基于ADVISOR的动力耦合系统参数匹配及仿真

混合动力汽车的动力耦合系统结构和参数匹配影响整车性能,通过对动力耦合系统的结构选择、参数匹配和控制策略的研究,以传统汽车的差速器作为动力耦合器并建立模型,并对此模型进行参数匹配,通过使用ADVISOR软件中修改控制策略模块,并将修改后的Simulink模型嵌入ADVISOR软件中进行仿真,验证选择方案对于改善汽车动力性和燃油经济性的有效性。     

红岩“杰狮”开展高原实测

近日，上汽依维柯红岩与上汽菲亚特红岩动力总成有限公司、菲亚特动力科技有限公司、博世汽车燃油系统有限公司、无锡康明斯增压技术有限公司共同组织了一支精干测试队伍，对红岩“杰狮”重卡在高原的表现展开试验。     

潍柴动力——为全球提供通用动力

<正>潍柴动力——全系列提供全球通用动力潍柴集团,创建于1946年,一直致力于为全球解决各种动力和动力相关性问题。是目前中国规模领先的汽车零部件集团,2009年实现营业收入523亿元,集团主营业务涵盖整车、动力总成、汽车零部件以及船舶动力、发电设备等五大板块。     

增程式电动公交车示范推广

增程式电动车是一种配有地面充电和车载供电功能的纯电驱动的电动汽车,它结合了混合动力车、纯电动车的优点。其动力系统由动力电池系统、动力驱动系统、整车控制系统和辅助动力系统(APU)组成。由整车控制器完成运行控制策略。电池组可由地面充电桩或车载充电器充电,发动机可采用燃油型或燃气型。整车运行模式可根据需要工作于纯电动模式、增程模式、电量保持模式。当工作于增程模式时,节油率随电池组容量增大无限接近纯电动汽车,是纯电动汽车的平稳过渡车型。由于低速扭矩大,高速运行平稳,刹车能量回收效率高,结构简单易维修,在当前混合动力车故障率较高、纯电动车续航里程短的情况下,是一种较为适用于城市公交的新能源客车。     

整车参数对混合动力汽车NEDC工况油耗的影响

混合动力整车油耗不仅仅取决于混合动力系统的优劣,与整车参数也有很大的关系,但混合动力汽车与传统汽车相比,整车参数对油耗的影响是有一定差别的,本文研究了一些主要的整车参数对混合动力汽车的油耗影响。基于功率分流式混合动力车辆的Amesim仿真模型,选取整车质量、轮胎滚动半径、滑行阻力曲线三个因素并利用正交表的方法分析其对油耗的影响,从而指导利用该模型进行功率分流式混合动力车辆的油耗分析和优化。研究表明,混合动力汽车由于制动能量回收的影响,整备质量对油耗的影响小于传统汽车;由于功率分流的能量控制策略,轮胎滚动半径对油耗的影响很小;滑行阻力对油耗的影响和传统汽车接近。     

柴油机电控燃油喷射系统的发展及研究现状

文章简要介绍了柴油机电控燃油喷射系统及高压共轨式电控燃油喷射系统的发展由来;比较了电控燃油喷射系统和传统燃油喷射系统的性能;阐述了高压共轨式电控燃油喷射系统的基本组成和基本功能,以及当前国内外高压共轨式电控燃油喷射系统的研究现状。     

波浪作用下悬浮隧道管体-锚索耦合系统水动力特性研究

水下悬浮隧道(SFT)是一种新型跨海交通通道型式。文章采用CFD方法研究悬浮隧道管体-锚索耦合系统在波浪作用下的动力响应特征,并分析浸没深度、浮重比(BWR)、系泊角度(IMA)、锚索刚度、锚索系统布置形式、锚索系统预张力分配及波浪参数等对悬浮隧道水动力特性的影响。结果表明,管体运动响应随浸没深度的增加而减小,随波高和IMA的增大而增大;BWR及锚索垂向刚度存在满足结构稳定性要求的合理取值区间;锚索系统预张力分配不是影响SFT水动力特性的关键因素;应避免无垂向锚索的布置形式及特定波浪周期下耦合系统的共振现象。     

