混联式混合动力汽车驱动控制与节能分析

混合动力汽车的节能减排的优势在于搭载了电动机,发动机与电机的合理搭配及其控制策略,是提高汽车经济性和动力性的关键。本文从混联式混合动力汽车的结构特点出发,分析了汽车运行与节能的关系,阐述了发动机与电机之间动能分配与能量回收控制策略,以及在混联式混合动力汽车上的具体运用。     

插电混动汽车在限行政策下的困境与出路

本文通过走访调研的形式,针对限行政策下插电混动汽车因无法及时辨别运行模式而被导致不公平罚款的这一艰难处境,通过对比分析、分组分析等方法分析出插电混动汽车企业当前所面临的困境和受到的限制,并结合调查情况总结出当下插电混动汽车面临如此问题的相应背景状况和具体原因;随后提出创新型的设计理念,改进插电混动汽车在不同条件下行驶状态及时间的指示指标,预期通过设计亮灯装置、时间装置等设备,来显示插电混动汽车行驶中所处的动力模式及相应行驶时间,以期为生产管理部门和相关执法部门提出建议,为今后新能源汽车的生产改进及限行政策的顺利实施提供相应的借鉴与参考.     

主动悬架系统模式切换控制策略研究

针对在不同工况下车辆行驶时对于主动悬架系统的性能需求,本文设计出一种可切换悬架工作模式的悬架控制策略,可以提高车辆在不同工况下行驶时的动力学性能。通过对控制策略进行建模仿真,结果得出相较于未进行模式切换的悬架,所设计的模式切换控制策略可以有效改善悬架工作时的性能,为后续控制参数的优化提供了研究基础。     

燃油添加剂对汽车排放性能影响分析研究

国内对于燃油添加剂效果的分析研究较少,文章为了探讨某型燃油添加剂对在用车排放和性能的影响,依据GB18285-2005《点燃式发动机汽车排气污染物排放限值及测量方法》,针对不同行驶里程的汽车,选用双怠速法检测汽车使用某型号燃油添加剂前后的排放变化,并对油耗和动力性进行简单测评。结果表明,使用燃油添加剂和选择合适标号燃油能有效降低汽车污染物排放及油耗,对车辆使用节能减排具有较为重要意义。     

对大通县汽车检测与维修的思考

随着社会经济的发展,交通也越来越发达,人们出行离不开各种各样的交通工具。随着我国居民收入水平不断提高,家庭汽车购买数量呈逐年增加倾向。车辆不但方便了人们的出行,而且对于人们的生产生活和社会经济发展发挥着重要作用。所以车辆安全的检测以及故障的维修具有重要的意义。我们个人一定要加强二次维修的意识,自觉主动的进行车辆的检测与维修,同时相关的部门必须加强检查监督的力度,建立健全监察体系,使得当代维修检测体系规范化、制度化,保障人民的生命财产安全。     

高校“汽车医院”建设的必要性与可行性分析

现代的汽车像人一样,人有生病的时候,生病了要去医院就诊,汽车也有出故障的时候,那么出了故障及要去汽车修理厂进行维修。把现代汽车维修企业比作医院,在目前的汽修领域显的尤为恰当。把汽车维修企业与当今高等教育结合,让高等教育来辅助车辆维修技术,让车辆维修技术更好的融入高等教育教学实践当中,由此,建立基于高校的“汽车医院”具有强烈的必要性和健康的可行性。这一概念对于高校汽车运用技术专业具有十分重要的意义,它不仅能够为高校本身争取社会效益,更能让学生在校提早接触到汽车维修一线,得到锻炼和宝贵的工作经验,为以后走向工作岗位打下坚实的基础。     

高校“汽车医院”建设的必要性与可行性分析

现代的汽车像人一样,人有生病的时候,生病了要去医院就诊,汽车也有出故障的时候,那么出了故障及要去汽车修理厂进行维修。把现代汽车维修企业比作医院,在目前的汽修领域显的尤为恰当。把汽车维修企业与当今高等教育结合,让高等教育来辅助车辆维修技术,让车辆维修技术更好的融入高等教育教学实践当中,由此,建立基于高校的"汽车医院"具有强烈的必要性和健康的可行性。这一概念对于高校汽车运用技术专业具有十分重要的意义,它不仅能够为高校本身争取社会效益,更能让学生在校提早接触到汽车维修一线,得到锻炼和宝贵的工作经验,为以后走向工作岗位打下坚实的基础。     

振动减速带的速度控制效果研究

车速是影响道路交通安全的一个重要因素,提高速度控制技术的功效,对于改善道路安全性具有重要的意义。文章通过对振动减速带的车辆速度进行观测和分析,评价了速度控制设施的减速效果。     

