半潜式航行器运动特性研究

论文研究了半潜式航行器的运动特性,建立了半潜式航行器的运动学模型,并从深度控制和回转航行两个方面对半潜式航行器的运动特性进行半实物仿真。半实物仿真结果表明：前水平舵是影响深度控制的主要因素,并得出前水平舵舵角和深度的对应关系;回转航行研究了航行器的垂直舵角、航速和回转半径的关系,得出了在一定航速下,不同垂直舵角下的回转半径。此研究准确把握了半潜式航行器的运动规律,为半潜式航行器的设计以及精确控制提供了理论基础。     

浅议新能源汽车驱动电机维护保养与故障维修

随着对环境保护的重视,国家大力扶持新能源汽车产业的建设和发展,相关政策不断推出,各大车企也纷纷投入到新能源汽车的生产和研发中来.驱动电机作为新能源汽车的三大核心部件之一,在新能源汽车销量不断攀升的情况下,其维护、保养以及维修的需求也在增加.本文从驱动电机的原理和构造出发,简要论述新能源汽车驱动电机维护保养的主要方法以及...     

新能源汽车产业背景下的车辆工程专业人才培养变革

随着新能源汽车产业的发展及国家新能源汽车产业发展规划的颁布,传统基于燃油车的车辆工程专业的人才培养方案已不能满足市场发展的要求.为此,我们对新能源汽车产业的发展方向和新能源汽车产业对车辆工程专业人才需求进行分析,对车辆工程专业的人才培养进行了思考并提出改革的措施.     

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...     

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。     

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.     

Electric vehicle charging station locations: Elastic demand,station congestion,and network equilibrium

Battery-only electric vehicles (BEVs) generally offer better air quality through lowered emissions, along with energy savings and security. The issue of long-duration battery charging makes charging-station placement and design key for BEV adoption rates. This work uses genetic algorithms to identify profit-maximizing station placement and design details, with applications that reflect the costs of installing, operating, and maintaining service equipment, including land acquisition. Fast electric vehicle charging stations (EVCSs) are placed across a congested city's network subject to stochastic demand for charging under a user-equilibrium traffic assignment. BEV users’ station choices consider endogenously determined travel times and on-site charging queues. The model allows for congested-travel and congested-station feedback into travelers’ route choices under elastic demand and BEV owners’ station choices, as well as charging price elasticity for BEV charging users.Boston-network results suggest that EVCSs should locate mostly along major highways, which may be a common finding for other metro settings. If 10% of current EV owners seek to charge en route, a user fee of $6 for a 30-min charging session is not enough for station profitability under a 5-year time horizon in this region. However, $10 per BEV charging delivers a 5-year profit of $0.82 million, and 11 cords across 3 stations are enough to accommodate a near-term charging demand in this Boston-area application. Shorter charging sessions, higher fees, and/or allowing for more cords per site also increase profits generally, everything else constant. Power-grid and station upgrades should keep pace with demand, to maximize profits over time, and avoid on-site congestion.     

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.     

基于交通信息的电动汽车制动策略及仿真

为了提高滑行能量回收经济性和踏板制动安全性、舒适性,基于交通信息,提出了电动汽车(EV)制动协调策略。分析了滑行制动的经济性,由交通信息和汽车行驶状态确定滑行制动强度;由道路信息和前方车辆信息建立汽车安全距离模型和碰撞预警策略,利用预警信息对滑行制动和踏板制动强度进行协调。对本策略进行仿真验证。结果表明:利用交通信息的滑行策略,在通行良好工况下综合能耗减少1.1%,拥堵工况下减轻驾驶员的制动疲劳;预警和协调策略避免了频繁预警,减小了紧急避撞触发几率。因此,利用交通信息能够辅助驾驶员进行更加合理的制动。