底盘测功机阻力设定对重型商用车油耗的影响分析

文章研究了重型商用车辆分别采用推荐道路阻力与实测道路阻力对在底盘测功机上进行整车油耗试验的结果差异。结果表明,采用推荐道路阻力不能真实反应出车辆的油耗水平;底盘测功机的阻力设定直接影响车辆的油耗结果,阻力设定值越大,油耗越大,反之越小。     

基于PID和模糊逻辑的车辆操纵稳定性控制分析

在线性二自由度车辆模型的基础上,以PID控制、模糊逻辑控制理论为基础,运用不同的控制策略,基于直接横摆力矩控制方法,利用Simulink设计了车辆操纵稳定性控制器,进行了控制效果的仿真分析和比较。仿真结果表明:单独控制质心侧偏角、以及对质心侧偏角和横摆角速度进行联合控制,控制效果要优于单独的横摆角速度控制;模糊逻辑控制具有较强的鲁棒性而PID控制具有较强的应用性。     

基于PID和模糊逻辑的车辆操纵稳定性控制分析

在线性二自由度车辆模型的基础上,以PID控制、模糊逻辑控制理论为基础,运用不同的控制策略,基于直接横摆力矩控制方法,利用Simulink设计了车辆操纵稳定性控制器,进行了控制效果的仿真分析和比较。仿真结果表明:单独控制质心侧偏角、以及对质心侧偏角和横摆角速度进行联合控制,控制效果要优于单独的横摆角速度控制;模糊逻辑控制具有较强的鲁棒性而PID控制具有较强的应用性。     

道路清障车发展现状与未来趋势预测

清障车是道路车辆事故(故障)施救,城市违章车辆处理以及自然灾害抢险救灾必不可少的救援装备。本文阐述了我国道路清障车行业从技术引进到自主创新的发展历程。通过比较国内外道路清障车技术水平差异,深入分析了当前我国清障车行业发展所遇到的"瓶颈"问题。根据清障车行业的发展轨迹,对我国道路清障车市场的未来发展前景与趋势做出了预测。     

节油技术整车对比检测方法的应用

对汽车节油技术的检测主要分为发动机性能台架对比试验和整车性能道路对比试验两大类别,文章采用整车性能道路对比试验,使用流量计检测内燃机采用节油技术前后的燃油消耗量,来评定内燃机在运用了节油技术或产品后的节油效果,适用于车辆和柴油发电机组等内燃机的应用产品。     

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。     

皮卡式清障车总体设计及市场应用

通过对高速针对常规清障车由于超高、转弯空间受限无法进入地下车库进行施救的难题,文章提出了专用皮卡式清障车的总体功能要求,探讨了总体布置、底盘选型与改造、专用装置结构设计等关键技术,研发并制造了皮卡式清障车样机,并进行了相应功能验证。在此基础上,深入剖析了皮卡式清障车在市场应用中所遇到的问题,并提倡将"主动救援新模式"常态化。     

传统燃油车的电动化改制方案研究

文章以前置后驱的传统燃油车改制为前置前驱的纯电动汽车案例,展开整车设计分析,在维持原型车的外形、长宽高、轴距和轮距等基本参数的基础上,提出了整车布置结构变化的改制设计方案,设定了电动车整车主要性能指标。在电动化设计中取消了传统燃油动力总成及其附属的燃油、进排气等系统,依据整车性能目标要求,结合车辆空间及整车结构原理,对驱动电机动力总成、电池PACK、VCU、PDC三合一等高压系统零部件进行选型及布置设计。     

基于蛇形试验汽车操稳性主客观评价相关性研究

为实现汽车操纵稳定性主观评价客观化,以实车蛇行试验为例,研究汽车操稳性主观得分与客观测量数据之间的关系,建立相关性"最优"模型。结果表明,在小样本情况下,主观评价得分分别与平均转向盘转角无线性相关关系,与平均横摆角速度正线性相关关系,与平均车身侧倾角、平均侧向加速度负线性相关关系;平均横摆角速度对主观评价得分影响最显著,平均侧向加速次之,平均车身侧倾角最小。     

汽车节油技术的检测与评定

对汽车节油技术的检测一般采用发动机或整车对比检测的方法,仅仅凭借一些普通的计量器具是无法准确检测出车辆各项性能的实际状况,必须采用高精度的测试仪器,并严格控制试验时的环境条件,方能检测出汽车节油技术的真实效果。     

Estimating daily vehicle usage distributions and the implications for limited-range vehicles

Understanding the potential market for limited-range vehicles is important to planning research and development programs for electric and hybrid vehicles and for gaseous-fueled vehicles as well. Studies of consumer preferences and perceptions have shown vehicle range to be a very important vehicle attribute. Studies of household vehicle use, on the other hand, have suggested that the range requirements most households place on vehicles are quite modest. The latter, however, have been severely limited by the absence of longitudinal data on the usage of individual vehicles. Instead, they have relied on single-day surveys on many vehicles, an inappropriate data source. This study develops a method for estimating daily travel distributions for individual vehicles and applies it to a recent longitudinal survey of miles and days between refuelings for over 2000 vehicles. Every vehicle in the sample has at least 30 consecutive refueling intervals. A variety of measures of “range requirement” are defined and calculated. The results confirm the existence of a substantial potential market (20–50% of all household vehicles) for vehicles with ranges on the order of 100 miles. Future research using these data and this method could describe the nature of vehicles with limited-range needs and the households which own them.     

