轨道交通车辆的工艺流程标准化

从生产线建立、工艺流程编制、工艺布局设计和生产能力等方面进行分析,提出了轨道交通车辆工艺流程标准化设计方法和优化方法。基于精益管理理念和工序能力测算法,可以合理编制标准化工艺流程,从而降低劳动强度,提高生产效率。     

上海松江区现代有轨电车规划研究

现代有轨电车因其环保、舒适、高效、低造价、高品质等特点,在国际上得到广泛应用,我国多个城市也在规划和建设之中。但是,由于其在国内尚为一种全新的交通方式,没有标准或规范予以指导,规划及设计体系不完善,有些已建项目已呈现问题。文章结合上海松江区规划背景及交通特征,阐述有轨电车示范线T1、T2线的布局规划、建设的必要性及适应性,为即将开展有轨电车规划及建设的城市提供借鉴与参考。     

Eco-driving behaviors of electric vehicle users: A survey study

Previous research has shown that electric vehicle (EV) users could behave differently compared to internal combustion engine vehicle (ICEV) drivers due to their consciousness or practices of eco-driving, but very limited research has fully investigated this assumption. This research explores this topic through investigating EV drivers’ eco-driving behaviors and motivations. We first conducted a questionnaire survey on EV drivers’ driving behavior and some hypothetical decisions of their driving. It indicates various characteristics between EV and ICEV commuters, including self-reported daily driving habits, preferences of route choices, tradeoff between travel time and energy saving, and adoption of in-vehicle display (IVD) technologies. Then, through statistical analysis with Fisher’s exact test and Mann-Whitney U test, this research reveals that, compared to ICEV drivers, EV drivers possess significantly calmer driving maneuvers and more fuel-efficient driving habits such as trip chaining. The survey data also show that EV drivers are much more willing to save energy in compensation of travel time. Furthermore, the survey data indicate that EV drivers are more willing to adopt eco-friendly IVD technologies. All these findings are expected to improve the understanding of some unique behavior found in EV drivers.     

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.     

Delivering improved alerts,warnings, and control assistance using basic safety messages transmitted between connected vehicles

When vehicles share their status information with other vehicles or the infrastructure, driving actions can be planned better, hazards can be identified sooner, and safer responses to hazards are possible. The Safety Pilot Model Deployment (SPMD) is underway in Ann Arbor, Michigan; the purpose is to demonstrate connected technologies in a real-world environment. The core data transmitted through Vehicle-to-Vehicle and Vehicle-to-Infrastructure (or V2V and V2I) applications are called Basic Safety Messages (BSMs), which are transmitted typically at a frequency of 10 Hz. BSMs describe a vehicle’s position (latitude, longitude, and elevation) and motion (heading, speed, and acceleration). This study proposes a data analytic methodology to extract critical information from raw BSM data available from SPMD. A total of 968,522 records of basic safety messages, gathered from 155 trips made by 49 vehicles, was analyzed. The information extracted from BSM data captured extreme driving events such as hard accelerations and braking. This information can be provided to drivers, giving them instantaneous feedback about dangers in surrounding roadway environments; it can also provide control assistance. While extracting critical information from BSMs, this study offers a fundamental understanding of instantaneous driving decisions. Longitudinal and lateral accelerations included in BSMs were specifically investigated. Varying distributions of instantaneous longitudinal and lateral accelerations are quantified. Based on the distributions, the study created a framework for generating alerts/warnings, and control assistance from extreme events, transmittable through V2V and V2I applications. Models were estimated to untangle the correlates of extreme events. The implications of the findings and applications to connected vehicles are discussed in this paper.     

城市轨道交通车辆产品标准体系探索

分析了国内外城市轨道交通车辆产品标准体系的现状,重点介绍了城市轨道交通车辆产品标准体系的总体要求、结构搭建、产品标准的制修订,以及标准的实施和改进措施。     

船舶低硫柴油系统设计的分析与优化

就新辟航线首制船“汉亚直达”集装箱船的低硫柴油系统,叙述了船舶低硫柴油系统的设计经验,从当前国内外对船用燃油硫含量的要求、应对方案到船舶低硫柴油冷却方式选择、低硫柴油冷却系统设计、高/低硫柴油转换、使用低硫柴油风险分析及处理等方面进行详细叙述,为业内同行提供参考。     

CACC车头时距与混合交通流稳定性的解析关系

研究协同自适应巡航控制(Cooperative Adaptive Cruise Control，CACC)车头时距对不同CACC比例下混合交通流稳定性的影响关系，进而为CACC车头时距设计提供参考. 应用优化速度模型(Optimal Velocity Model，OVM)作为手动车辆的跟驰模型，PATH真车实验标定的模型作为CACC车辆的跟驰模型. 基于传递函数理论，推导混合交通流稳定性判别条件，计算关于CACC比例与平衡态速度的混合交通流稳定域. 分析混合交通流在任意速度下稳定所需满足的临界CACC比例与CACC车头时距的解析关系，提出随CACC比例增加的可变 CACC车头时距设计策略，并通过数值仿真实验验证所提可变CACC车头时距策略的正确性. 研究结果表明：在所提可变CACC车头时距策略下，CACC车头时距随CACC比例增加而逐渐降低，避免取值较大影响混合交通流通行能力的提升；当CACC比例大于35%时，混合交通流在任意速度下稳定.研究结果可为大规模CACC真车实验的实施提供理论设计参考.     

船用厨房和具有烹调设备的配餐室的通风计算及空气处理方法

本文介绍了ISO 9943-2009国际标准和GBT 20846-2007中国国家标准中对船用厨房和具有烹调设备的配餐室的通风计算及空气处理中提出的送风量的计算方法，提出另一种更易于大家理解和接受的简易计算方法和空气处理过程，供工程技术及设计研究人员参考。