粘连蚕卵图像分离算法研究

针对蚕卵图像中存在的粘连或者部分重叠现象,本文提出了一种新的分离方法。该方法先采用模糊C均值聚类算法将蚕卵图像从背景中分割,然后采用模糊距离变换得到模糊距离图像,最后使用分水岭算法将粘连或者部分重叠蚕卵分离。实验证明,此法能够将粘连颗粒物图像有效分离。     

地铁车辆辅助逆变器的设计与仿真

以地铁车辆用DC1500V/160kVA辅助逆变器为例,阐述了采用IGBT作为主要开关元件的主电路及其控制系统,并利用MATLAB/SIMULINK进行仿真验证其可行性,最后给出了采用电压空间矢量控制的仿真结果。     

改善刚柔过渡区域弓网关系的探讨

对刚柔过渡区域刚性和柔性接触网的弹性不同及接触线高度不等情况进行了定性及定量分析,找出该区域弓网关系恶劣的原因,并针对原因提出改善刚柔过渡区域弓网关系的解决方案。     

在汽车装备企业联合共建工程中心的意义

为了落实我国智能制造发展规划(2015-2025年)指导精神,以我国汽车产业链智能制造需求为导向,加快提升新能源汽车智能装备系统研发与集成工程技术能力,全面实现我国汽车智能制造自主创新体系和国产化水平,在机器人应用最为广泛的汽车及其零部件行业大力发展智能装备与系统、培育发展系统集成及其应用,成为了当前我国智能制造202...     

关于城市轨道交通列车编组形式的探讨

城市轨道交通列车编组形式是确定轨道交通工程规模的重要原则之一。以预测客流量为依据,从行车运营的几个重要指标来分析、比较初期、近期、远期的3个列车编组方案,最后对列车编组方案进行论述,给相关工程提供借鉴。     

马来西亚东海岸铁路CTCS-2级列控系统方案研究

对马来西亚东海岸铁路CTCS-2级列控系统方案进行了分析和研究;针对单线自动站间闭塞情况提出了CTCS-2级列控系统方案;通过综合比较后提出马来西亚东海岸铁路列控系统推荐方案,可为CTCS-2级列控系统在单线自动站间闭塞中的应用提供一定参考.     

四面六边透水框架自动同步抛投装置与工艺

针对四面六边透水框架抛投效率低、成本高、准确度低、存在安全隐患等问题,建立四面六边透水框架抛投漂移距离的数学模型,得出抛投高度、水深、水流速度、透水框架阻水面积等参数对漂移距离的影响规律。提出一种大框架、多转轴的空中自动同步脱钩抛投吊具,增加每次抛投透水框架的数量,并采用GPS引导抛投船舶精准定位,对抛投作业过程进行实时控制。结果表明,此种抛投装置可提高透水框架抛投的准确性,且提高施工效率。     

Towards connected autonomous driving: review of use-cases

Connected autonomous vehicles are considered as mitigators of issues such as traffic congestion, road safety, inefficient fuel consumption and pollutant emissions that current road transportation system suffers from. Connected autonomous vehicles utilise communication systems to enhance the performance of autonomous vehicles and consequently improve transportation by enabling cooperative functionalities, namely, cooperative sensing and cooperative manoeuvring. The former refers to the ability to share and fuse information gathered from vehicle sensors and road infrastructures to create a better understanding of the surrounding environment while the latter enables groups of vehicles to drive in a co-ordinated way which ultimately results in a safer and more efficient driving environment. However, there is a gap in understanding how and to what extent connectivity can contribute to improving the efficiency, safety and performance of autonomous vehicles. Therefore, the aim of this paper is to investigate the potential benefits that can be achieved from connected autonomous vehicles through analysing five use-cases: (i) vehicle platooning, (ii) lane changing, (iii) intersection management, (iv) energy management and (v) road friction estimation. The current paper highlights that although connectivity can enhance the performance of autonomous vehicles and contribute to the improvement of current transportation system performance, the level of achievable benefits depends on factors such as the penetration rate of connected vehicles, traffic scenarios and the way of augmenting off-board information into vehicle control systems.     

Consumer preferences for battery electric vehicles: A choice experimental survey in China

To accelerate the diffusion of battery electric vehicles (BEVs), consumer preferences for different products and policy attributes must be determined. Although previous studies have investigated consumer preferences for some product attributes, including purchase price, operation cost, driving range, and charging time, limited studies have discussed the broader aspects of product attributes, such as battery warranty and depreciation rate. Moreover, market-oriented incentives, including the personal carbon trading (PCT) scheme and the tradable driving credits (TDC) scheme, can theoretically be effective alternatives to expensive purchase subsidies. However, there is a lack of empirical evidence that confirms the influence of these two schemes on BEV adoption. To fill these gaps, we conducted a stated preference choice experimental survey in China and investigated the effect of product attributes, existing policy incentives, and two emerging market-oriented incentives on BEV adoption. Our results reveal that along with the main product attributes, battery warranty has a significant positive effect on inducing mainstream consumers to adopt BEVs while no preference difference occurs among existing policy incentives after purchase subsidies are abolished. For young consumers, almost all incentives that reduce the operation cost (e.g., PCT) or increase convenience (e.g., TDC) can increase their adoption of BEVs. These findings can provide important implications for the government with regard to designing novel incentives and promoting BEV adoption.     

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.