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。     

PHEV行驶模式选择控制系统研究

插电式混合动力汽车(PHEV)可以在电池电量耗尽后通过外接电网获取能量,其电池电量更加充足、纯电动续驶里程更长。为了充分发挥PHEV这一优势,本文提出了基于驾驶员选择行驶模式的控制策略,通过驾驶员选择行驶模式的方式将驾驶员作为控制系统的一部分,体现了人-车-路闭环控制的思想,以达到在各种行驶工况下合理分配电池电量的目标,实现整车最优的能量管理及控制。本文对控制系统进行设计,对其工作原理以及控制系统的结构方案设计过程进行了系统论述,最后在仿真平台上对设计的控制系统功能进行验证,所开展的工作对于插电式混合动力汽车的控制系统的开发及研究具有一定的指导意义,实现了预期的研究目标。     

“三峡氢舟1”氢燃料供电系统设计要点

“三峡氢舟1”是国内首艘入级CCS的氢燃料电池动力船舶,其氢燃料供电系统的研发、设计和实船应用是项目建设中的难点。本文通过对“三峡氢舟1”的发电系统、配电系统、能量管理策略、涉氢设备的布置以及涉氢安全处理措施等设计情况进行分析,解决了氢燃料电池动力船舶氢燃料供电系统应用中的关键问题。     

Feebates, footprints and highway safety

This paper presents an analysis of a market-based policy aimed at encouraging manufacturers to develop more fuel efficient vehicles without affecting the car buyer’s choice of vehicle size. A vehicle’s size is measured by its “footprint”, the product of track width and wheelbase. Traditional market-based policies to promote higher fuel economy, such as higher gasoline taxes or gas guzzler taxes, also induce motorists to purchase smaller vehicles. Whether or not such policies affect overall road safety remains controversial, however. Feebates, a continuous schedule of new vehicle taxes and rebates as a function of vehicle fuel consumption, can also be made a function of vehicle size, thus removing the incentive to buy a smaller vehicle. A feebate system based on a vehicle’s footprint creates the same incentive to adopt technology to improve fuel economy as simple feebate systems while removing any incentive for manufacturers or consumers to downsize vehicles.     

Well-to-wheel costs,primary energy demand,and greenhouse gas emissions for the production and operation of conventional and alternative vehicles

This study provides a comprehensive comparison of well-to-wheel (WTW) energy demand, WTW GHG emissions, and costs for conventional ICE and alternative passenger car powertrains, including full electric, hybrid, and fuel cell powertrains. Vehicle production, operation, maintenance, and disposal are considered, along with a range of hydrogen production processes, electricity mixes, ICE fuels, and battery types. Results are determined based on a reference vehicle, powertrain efficiencies, life cycle inventory data, and cost estimations. Powertrain performance is measured against a gasoline ICE vehicle. Energy carrier and battery production are found to be the largest contributors to WTW energy demand, GHG emissions, and costs; however, electric powertrain performance is highly sensitive to battery specific energy. ICE and full hybrid vehicles using alternative fuels to gasoline, and fuel cell vehicles using natural gas hydrogen production pathways, are the only powertrains which demonstrate reductions in all three evaluation categories simultaneously (i.e., WTW energy demand, emissions, and costs). Overall, however, WTW emission reductions depend more on the energy carrier production pathway than on the powertrain; hence, alternative energy carriers to gasoline for an ICE-based fleet (including hybrids) should be emphasized from a policy perspective in the short-term. This will ease the transition towards a low-emission fleet in Switzerland.     