基于底盘测功机的汽车燃油消耗量测试研究

随着石油储量的减少和油价的持续走高,油耗已经成为大家关注的焦点.文章通过基于底盘测功机的汽车燃油消耗量的测试研究,获得了不同车况和车速下的油耗曲线,试验结果比较科学地反映了车辆的真实油耗,可供各种汽车油耗测试参考.     

重型清障车吊臂和托臂的优化设计及应力分析

清障车是一种具有道路抢险作业装备,能够起吊和托起事故、违章或损坏车辆,并能快速离开事故现场的专用车辆。文章采用UG软件对吊臂模型处理,通过其自带软件NX NASTRAN对托臂总成进行有限元分析,根据实际作业工况对托臂总成进行约束与载荷施加,使托臂的强度分析更具有可信度。其结果为吊臂和托臂总成的设计及优化提供了参考依据。     

客车车架结构设计与分析

文章根据客车车架设计理论和某长途客车底盘参数,设计出适用于客车底盘总成布置的三段式车架,并应用有限元分析软件Ansys WorkBench进行车架静力学分析,同时根据分析结果对车架薄弱部位进行了改进设计。     

Vehicular emissions prediction with CART-BMARS hybrid models

Vehicular emission models play a key role in the development of reliable air quality modeling systems. To minimize uncertainties associated with these models, it is essential to match the high-resolution requirements of emission models with up-to-date information. However, these models are usually based on average trip speed, not on environmental parameters like ambient temperature, and vehicle’s motion characteristics, such as speed, acceleration, load and power. This contributes to the degradation of its predictive performance. In this paper, we propose to use the non-parametric Classification and Regression Trees (CART), the Boosting Multivariate Adaptive Regression Splines (BMARS) algorithm and a combination of them in hybrid models to improve the accuracy of vehicular emission prediction using on-board measurements and the chassis dynamometer testing. The experimental comparison between the proposed CART-BMARS hybrid model with the BMARS and artificial neural networks (ANNs) algorithms demonstrates its effectiveness and efficiency in estimating vehicular emissions.     

Using a chassis dynamometer to determine the influencing factors for the emissions of Euro VI vehicles

In order to explore the influence of different factors on the emissions of heavy diesel vehicles, a chassis dynamometer was used to test and analyze a Euro VI standard heavy-duty diesel vehicle under different load, fuel, driving conditions, and resistance conditions. The full load condition was found to increase NOx emissions by about 0.107 g/km (30%) and the particulate matter (PM) by 0.003 g/km (18%) compared to the empty load condition. Compared with the China V diesel, the NOx emissions of the Beijing VI diesel were reduced by 0.065 g/km (18%), and PM decreased by 0.004 g/km (25%). The HC, CO, PM, and NOx emissions measured during the Chinese World Harmonized Transient Cycle (C-WHTC) were 0.002 g/km (27%), 0.0005 g/km (14%), 0.0024 g/km (15%), and 0.092 g/km (25%) higher, respectively, than those measured during the European Transient Cycle (ETC). The HC, CO, PM, and NOx emissions measured by using the test resistance were 0.002 g/km (28%), 0.001 g/km (25%), 0.003 g/km (18.7%), and 0.09 g/km (25.7%) higher, respectively, than those calculated with the recommended formula.     

Well-to-wheel assessment of natural gas vehicles and their fuel supply infrastructures – Perspectives on gas in transport in Denmark

In this paper, potential natural gas and renewable natural gas supply pathways and natural gas vehicles (NGVs) have been selected and evaluated with regards to well-to-wheel energy expended, greenhouse gas (GHG) emissions, and regulated (air pollutant) emissions. The vehicles included in the evaluation are passenger cars, light-duty vehicles (LDVs), and heavy-duty vehicles (HDVs) for road-transport applications, and a short-range passenger vessel for maritime transport applications. The results show that, compared to conventional fuels, in both transport applications and for all vehicle classes, the use of compressed and liquefied natural gas has a 15–27% GHG emissions reduction effect per km travel. The effect becomes large, 81–211%, when compressed and liquefied renewable natural gas are used instead. The results are sensitive to the type and source of feedstock used, the type of vehicle engine, assumed methane leakage and methane slip, and the allocated energy and environmental digestate credits, in each pathway. In maritime applications, the use of liquefied natural gas and renewable natural gas instead of low sulfur marine fuels results in a 60–100% SOx and 90–96% PM emissions reduction. A 1% methane slip from a dedicated LNG passenger vessel results, on average, in 8.5% increase in net GHG emissions.     

Time-dependent drivers’ merging behavior model in work zone merging areas

This study investigates the drivers’ merging behavior in work zone merging areas during the entire merging implementation period from the time of starting a merging maneuver to that of completing the maneuver. With the actual work zone merging traffic data, we propose a time-dependent logistic regression model considering the possible time-varying effects of influencing factors, and a standard logistic regression model for the purpose of model comparison. Model comparison results show that the time-dependent model performs better than the standard model because the former can provide higher prediction accuracy. The time-dependent model results show that seven factors exhibit time-varying effects on the drivers’ merging behavior, including merging vehicle speed, through lane lead vehicle speed and through lane lag vehicle speed, longitudinal gap between the merging and lead vehicles, longitudinal gap between the merging and through lane lead vehicles, types of through lane lead and through lane lag vehicles. Interestingly, both the through lane lead vehicle speed and the through lane lag vehicle speed are found to exhibit heterogeneous effects at different times of the merging implementation period. One important finding from this study is that the merging vehicle has a decreasing willingness to take the choice of “complete a merging maneuver” as the elapsed time increases if the through lane lead vehicle is a heavy vehicle.