CO2 abatement and CH4 recovery at vehicle exhausts: Comparison and characterization of Ru powder and pellet catalysts

The catalytic conversion of CO₂ to CH₄ (Sabatier reaction) has been studied to develop an after-treatment process at vehicles exhausts. Three different formulations of Ru commercial catalysts, two in powder and one in pellets shape, were tested and characterized by means of X-ray powder diffraction, scanning electron microscopy (SEM-EDX), N₂ adsorption at −196 °C and temperature-programmed reduction (TPR).Experimental results show a high CO₂ conversion (X_CO2 = 0.96 @ T = 280 °C) for one powder catalyst formulation whereas the other one has maximum CO₂ conversion = 0.69. In both cases a high CH₄ selectivity is measured. High CO₂ conversion (X_CO2 = 0.92 @ T = 300 °C) is obtained also with pellet catalysts but only at lower GHSV values. The different behavior of the catalysts was ascribed to the different physicochemical properties and the key parameters for the application development of the process were identified. In particular, the possibility to use pellets or monolithic reactors, thus minimizing the pressure drops in the reactor, makes possible a commercial application in the treatment of vehicles exhausts.     

车联网环境下基于节点认知交互的路由算法

针对车联网（IoV）环境下消息传输效率低下、网络资源开销较大等诸多问题，提出一种适用于城市交通场景下基于车辆节点认知交互的路由算法。首先，依据信任理论提出节点认知交互度的概念，并在此基础上对车联网中的车辆节点进行分类，赋予它们不同的认知交互度初值；同时还引入车辆节点交互时间、交互频率、车辆节点物理间隔距离、间隔跳数以及消息生存时间等影响因子，进而构建了车辆节点认知交互评估模型。基于该模型计算并更新节点的认知交互度，并通过比较对应车辆节点间的认知交互度值来选取认知交互度相对较高的邻居节点作为中继节点进行消息转发。仿真实验结果表明，与Epidemic和Prophet路由算法相比，所提路由算法有效提高了消息投递率并降低了消息投递时延，同时显著降低了网络资源的开销，有助于提升车联网环境的消息传输质量。     

Exploring to direct the reaction pathway for hydrogenation of levulinic acid into γ-valerolactone for future Clean-Energy Vehicles over a magnetic Cu-Ni catalyst

A cheap and magnetic Ni/Cu/Al/Fe catalyst for the selective hydrogenation of LA into GVL catalysts was prepared by sol-gel method. The reaction pathway was systematically studied by examining the reaction conditions, such as reaction pressure, catalyst loadings, water content, and reaction temperature. Higher reaction pressure and catalyst loadings were prior to form HA, then MHV, finally GVL; ML was easily to form with a higher reaction temperature. Water, as a key role, which was in favor to form HA, then MHV, finally GVL; more important, a higher LA conversion could be obtained in methanol as the solvent with some certain content of water. And, it can give a reference for future new clean energy vehicles' application.     

WAVE协议栈下基于高斯混合模型的无线定位研究

无线定位是车联网中各应用的基础,对实时性和精度要求更高。基于此,本文提出了一个在WAVE系统下基于混合高斯模型的位置指纹定位算法。该算法由离线训练和在线定位两部分组成,采用GMM对离线训练阶段的指纹数据库进行聚类建模处理,并在定位阶段对结果采用多点均值方法,不仅降到了系统定位误差,也减少了定位阶段的运算量,提高了定位的实时性。实验结果表明,该算法有较好的定位精度和实时性,为WAVE环境下的快速定位进一步研究提供有效参考价值。     

Implementing an emerging mobility model for a fleet of UAVs based on a fuzzy logic inference system

In this paper, we design and implement a novel generic mobility model, named Alpha-based, for a fleet of small interconnected UAVs (Unmanned Aerial Vehicles) that collaborate to explore a geographic area (battle field, research and rescue missions, surveillance applications, etc.). In fact, due to the significant impact of mobility models on the networking performance, the mobility models must realistically capture the UAV’s attributes. Hence, we propose to use a combination of energy level, coverage-area and network connectivity for mobility decision-making, in contrast to the literature where only network connectivity and area coverage are investigated. On the one hand, these two metrics are very important, especially for applications where achieving the best area-coverage and maintaining network connectivity represent an essential requirement. On the other hand, energy is another equally noteworthy constraint that should be taken into account. In fact, being a crucial resource for all mobile devices and especially for UAVs, the energy becomes vital to ensure the network lifetime and mission success. As far as we know, Alpha-based mobility model is the first to ever consider a combination of these three metrics within the same decision-making criterion. A distributed scheme is adopted, where each UAV determines locally its future movement based on the information it receives from its neighbors. Moreover, a novel fuzzy inference system is implemented in order to compute the values of a followship weighting parameter, named Alpha. This latter is used to choose the most suitable neighboring UAV to follow. To validate the proposed mobility model, rigorous testing has been accomplished, through simulation work. Compared to Random-based and Forces-based mobility models, the Alpha-based mobility model achieves good coverage rate while maintaining connectivity.     