钢-混组合箱梁的车桥耦合振动影响分析

随着对于钢-混组合箱梁结构研究的深入开展,其在车辆荷载作用下的车桥振动响应问题也备受关注。不同截面形式对其车-桥相互作用性能有着较大影响。文章基于模态综合法的原理,建立两种不同截面形式的钢-混组合箱梁的动力计算模型,并对其动力特性进行了比较分析,结果表明：双车响应大致为单车响应的两倍,说明不同车辆荷载作用下桥梁的反应是线性的,为以后此类桥梁的设计提供参考。     

特种车辆在电力生产中的应用

特种车辆在电力生产中的应用已成为电力行业中备受关注的研究领域。本文探究了特种车辆在电力生产中的实际应用价值,采用实地调研和数据分析的方法对电力生产现场特种车辆的运用情况进行深入研究和评估,对于提高电力生产效率、降低生产成本以及优化资源配置等具有重要意义,以期进一步提高电力生产效率和安全性,为电力行业的发展和满足其市场需求提供实际指导。     

Development a new power management strategy for power split hybrid electric vehicles

Reduction of greenhouse gas emission and fuel consumption as one of the main goals of automotive industry leading to the development hybrid vehicles. The objective of this paper is to investigate the energy management system and control strategies effect on fuel consumption, air pollution and performance of hybrid vehicles in various driving cycles. In order to simulate the hybrid vehicle, the combined feedback–feedforward architecture of the power-split hybrid electric vehicle based on Toyota Prius configuration is modeled, together with necessary dynamic features of subsystem or components in ADVISOR. Multi input fuzzy logic controller developed for energy management controller to improve the fuel economy of a power-split hybrid electric vehicle with contrast to conventional Toyota Prius Hybrid rule-based controller. Then, effects of battery’s initial state of charge, driving cycles and road grade investigated on hybrid vehicle performance to evaluate fuel consumption and pollution emissions. The simulation results represent the effectiveness and applicability of the proposed control strategy. Also, results indicate that proposed controller is reduced fuel consumption in real and modal driving cycles about 21% and 6% respectively.     

基于AMESim的插电式并联混合动力汽车能量管理策略仿真分析

为了缩短混合动力汽车开发时间,减少开发成本,本文以插电式并联混合动力汽车为研究对象,针对设计指标进行动力系统参数匹配以及使用AMESim软件搭建了整车模型,然后设计了基于门限值的能量管理策略并使用AMESim软件中的Signal,Control库进行搭建。之后对已搭建完成的车辆进行动力性经济性仿真分析,其中经济性分析是在NEDC工况下进行的,验证了本文所搭建策略和整车模型的正确性和可行性。     

并联混合动力汽车改进模糊控制策略研究

本文提出一种兼顾电池SOC限值方法的混合动力汽车多种群遗传模糊控制策略。引入模糊逻辑控制以增强整车控制系统鲁棒性、实时性;用多种群遗传算法对模糊变量隶属度函数进行优化,使在模糊逻辑控制下整车燃油消耗得到降低;使用电池SOC限值方法避免电池在SOC过低时继续放电。利用matlab平台联合advisor软件进行联合仿真实验,仿真结果表明多种群遗传模糊模糊控制策略能够比advisor软件默认的电机辅住控制策略燃油经济性提高6.96%的情况,SOC限值方法使电池工作在更加合理的SOC值区间范围内,有效保护电池。     

公共充电站在基础设施建设中的规划与研究

随着我国社会经济发展水平的不断提高,汽车使用量持续攀高。大力发展新能源汽车,能够促进资源充分利用,减少汽车尾气排放,对保障能源安全、促进节能减排、防治大气污染、推动我国能源可持续发展具有重要意义。随着电动汽车的推广使用,电动汽车对充电站的基础设施建设以及服务网络的完善等需求日益紧迫。充电基础设施的建设,用以满足电动汽车的发展需求,并以充电设施、充电系统的适度超前发展引导电动汽车的业务发展。     

基于ADVISOR的纯电动汽车动力系统匹配及仿真

纯电动汽车作为新能源汽车行业发展的主要方向,在发展其核心技术中,动力系统的匹配对于发展纯电动汽车具有重要的意义,合理的动力系统匹配影响着汽车的动力性和续航里程等因素。根据纯电动汽车的整车参数和性能指标,计算选择动力系统的基本参数,并利用ADVISOR仿真软件进行仿真分析,为改进技术提供依据,验证了设计的有效性。     