Electric vehicles in car sharing networks – Challenges and simulation model analysis

In this paper, we examine the operation of electric vehicles in urban car sharing networks. After surveying strategic and operational differences and comparing them to gasoline-fueled cars, a simulation study was carried out. The proposed discrete event simulation tool covered important operational characteristics of electric vehicles, including realistic charging routines. Different vehicle types were compared under various conditions and on multiple markets to determine their performance. The data obtained indicated the competitiveness of electric vehicles in car sharing networks. Key success factors included advantageous relations between the market environment (e.g. electricity and fuel prices) and important characteristics of electric cars (e.g. price and range).     

A new offline optimization approach for designing a fuel cell hybrid bus

In this study a hydrogen powered fuel cell hybrid bus is optimized in terms of the powertrain components and in terms of the energy management strategy. Firstly the vehicle is optimized aiming to minimize the cost of its powertrain components, in an official driving cycle. The optimization variables in powertrain component design are different models and sizes of fuel cells, of electric motors and controllers, and batteries. After the component design, an energy management strategy (EMS) optimization is performed in the official driving cycle and in two real measured driving cycles, aiming to minimize the fuel consumption. The EMS optimization is based on the control of the battery’s state-of-charge. The real driving cycles are representative of bus driving in urban routes within Lisbon and Oporto Portuguese cities. A real-coded genetic algorithm is developed to perform the optimization, and linked with the vehicle simulation software ADVISOR. The trade-off between cost increase and fuel consumption reduction is discussed in the lifetime of the designed bus and compared to a conventional diesel bus. Although the cost of the optimized hybrid powertrain (62,230 €) achieves 9 times the cost of a conventional diesel bus, the improved efficiency of such powertrain achieved 36% and 34% of lower energy consumption for the real driving cycles, OportoDC and LisbonDC, which can originate savings of around 0.43 €/km and 0.37 €/km respectively. The optimization methodology presented in this work, aside being an offline method, demonstrated great improvements in performance and energy consumption in real driving cycles, and can be a great advantage in the design of a hybrid vehicle.     

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.     

Hardware-in-the-loop testbed for evaluating connected vehicle applications

Connected vehicle environment provides the groundwork of future road transportation. Researches in this area are gaining a lot of attention to improve not only traffic mobility and safety, but also vehicles’ fuel consumption and emissions. Energy optimization methods that combine traffic information are proposed, but actual testing in the field proves to be rather challenging largely due to safety and technical issues. In light of this, a Hardware-in-the-Loop-System (HiLS) testbed to evaluate the performance of connected vehicle applications is proposed. A laboratory powertrain research platform, which consists of a real engine, an engine-loading device (hydrostatic dynamometer) and a virtual powertrain model to represent a vehicle, is connected remotely to a microscopic traffic simulator (VISSIM). Vehicle dynamics and road conditions of a target vehicle in the VISSIM simulation are transmitted to the powertrain research platform through the internet, where the power demand can then be calculated. The engine then operates through an engine optimization procedure to minimize fuel consumption, while the dynamometer tracks the desired engine load based on the target vehicle information. Test results show fast data transfer at every 200 ms and good tracking of the optimized engine operating points and the desired vehicle speed. Actual fuel and emissions measurements, which otherwise could not be calculated precisely by fuel and emission maps in simulations, are achieved by the testbed. In addition, VISSIM simulation can be implemented remotely while connected to the powertrain research platform through the internet, allowing easy access to the laboratory setup.     

