纯电骡子车开发及试制新方法应用

通过对比燃油汽车与纯电动汽车整车架构,分析燃油车改制纯电动骡子车的可行性.利用现有车型完成纯电动骡子车改制,不仅可以节省开发成本,还可以加快新产品升级换代.同时基于两种车型的差异性,制定相应的车型改制方案.阐述常见的改制内容与创新方法应用,为后续同平台新车型开发提供参考.     

基于“1+3”的复合型人才课程体系的探索与实践——以新能源汽车技术专业为例

当前时期,针对复合型人才教学体系的创新,应当有对性地构建起更加完善的人才培养体系,并做好对于学生的专业性知识技能和专业性职业技能优化培养。结合现阶段的新能源汽车技术专业培养,要针对把握性教学标准和教学要求,做好有效性的更新和完善,本文主要结合基于1+3的复合型人才课程体系的探索与实践展开了研究分析。     

新媒体环境下全地形车营销策略分析

互联网+和大数据技术的不断发展和进步让信息经济时代真正地到来了.伴随着电子商务从起步到发展,很多的电商运营平台也逐渐凸显出自己的价值和地位.与此同时,电子商务的营销模式也从传统的B2B、B2C模式向着O2O、C2B的方向发展.全地形车,是一种十分独特的车型,适用的范围和人群也具有特定性.为此,在新媒体的环境之下,如何进...     

基于深度学习的智能车辆视觉里程计技术发展综述

针对基于模型的视觉里程计在光照条件恶劣的情况下存在鲁棒性差、回环检测准确率低、动态场景中精度不够、无法对场景进行语义理解等问题,利用深度学习可以弥补其不足。首先,简略介绍了基于模型的里程计的研究现状,然后对比了常用的智能车数据集,将基于深度学习的视觉里程计分为有监督学习、无监督学习和模型法与深度学习结合3种,从网络结构、输入和输出特征、鲁棒性等方面进行分析,最后,讨论了基于深度学习的智能车辆视觉里程计研究热点,从视觉里程计在动态场景的鲁棒性优化、多传感器融合、场景语义分割3个方面对智能车辆视觉里程计技术的发展趋势进行了展望。     

电动汽车整车运行性能检测试验技术

电动汽车的生产和制造需要符合相关的标准,并且还要对整车的性能进行测试,只有这样才能更好的符合汽车上路的条件。本文主要是将国标要求作为基础来对电动汽车的最高车速、滑行能力、加速性能、制动性能和爬坡能力和能量消耗率和续航里程进行测试,通过实施一定的检测试验方法和配套的相关试验设备来做好检测,并且要对测试的结果进行分析,对电动汽车的运行性能进行进一步的优化,从而推进我国电动汽车行业的更好发展和进步。     

电动汽车大数据处理活动中的伦理问题研究

为了解车辆零部件运行状态,分析整车故障原因,技术人员通过车载终端把电动汽车的整车控制系统各节点发送至大数据平台进行查阅、分析和下载使用.大数据的使用引发了信息工程领域的伦理问题.本文重点阐述了电动汽车产业运用大数据时可能产生的伦理问题及其产生原因,探索强化责任、加强职业道德教育等解决办法,并结合伦理学理论提出了建议.     

纯电动物流车用PMSM降开关损耗控制

物流车是城市内部运送货物的重要交通工具,具有运行距离短、启停频率高、运行时间长的特点.城市内部物流车都逐步采用纯电动物流车代替传统的燃油车.针对物流车运行特点,文章对电动物流车电机控制算法进行优化,在考虑不同工况下使用不同的开关频率,降低开关损耗,减少控制器发热.通过对降低开关损耗控制方法与传统控制方法在不同车辆运行工...     

我国商用车底盘运输车的发展现状分析

根据国外商用车底盘运输模式,对国内商用车底盘运输现状进行分析,并以国内首辆商用车底盘运输半挂车为例,介绍其产品特点和综合社会经济效益。结合现有的基本国情和法规,提出了商用车底盘运输的发展建议。     

Strategies to achieve deep reductions in metropolitan transportation GHG emissions: the case of Philadelphia

ABSTRACT

This paper investigates strategies that could achieve an 80% reduction in transportation emissions from current levels by 2050 in the City of Philadelphia. The baseline daily lifecycle emissions generated by road transportation in the Greater Philadelphia Region in 2012 were quantified using trip information from the 2012 Household Travel Survey (HTS). Emissions were projected to the year 2050 accounting for population growth and trends in vehicle technology for both the Greater Philadelphia Region and the City of Philadelphia. The impacts of vehicle technology and shifts in travel modes on greenhouse gas (GHG) emissions in 2050 were quantified using a scenario approach. The analysis of 12 different scenarios suggests that 80% reduction in emissions is technically feasible through a combination of active transportation, cleaner fuels for public transit vehicles, and a significant market penetration of battery-electric vehicles. The additional electricity demand associated with greater use of electric vehicles could amount to 10.8 TWh/year. The use of plug-in hybrid electric vehicles (PHEV) shows promising results due to high reductions in GHG emissions at a potentially manageable cost.     

Extracting driving characteristics from heavy goods vehicle tachograph charts

European Union regulations require haulage companies of member states like the UK to keep records of their drivers’ hours of work. All heavy goods vehicles (HGV's) over 7.5 tonnes are fitted with tachographs which record a driver's operating activities (periods of driving, other work and rest). These records are etched onto a laminated chart by various styli, one of which records the vehicle's speed. This paper describes the development and testing of a new technique for extracting individual driving characteristics from the speed trace of an HGV tachograph chart to calculate four parameters: distance travelled, average speed, time travelled and speed variability.

The average speed, time travelled and speed variability were analysed statistically using one‐way analysis of variance tests. Speed variability was found to be particularly useful for identifying differences between individual driver's behaviour. Once differences in behaviours can be identified it may be possible to link certain driving habits to factors such as component wear, accident rates and excessive fuel usage.