中国新能源汽车的发展现状及未来展望

随着全球能源和生态环境面临严峻挑战,节能和新能源汽车是解决中国能源和环境问题的关键措施,那么新能源汽车的推广也就会越来越广泛。对于不同技术的前景,产业界和学术界尚未达成共识。本文首先介绍了新能源汽车的概念和发展历史,讲述了我国纯电动汽车、插电式混合动力汽车和燃料电池汽车的发展现状,并进一步分析了目前新能源汽车产业的发展机遇,并对其未来发展前景进行展望。最后,针对新能源汽车动力电池技术、安全性、基础设施建设等方面存在的问题,提出发展建议。     

氢燃料内燃机技术现状与发展展望

介绍了氢气及氢燃料内燃机的特点及氢燃料内燃机的技术现状。通过对比分析指出氢燃料内燃机既可以采用清洁可再生能源,又可以充分利用现有的庞大工业体系,是实现氢气经济的现实途径。     

新能源汽车车载终端下线检测系统设计

在车辆的生产过程中,除了需要确保车辆装配正常,还需要确保各个零件功能正常才能确保车辆正常下线。传统的车辆下线检测系统,需要人为的对车辆的识别码、车载终端的各路参数进行人工记录和比对,再将参数录入后台系统,耗费人力较多,检测耗时也较长,车辆下线检测的效率也较低。同时,通常的下线检测过程中,未对车载设备的正常运行进行判断,如果将问题车载终端装车下发,会导致监控平台无法对该车辆进行正常监控,存在安全隐患,也不满足相关要求,同时增加售后维护成本。基于此,本文设计开发了一种新能源汽车车载终端下线检测系统,实现了新能源车辆在出厂时,通过检测时,由检测人员操作该系统来查看终端工作状态,系统自动根据终端返回平台信息判断该终端工作是否正常,然后把结果反馈至生产系统。     

汽车强国战略背景下H市新能源汽车销售影响因素分析

本文主要从市场角度出发,以H市为例,对影响消费者购买新能源汽车的因素进行分析,应用实证分析方法,构建出影响因素分析体系,对收集到的市场数据提取出相关变量,然后进行变量的显著性检验及分析,最后在此基础上提出政策建议。     

探索新能源汽车充电设施的电气设计

现如今,新能源电动汽车充电装置电气设计,得要顺应现代化实际需求与发展趋势。在后期发展阶段之中,新能源汽车会引领着整个汽车行业的发展,当然也可以凸显出节能减排、绿色出行的优势。因此在新能源项目发展阶段之中,针对新能源汽车充电设施实施电气设计至关重要。鉴于此,本文主要分析新能源汽车充电设施的电气设计。     

基于用户认知的新能源汽车内饰研究

在体验经济时代(在消费过程中追求顾客满意、注重自我体验),新能源汽车作为汽车行业的新兴产业,不断受到人们的追捧,其内饰比外观更为重要。在新能源汽车的内饰中,许多零部件具有不可替代的互动性,这也是用户了解新能源汽车内饰的关键因素之一。在智能化时代的背景下,大多数新能源汽车制造商单纯地将智能技术应用到新能源汽车上,其内饰造型、人机交互和使用体验已经不能满足客户对新能源汽车的要求。人机工程学是新能源汽车内饰设计的出发点,掌握用户形象认知是新能源汽车内饰设计的关键。因此,本文从用户的认知角度来研究新能源汽车的内饰设计与创新。     

技工院校新能源汽车技能人才培养探索

素质教育背景下,技工院校的人才培养不仅要具备较高的职业综合素养、专业技能知识储备与技能实践能力,还需要具备较高的人才市场核心竞争力与岗位适应能力。但就目前我国技工院校的新能源汽车专业课程教学现状来看,还存在很多教学问题,需要改变传统的教学形式与教学观念,积极探索顺应时代发展的专业技能人才培养模式,才能够有效满足企业对新能源汽车专业人才的岗位需求,促进新能源汽车行业的健康可持续发展。本文以技工院校新能源汽车技能人才培养探索为主要的论点,结合教学实际情况提出了能够提升技工院校新能源汽车技能人才培养质量的有效策略,仅供参考。     

基于生长曲线函数的货车运营环节碳达峰研究

货车是我国大气环境污染的重要来源之一,也是影响我国碳达峰总体目标实现的重要因 素。本文从货车运营环节入手,在运用生长曲线函数对货车保有量进行预测的基础上,对不同类 型货车的保有量和单车碳排放变化进行研究,并从货车节能技术发展、新能源货车推广和应用进 程两方面入手,分3种情景对货车运营环节中产生的碳排放总量趋势进行预判,推演货车运营环 节的碳达峰时间。研究结果表明,只有同时加快货车节能技术发展以及新能源货车推广和应用 进程,货车运营环节中产生的碳排放总量规模才能得到有效抑制并逐渐减少。若到 2030 年货 车单车燃料消耗水平较 2019 年降低 20%以上,新能源货车在货车整体保有量中的占比达到 20%,到 2060 年货车单车燃料消耗水平较 2019 年降低 50%,新能源货车占比达到 50%,则货车 运营环节碳达峰时间将缩短至2030年左右实现,2030年后货车运营环节产生的碳排放总量规 模将逐渐减少。     

Weight threshold estimation of falling UAVs (Unmanned Aerial Vehicles) based on impact energy

Different weight thresholds for drone operations have been specified by regulatory agencies in different countries, without detailed backgrounds of guidelines. Therefore, this paper aims to study weight thresholds by focusing different levels of injuries caused by the impact of the drones on human head of different weights dropped at various heights. The work covers drone free drop modelling, FEM (finite element method) based impact modeling, and comparable drop impact experiments. The analyses and experiments were conducted accordingly to two individual commercially-available groups: small and large drones in weights. Two well-established indicators defining head injuries due to impact, which are known as Head Injury Criterion (HIC) and Abbreviated Injury Scale (AIS), are used in the present weight threshold study. The proposed AIS level for the weight threshold estimation has been set at AIS level 3, which indicates major skull fracture, in the further analysis through the probability of fatality. The main focus of the present work is to perform a parametric study and to present a reliable model to estimate the weight thresholds of the drone operations based on HIC and AIS. In conclusion, the results obtained and presented in this paper have demonstrated and provided a comprehensive analysis of possible direct injuries of a falling drone impacting a human head, with relevant data of impact or injury levels associated with HIC and AIS obtained for a drone with different weights falling from various heights.     

The impact of land-use mix on residents' travel energy consumption: New evidence from Beijing

Policies that encourage mixed land use are widely believed to make transport more energy efficient. However, few studies have directly examined the impacts of land-use heterogeneity on travel energy consumption at the individual level. Moreover, the definition and measures of land-use heterogeneity are debated. This paper aims to fill these gaps using the large city of Beijing, China, as a case study. Three types of land use are examined in terms of their effects on individual residents’ travel energy consumption. The results suggest that high land-use diversity and a good jobs-housing balance significantly reduces commuting travel. Interestingly, highly heterogeneous retail and housing areas may have high travel energy use, as residents are more likely to go shopping. There are obvious spatial variations in these effects. Residents of suburban ‘newtowns’, where the jobs-housing balance is particularly good, consume less travel energy. The results suggest that decreased use of conventional planning patterns, such as the socialist danwei system, and increasing urban sprawl, bring new challenges to achieving transport efficiency. Mixed land-use policies can be an effective solution to these challenges.