Coverage path planning for UAVs based on enhanced exact cellular decomposition method

In this paper, an enhanced exact cellular decomposition method to plan the coverage path of UAVs in a polygon area is proposed. To be more specific, the contributions of the paper are: firstly, the turning motion of UAVs is shown to be less efficient from the viewpoints of route length, duration and energy. Secondly, the problem of coverage Path Planning (CPP) in a convex polygon area is transformed to width calculation of the convex polygon, and a novel algorithm to calculate the widths of convex polygons with time complexity of O(n) is developed. The path of the least number of turns for an UAV based on the widths of convex polygons is devised. Thirdly, a convex decomposition algorithm for minimum width sum based on the greedy recursive method which revolves around decomposing the concave area into convex subregions is developed. It is proved that the algorithm is a polynomial time algorithm. To avoid unnecessary back and forth motion, some entirely adjacent subregions are combined. Finally, comparing different weights of two joint-points, a subregion connection algorithm based on minimum traversal of weighted undirected graph is proposed to connect the coverage paths of the subregions. Simulation results show that the proposed method is feasible and effective.     

基于排队论的车辆维修保障中维修组个数优化

利用排队论原理解决车辆维修保障中维修组个数的确定.首先在定点保障中,对维修组进行集中配置,由此确定定点维修中维修组数目.然后以车辆完好率为目标,确定伴随保障中抢修车的数量.最后,将运输任务重要程度对车辆战损率进行加权,确定应配置抢修车的车队的最小车辆数.     

基于公交轨迹和定位信息的地域群播算法研究

传统的地域群播算法大多数在WSN中使用,没有考虑到道路路网和车辆轨迹信息,没有很好地适用于车联网中的群播需求。基于目前的一些商业需求,引入了公交车的轨迹信息,提出了一种基于公交轨迹的地域群播算法。第一阶段先建立公交节点的轨迹树以及相遇模型,再根据相遇图计算公交节点对目标区域的消息转发能力,选择具有更高消息转发能力的节点转发消息到目的区域。第二阶段使用稳定性指数来估计两辆车的稳定性,在目的区域的每条街道上建立一个车辆集,通过建立和维护车辆集达到群播的目的。在联合仿真平台SUMO和OMNET++下仿真,其实验结果分析表明,随着车辆数目增加,该算法在维持高的数据包投递率情况下可以将整网的传输开销降低,达到预期的目标。     

元胞自动机交通流模型中的车辆更新方式研究

基于TASEP(Totally Asymmetric Simple Exclusion Process)模型,使用蒙特卡洛方法模拟开放边界条件下不同车辆更新方式对稳态时车辆特性及相变行为的影响,得到不同注入概率α和输出概率β条件下的交通流基本图。结果表明,不同更新方式对系统的稳态特性及相变行为有较大影响,流量和密度随α和β的不同而变化,模拟结果与解析解吻合。随机更新方式下道路车流量的大小由输出概率决定,当输出概率达到一定值时,它的增大无法提高道路上的车流量;顺序更新方式的优点是仅当输入和输出概率都相等时,系统保持畅行相;而局部并行更新方式下得出的相图则与顺序和全局并行更新这两种方式下得到的相图类似且可以更好地反映交通流现实。     

高速公路收费站车辆能耗研究

车辆通过高速公路收费站时,需要减速或停车缴费,当车辆较多时,容易形成排队,产生大量延误,大大削弱了车辆的运行效率,增加了车辆的能耗,同时使得车辆尾气的排放量增加,严重污染了环境。本文使用排队论知识对收费站车辆排队与疏散情况进行分析,减少车辆的排队等候时间和驶离站口所需时间,以达到减少行车能耗的目的。最后,通过一个实例给出几种收费方式下的能耗,并给出了相应的分析和建议,可为高速公路收费方式和能耗研究提供一定的参考。