Life cycle emissions and cost model for urban light duty vehicles

The growth of vehicle sales and use internationally requires the consumption of significant quantities of energy and materials, and contributes to the deterioration of air-quality and climate conditions. Advanced propulsion systems and electric drive vehicles have substantially different characteristics and impacts. They require life cycle assessments and detailed comparisons with gasoline powered vehicles which, in turn, should lead to critical updates of traditional models and assumptions. For a comprehensive comparison of advanced and traditional light duty vehicles, a model is developed that integrates external costs, including emissions and time losses, with societal and consumer life cycle costs. Life cycle emissions and time losses are converted into costs for seven urban light duty vehicles. The results, which are based on vehicle technology characteristics and transportation impacts on environment, facilitate vehicle comparisons and support policy making in transportation. Substantially, more sustainable urban transportation can be achieved in the short-term by promoting policies that increase vehicle occupancy; in the intermediate-term by increasing the share of hybrid vehicles in the car market and in the long-term by the widespread use of electric vehicles. A sensitivity-analysis of life cost results revealed that vehicle costs change significantly for different geographical areas depending on vehicle taxation, pricing of gasoline, electric power and pollution. Current practices in carbon and air quality pricing favor oil and coal based technologies. However, increasing the cost of electricity from coal and other fossil fuels would increase the variable cost for electric vehicles, and tend to favor the variable cost of hybrid vehicles.     

Adoption of alternative fuel vehicles: Influence from neighbors,family and coworkers

During the last years, many governments have set targets for increasing the share of biofuels in the transportation sector. Understanding consumer behavior is essential in designing policies that efficiently increase the uptake of cleaner technologies. In this paper we analyze adopters and non-adopters of alternative fuel vehicles (AFVs). We use diffusion of innovation theory and the established notion that the social system and interpersonal influence play important roles in adoption. Based on a nationwide database of car owners we analyze interpersonal influence on adoption from three social domains: neighbors, family and coworkers. The results point primarily at a neighbor effect in that AFV adoption is more likely if neighbors also have adopted. The results also point at significant effects of interpersonal influence from coworkers and family members but these effects weaken or disappear when income, education level, marriage, age, gender and green party votes are controlled for. The results extend the diffusion of innovation and AFV literature with empirical support for interpersonal influence based on objective data where response bias is not a factor. Implications for further research, environmental and transport policy, and practitioners are 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.     

复杂载荷下裂纹SIF计算的子模型技术

对船舶与海洋工程结构物进行疲劳评估,首先要通过子模型技术解决复杂应力场中裂纹应力强度因子(SIF)的计算问题。针对子模型技术实现过程繁杂且效率较低的问题,分别提出"逐周分层法","转换矩阵法"及"映射划分法"并基于VBA及APDL语言编写插件MPCarrangerV1.0,FEMcoortransferV1.0及CrackmapperV1.0,解决从Patran整体有限元模型到Ansys子模型时壳体单元间MPC创建低效、不同坐标系间节点位置转换困难及裂纹自由划分的局限性问题。基于DNV及ABS相关规范,以某B型LNG燃料舱的疲劳热点为例,对改进的子模型技术进行验证,结果表明经改进的子模型技术可成功施加合理边界条件并实现SIF的求解,可为子模型技术快速实现复杂载荷下裂纹SIF的准确计算提供参考。     

基于生长曲线函数的货车运营环节碳达峰研究

货车是我国大气环境污染的重要来源之一，也是影响我国碳达峰总体目标实现的重要因 素。本文从货车运营环节入手，在运用生长曲线函数对货车保有量进行预测的基础上，对不同类 型货车的保有量和单车碳排放变化进行研究，并从货车节能技术发展、新能源货车推广和应用进 程两方面入手，分3种情景对货车运营环节中产生的碳排放总量趋势进行预判，推演货车运营环 节的碳达峰时间。研究结果表明，只有同时加快货车节能技术发展以及新能源货车推广和应用 进程，货车运营环节中产生的碳排放总量规模才能得到有效抑制并逐渐减少。若到 2030 年货 车单车燃料消耗水平较 2019 年降低 20%以上，新能源货车在货车整体保有量中的占比达到 20%，到 2060 年货车单车燃料消耗水平较 2019 年降低 50%，新能源货车占比达到 50%，则货车 运营环节碳达峰时间将缩短至2030年左右实现，2030年后货车运营环节产生的碳排放总量规 模将逐渐减少。     

基于以太网的机舱监测报警系统设计

本文介绍了基于以太网的机舱监测报警系统的组成和功能,并对机舱监测报警系统的硬件、软件进行了设计,为后续的机舱监测系统设计提供参考。     

某船右主机不能正常建立滑油压力的故障排除

文章对某船右主机启动过程中,机带滑油泵不能正常建立滑油压力进行了分析,制定了针对性的排除故障措施,通过在机带滑油泵通舱管吸入口处安装吸入止回阀解决了滑油压力非正常下降的故障,实船应用证明措施合理,对同类故障排除有较好的借鉴意义。     

从一起船舶主机拉缸故障谈柴油机润滑油的选用

通过某LPG船一起主机拉缸案例,阐述船舶柴油机润滑油合理选用和管理的重要性,讨论选用润滑油应根据船舶柴油机的型号、燃油品质等具体情况,充分考虑润滑油的黏度等级和碱度。介绍船用柴油机润滑油国内外主要生产商及其相应的产品牌号。     

废气旁通阀开度对增压直喷汽油机部分负荷性能的影响

汽油机节气门产生的节流损失对增压发动机泵气损失的影响相当严重,尤其是在中小负荷时,针对这一问题采用试验的方法研究了中小负荷下旁通阀开度对增压直喷汽油机性能的影响。研究结果表明,在节气门开度较小的小负荷工况下,涡轮增压器不宜工作,否则排气背压过大,对发动机非常不利;而废气旁通阀全开可以减小排气背压,能使发动机的动力性和经济性提高3%左右。对废气旁通阀的合理控制可以实现发动机在自然吸气和涡轮增压两种模式之间的转换。