Vehicle electrification in a developing country: Status and issue,from a well-to-wheel perspective

The increase of public attention, scientific research and political interest in environmental problems associated with transportation has provided the motivation for re-invention of electric vehicles. However the usage of grid-dependent EVs with a high-carbon electricity grid might produce more damage to the environment. This study aims to provide an environmental impact comparison of ICEVs, HEVs and EVs during their usage cycle, by modeling their energy consumption (electricity or fuel) and the supply chains of the supplied energy, (well-to-wheel) based on a life cycle assessment. The results show that running EVs with the existing mixed sources of electrical energy produce larger impacts on the environment 60% of the time; when compared to HEVs. When compared to ICEVs, EVs produce a larger environmental impact on 7 out of 15 environmental impact categories. Overall the environmental impacts of EVs are substantial based on the well-to-wheel analysis. It will continue to be so if no change is made to the methods of electricity generation in the near future. Given that the environmental profile of EVs is linked with the existing national electricity generation mix, the national electricity supply must be made cleaner before the electrification of the urban transport system.     

Cost scaling based successive approximation algorithm for the traffic assignment problem

This paper presents a cost scaling based successive approximation algorithm, called ε-BA (ε-optimal bush algorithm), to solve the user equilibrium traffic assignment problem by successively refining ε-optimal flows. As ε reduces to zero, the user equilibrium solution is reached. The proposed method is a variant of bush-based algorithms, and also a variant of the min-mean cycle algorithm to solve the min-cost flow by successive approximation. In ε-BA, the restricted master problem, implying traffic equilibration restricted on a bush, is solved to ε-optimality by cost scaling before bush reconstruction. We show that ε-BA can reduce the number of flow operations substantially in contrast to Dial’s Algorithm B, as the former operates flows on a set of deliberately selected cycles whose mean values are sufficiently small. Further, the bushes can be constructed effectively even if the restricted master problem is not solved to a high level of convergence, by leveraging the ε-optimality condition. As a result, the algorithm can solve a highly precise solution with faster convergence on large-scale networks compared to our implementation of Dial’s Algorithm B.     

基于发动机台架考核方法的气缸盖高周疲劳特性研究

依据发动机台架考核规范,运用疲劳强度理论,对某铸铁气缸盖进行高周疲劳强度评估。明确温度和应力随考核工况改变的变化行为,研究气缸盖各区域受工作载荷的影响状况,为缸盖寿命评估模型提供载荷边界。结合疲劳理论,在考虑材料修正的基础上进行了疲劳特性分析和损伤状况分析。分析表明,气缸盖各区域的疲劳安全系数均大于1,视为安全,但冷却钻孔区域的安全裕度较小。     

浅谈滚动物料计划在汽车行业中的应用

随着汽车逐年普及,消费者需求多样化、个性化随着增长,而且消费者对提车周期要求越来越高.汽车生产企业如何快速、高效的占领市场,同时降低供应链物流成本,是目前自主品牌汽车企业面临重大挑战.需要从软硬件进行全面提升竞争能力,物料组织改进是整个汽车供应链改进不可缺少的一个重要环节,能帮助企业迅速占领市场,以最小的成本换取最大利...     

一类离散陀螺系统特征值反问题

考虑由两个实值非奇异矩阵,一个对称,一个反对称,所定义的2n个一阶常微分方程刻画的陀螺系统特征值反问题。在给定完整谱数据及部分谱数据两种情况下,给出了可解性条件及解的表示。     

轨迹数据驱动的单点信号交叉口运行效率评价方法

为解决信号交叉口运行效率评价方法偏理论化、实用性不强等问题,以出租车、公交车、驾图(车联网)多源GPS轨迹数据为基础,充分利用车辆减速、停车、加速等连续速度变化特征及位置信息,提出交叉口个体车辆排队长度、通行时间、停车次数等交通参数提取技术.基于此,构建以信号交叉口运行指数为一级指标,车辆平均通行时间,第95％分位排队...     

基于结果导向的绿色公路评价指标体系研究

本文在梳理绿色公路建设历程的基础上,结合绿色公路提出的时代背景、发展要求及目前评价指标体系存在的问题,借鉴目标管理法(MBO)突出结果导向,面向全寿命周期的三个阶段,从"资源节约"、"生态环保"、"低碳减排"、"智慧高效"等方面构建了包括4个一级指标、25个二级指标的绿色公路评价指标体系。     

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.     

冻融作用下的沥青混合料力学特性

冻融损坏是冰冻地区沥青混合料的主要破坏形式。通过冻融循环作用下的沥青混合料单轴压缩和劈裂强度试验,分析了冻融循环次数、油石比等因素对沥青混合料力学特性的影响。试验得出,冻融循环次数和油石比对混合料的抗压和劈裂抗拉特性均有影响,油石比越小,影响越明显;在最佳油石比5.5%时,混合料的抗冻性能最好;冻融循环次数对沥青混合料力学特性的影响逐渐减弱,在10~12次冻融循环后,沥青混合料冻融后的强度和模量损失率均逐渐趋于稳定。     

动态载荷识别的自适应延迟逆模型方法

为减小载荷识别问题对原系统先验知识的依赖,采用系统的自适应延迟逆模型识别时域载荷。采用自适应算法辨识延迟逆模型,代替了一般识别方法中的系统特性矩阵求逆过程,避免了病态问题。随后将工作状态下的响应作为逆模型的输入,则其输出就是时域载荷的延迟估计。通过对两端简支梁结构进行载荷识别的仿真研究,以及对双层隔振试验台架的试验研究,识别了稳态激励和瞬态激励,验证了该方法的有效性。该方法不需要了解系统的数学模型及参数,因此能够应用于工程实践中。