicles. Ideally, adopters of AFVs are able to maintain the same level of mobility as users of conventional vehicles while reducing energy use and emissions. Greater knowledge of AFV benefits can support consumers’ vehicle purchase and use choices. The Environmental Protection Agency’s fuel economy ratings are a key source of potential benefits of using AFVs. However, the ratings are based on pre-designed and fixed driving cycles applied in laboratory conditions, neglecting the attributes of drivers and vehicle types. While the EPA ratings using pre-designed and fixed driving cycles may be unbiased they are not necessarily precise, owning to large variations in real-life driving. Thus, to better predict fuel economy for individual consumers targeting specific types of vehicles, it is important to find driving cycles that can better represent consumers’ real-world driving practices instead of using pre-designed standard driving cycles. This paper presents a methodology for customizing driving cycles to provide convincing fuel economy predictions that are based on drivers’ characteristics and contemporary real-world driving, along with validation efforts. The methodology takes into account current micro-driving practices in terms of maintaining speed, acceleration, braking, idling, etc., on trips. Specifically, using a large-scale driving data collected by in-vehicle Global Positioning System as part of a travel survey, a micro-trips (building block) library for California drivers is created using 54 million seconds of vehicle trajectories on more than 60,000 trips, made by 3000 drivers. To generate customized driving cycles, a new tool, known as Case Based System for Driving Cycle Design, is developed. These customized cycles can predict fuel economy more precisely for conventional vehicles vis-à-vis AFVs. This is based on a consumer’s similarity in terms of their own and geographical characteristics, with a sample of micro-trips from the case library. The AFV driving cycles, created from real-world driving data, show significant differences from conventional driving cycles currently in use. This further highlights the need to enhance current fuel economy estimations by using customized driving cycles, helping consumers make more informed vehicle purchase and use decisions.