A hybrid controller for autonomous vehicles driving on automated highways

This paper addresses the problem of the hybrid control of autonomous vehicles driving on automated highways. Vehicles are autonomous, so they do not communicate with each other nor with the infrastructure. Two problems have to be dealt with: a vehicle driving in a single-lane highway must never collide with its leading vehicle; and a vehicle entering the highway at a designated entry junction must be able to merge from the merging lane to the main lane, again without any collision. To solve these problems, we equip each vehicle with a hybrid controller, consisting of several continuous control laws embedded inside a finite state automaton. The automaton specifies when a given vehicle must enter the highway, merge into the main lane, yield to other vehicles, exit from the highway, and so on. The continuous control laws specify what acceleration the vehicle must have in order to avoid collisions with nearby vehicles. By carefully designing these control laws and the conditions guarding the automaton transitions, we are able to demonstrate three important results. First, we state the initial conditions guaranteeing that a following vehicle never collides with its leading vehicle. Second, we extend this first result to a lane of autonomous vehicles. Third, we prove that if all the vehicles are equipped with our hybrid controller, then no collision can ever occur, and all vehicles either merge successfully or are forced to drop out when they reach the end of their merging lane. Finally, we show the outcome of a highway microsimulation modelled after the Katy Corridor near Houston, Texas: our single-lane highway can accommodate 4000 vehicles per hour with neither drop-outs nor traffic congestion. It is entirely programmed in SHIFT, a hybrid systems simulation language developed at UC Berkeley by the PATH group. This shows that SHIFT is a well suited language for designing safe control laws for autonomous highway systems, among others.     

Hierarchical control strategies for energy management of connected hybrid electric vehicles in urban roads

This paper presents a fuel efficient control strategy for a group of connected hybrid electric vehicles (HEVs) in urban road conditions. A hierarchical control architecture is proposed in this paper for every HEV, where the higher level and the lower level controller share information with each other and solve two different problems that aim at improving its fuel efficiency. The higher level controller of each HEV is considered to utilize traffic light information, through vehicle to infrastructure (V2I) communication, and state information of the vehicles in its near neighborhood, via vehicle to vehicle (V2V) communication. Apart from that, the higher level controller of each HEV uses the recuperation information from the lower level controller and provides it the optimal velocity profile by solving its problem in a model predictive control framework. Each lower level controller uses adaptive equivalent consumption minimization strategy (ECMS) for following their velocity profiles, obtained from the higher level controller, in a fuel efficient manner. In this paper, the vehicles are modeled in Autonomie software and the simulation results are provided in the paper that shows the effectiveness of the proposed control architecture.     

Forward power-train energy management modeling for assessing benefits of integrating predictive traffic data into plug-in-hybrid electric vehicles

In this paper, a forward power-train plug-in hybrid electric vehicle model with an energy management system and a cycle optimization algorithm is evaluated for energy efficiency. Using wirelessly communicated predictive traffic data for vehicles in a roadway network, as envisioned in intelligent transportation systems, traffic prediction cycles are optimized using a cycle optimization strategy. This resulted in a 56-86% fuel efficiency improvements for conventional vehicles. When combined with the plug-in hybrid electric vehicle power management system, about 115% energy efficiency improvements were achieved. Further improvements in the overall energy efficiency of the network were achieved with increased penetration rates of the intelligent transportation assisted enabled plug-in hybrid electric vehicles.     

Fuel economy improvements for urban driving: Hybrid vs. intelligent vehicles

The quest for more fuel-efficient vehicles is being driven by the increasing price of oil. Hybrid electric powertrains have established a presence in the marketplace primarily based on the promise of fuel savings through the use of an electric motor in place of the internal combustion engine during different stages of driving. However, these fuel savings associated with hybrid vehicle operation come at the tradeoff of a significantly increased initial vehicle cost due to the increased complexity of the powertrain. On the other hand, telematics-enabled vehicles may use a relatively cheap sensor network to develop information about the traffic environment in which they are operating, and subsequently adjust their drive cycle to improve fuel economy based on this information – thereby representing ‘intelligent’ use of existing powertrain technology to reduce fuel consumption. In this paper, hybrid and intelligent technologies using different amounts of traffic flow information are compared in terms of fuel economy over common urban drive cycles. In order to develop a fair comparison between the technologies, an optimal (for urban driving) hybrid vehicle that matches the performance characteristics of the baseline intelligent vehicle is used. The fuel economy of the optimal hybrid is found to have an average of 20% improvement relative to the baseline vehicle across three different urban drive cycles. Feedforward information about traffic flow supplied by telematics capability is then used to develop alternative driving cycles firstly under the assumption there are no constraints on the intelligent vehicle’s path, and then taking into account in the presence of ‘un-intelligent’ vehicles on the road. It is observed that with telematic capability, the fuel economy improvements equal that achievable with a hybrid configuration with as little as 7 s traffic look-ahead capability, and can be as great as 33% improvement relative to the un-intelligent baseline drivetrain. As a final investigation, the two technologies are combined and the potential for using feedforward information from a sensor network with a hybrid drivetrain is discussed.