Life cycle emissions and cost model for urban light duty vehicles

The growth of vehicle sales and use internationally requires the consumption of significant quantities of energy and materials, and contributes to the deterioration of air-quality and climate conditions. Advanced propulsion systems and electric drive vehicles have substantially different characteristics and impacts. They require life cycle assessments and detailed comparisons with gasoline powered vehicles which, in turn, should lead to critical updates of traditional models and assumptions. For a comprehensive comparison of advanced and traditional light duty vehicles, a model is developed that integrates external costs, including emissions and time losses, with societal and consumer life cycle costs. Life cycle emissions and time losses are converted into costs for seven urban light duty vehicles. The results, which are based on vehicle technology characteristics and transportation impacts on environment, facilitate vehicle comparisons and support policy making in transportation. Substantially, more sustainable urban transportation can be achieved in the short-term by promoting policies that increase vehicle occupancy; in the intermediate-term by increasing the share of hybrid vehicles in the car market and in the long-term by the widespread use of electric vehicles. A sensitivity-analysis of life cost results revealed that vehicle costs change significantly for different geographical areas depending on vehicle taxation, pricing of gasoline, electric power and pollution. Current practices in carbon and air quality pricing favor oil and coal based technologies. However, increasing the cost of electricity from coal and other fossil fuels would increase the variable cost for electric vehicles, and tend to favor the variable cost of hybrid vehicles.     

Projecting adoption of truck powertrain technologies and CO2 emissions in line-haul networks

In this paper we present a mixed-integer linear program to represent the decision-making process for heterogeneous fleets selecting vehicles and allocating them on freight delivery routes to minimize total cost of ownership. This formulation is implemented to project alternative powertrain technology adoption and utilization trends for a set of line-haul fleets operating on a regional network. Alternative powertrain technologies include compressed (CNG) and liquefied natural gas (LNG) engines, hybrid electric diesel, battery electric (BE), and hydrogen fuel cell (HFC). Future policies, economic factors, and availability of fueling and charging infrastructure are input assumptions to the proposed modeling framework. Powertrain technology adoption, vehicle utilization, and resulting CO₂ emissions predictions for a hypothetical, representative regional highway network are illustrated. A design of experiments (DOE) is used to quantify sensitivity of adoption outcomes to variation in vehicle performance parameters, fuel costs, economic incentives, and fueling and charging infrastructure considerations. Three mixed-adoption scenarios, including BE, HFC, and CNG vehicle market penetration, are identified by the DOE study that demonstrate the potential to reduce cumulative CO₂ emissions by more than 25% throughout the period of study.     

A choice experiment on alternative fuel vehicle preferences of private car owners in the Netherlands

This paper presents results of an online stated choice experiment on preferences of Dutch private car owners for alternative fuel vehicles (AFVs) and their characteristics. Results show that negative preferences for alternative fuel vehicles are large, especially for the electric and fuel cell car, mostly as a result of their limited driving range and considerable refueling times. Preference for AFVs increases considerably with improvements on driving range, refueling time and fuel availability. Negative AFV preferences remain, however, also with substantial improvements in AFV characteristics; the remaining willingness to accept is on average € 10,000–€ 20,000 per AFV. Results from a mixed logit model show that consumer preferences for AFVs and AFV characteristics are heterogeneous to a large extent, in particular for the electric car, additional detour time and fuel time for the electric and fuel cell car. An interaction model reveals that annual mileage is by far the most important factor that determines heterogeneity in preferences for the electric and fuel cell car. When annual mileage increases, the preference for electric and fuel cell cars decreases substantially, whilst the willingness to pay for driving range increases substantially. Other variables such as using the car for holidays abroad and the daily commute also appear to be relevant for car choice.     

Consumer preferences for alternative fuel vehicles: A discrete choice analysis

This paper analyzes the potential demand for privately used alternative fuel vehicles using German stated preference discrete choice data. By applying a mixed logit model, we find that the most sensitive group for the adoption of alternative fuel vehicles embraces younger, well-educated, and environmentally aware car buyers, who have the possibility to plug-in their car at home, and undertake numerous urban trips. Moreover, many households are willing to pay considerable amounts for greater fuel economy and emission reduction, improved driving range and charging infrastructure, as well as for enjoying vehicle tax exemptions and free parking or bus lane access. The scenario results suggest that conventional vehicles will maintain their dominance in the market. Finally, an increase in the battery electric vehicles’ range to a level comparable with all other vehicles has the same impact as a multiple measures policy intervention package.