Estimation of road profile variability from measured vehicle responses

When assessing the statistical variability of fatigue loads acting throughout the life of a vehicle, the question of the variability of road roughness naturally arises, as both quantities are strongly related. For car manufacturers, gathering information on the environment in which vehicles evolve is a long and costly but necessary process to adapt their products to durability requirements. In the present paper, a data processing algorithm is proposed in order to estimate the road profiles covered by a given vehicle, from the dynamic responses measured on this vehicle. The algorithm based on Kalman filtering theory aims at solving a so-called inverse problem, in a stochastic framework. It is validated using experimental data obtained from simulations and real measurements. The proposed method is subsequently applied to extract valuable statistical information on road roughness from an existing load characterisation campaign carried out by Renault within one of its markets.     

Connected variable speed limits control and car-following control with vehicle-infrastructure communication to resolve stop-and-go waves

The vision of intelligent vehicles traveling in road networks has prompted numerous concepts to control future traffic flow, one of which is the in-vehicle actuation of traffic control commands. The key of this concept is using intelligent vehicles as actuators for traffic control systems. Under this concept, we design and test a control system that connects a traffic controller with in-vehicle controllers via vehicle-to-infrastructure communication. The link-level traffic controller regulates traffic speeds through variable speed limits (VSL) gantries to resolve stop-and-go waves, while intelligent vehicles control accelerations through vehicle propulsion and brake systems to optimize their local situations. It is assumed that each intelligent vehicle receives VSL commands from the traffic controller and uses them as variable parameters for the local vehicle controller. Feasibility and effectiveness of the connected control paradigm are tested with simulation on a two-lane freeway stretch with intelligent vehicles randomly distributed among human-driven vehicles. Simulation shows that the connected VSL and vehicle control system improves traffic efficiency and sustainability; that is, total time spent in the network and average fuel consumption rate are reduced compared to (uncontrolled and controlled) scenarios with 100% human drivers and to uncontrolled scenarios with the same intelligent vehicle penetration rates.     

Review of flywheel based internal combustion engine hybrid vehicles

Hybrid vehicles of different configurations and utilizing different energy storage systems have existed in development for many decades and more recently in limited production. They can be grouped as parallel, series or complex hybrids. Another classification is micro, mild and full hybrids which makes the distinction on the basis of functionality. The common energy storage systems in hybrid vehicles are batteries, supercapacitors and high speed flywheels. This paper aims to review a specific type of hybrid vehicle which involves the internal combustion engine (ICE) as the prime mover and the high speed flywheel as an energy storage device. Such hybrids are now attracting considerable interest given their potential for low cost. It is hence timely to produce a review of research and development in this subject. The flywheel is coupled to the drive line with a continuous variable transmission (CVT). The CVT can be of various types such as electrical, hydraulic or mechanical but usually in this case it is a non-electrical one. Different configurations are possible and the paper provides a timeline of the development of such powertrains with various examples. These types of hybrid vehicles have existed as prototypes for many decades and the authors believe that their development has reached levels where they can be considered serious contenders for production vehicles.     

不同加载幅值下考虑层间界面条件和侧向剪力作用的柔性铺面响应

该文进行了一个三维有限元参数量化的粘弹性路面响应研究,由于不同的轮胎配置:双轮和宽基轮胎在3种温度(5、25和40℃)和两种速度(8、72 km/h);还有影响路面响应的3种因素:移动车轮荷载幅值(连续,梯形),层间界面条件(简单的摩擦和粘弹性模型)和横向力共同对路面响应的影响进行了研究.研究发现连续加载幅值,不但可以模拟路面对运动轮荷载的响应,并且是一种比目前使用的梯形荷载幅值更准确的研究模型.粘弹性模型极大地提高了双轮胎对预测路面的响应,而简单的摩擦模型更接近宽基轮胎的实地测量.侧向剪力是积极改善预测轮底的表面磨损和底部热拌沥青(沥青)基层的较小程度上的应变.研究表明:使用连续加载幅值和非均匀压力分布模拟移动轮,侧向剪切力和适当的界面摩擦可显著改善有限元模型对车辆加载路面响应的预测能力.     

不同外加剂对OGFC混合料路用性能的影响

OGFC为开级配沥青混合料,主要由粗集料嵌挤组成,在世界各地越来越广泛地用于铺筑路面.OGFC混合料可以增大路表面渗透性,减少噪音,增强表面摩擦力,尤其是在潮湿条件下.该文主要研究不同外加剂对OGFC路用性能的影响,其混合料分别由再生聚乙烯改性沥青(RPEB)、橡胶粉改性沥青(CRMB)和70#基质沥青+纤维与矿料拌和而成.并分别采用析漏试验、肯塔堡飞散试验、渗水试验、劈裂试验、静态模量试验,车辙试验和抗滑试验评估OGFC混合料的路用性能.结果表明:纤维和聚合物可以有效地减小OGFC离析的可能性,混合料每面击实50次能相应地提高磨耗性和其他相关的性能.改性沥青混合料的抗拉强度比(TSR)低于纤维+基质沥青混合料的抗拉强度比.     

Vehicle sensor data-based analysis on the driving style differences between operating indoor simulator and on-road instrumented vehicle

Abstract

Indoor simulator and on-road instrumented vehicle are the most popular ways to analyze driving behaviors by using collected Vehicle Sensor Data (VSD). However, for a same driver, the driving performance could be different in the real world and in the simulated world. Even though many studies have been conducted to discover the differences of driving behaviors in these two circumstances, little research has focused on analyzing the differences in driving style, which can provide more integrated knowledge of a driver from the natural structure, stimulus–response mechanism, of driving behaviors. Therefore, in this paper, the driving styles in both the real world and the simulated world are extracted by implementing the nonnegative matrix factorization method on the collected VSD data. Through this analysis, the driving style differences can be quantitatively described and discussed in detail. It is found that the drivers tend to be more unstable and sometimes aggressive when driving the simulator and the deviation in the perception of temporal gap in two circumstances is also discovered. The research findings are particularly valuable to calibrate the driving simulator and construct more reliable driving behavior models.     

Exhaust emissions and its control methods in compression ignition engines: A review

Extensive usage of automobiles has certain disadvantages and one of them is its negative effect on environment. Carbon dioxide (CO₂), carbon monoxide (CO), hydrocarbons (HC), oxides of nitrogen (NO_x), sulphur dioxide (SO₂) and particulate matter (PM) come out as harmful products during incomplete combustion from internal combustion (IC) engines. As these substances affect human health, regulatory bodies impose increasingly stringent restrictions on the level of emissions coming out from IC engines. This trend suggests the urgent need for the investigation of all aspects relevant to emissions. It is required to modify existing engine technologies and to develop a better after-treatment system to achieve the upcoming emission norms. Diesel engines are generally preferred over gasoline engines due to their undisputed benefit of fuel economy and higher torque output. However, diesel engines produce higher emissions, particularly NO_x and PM. Aftertreatment systems are costly and occupy more space, hence, in-cylinder solutions are preferred in reducing emissions. Exhaust gas recirculation (EGR) technology has been utilized previously to reduce NO_x. Though it is quite successful for small engines, problem persists with large bore engines and with high rate of EGR. EGR helps in reducing NO_x, but increases particulate emissions and fuel consumption. Many in-cylinder solutions such as lower compression ratios, modified injection characteristics, improved air intake system etc. are required along with EGR to accomplish the future emission norms. Modern combustion techniques such as low temperature combustion (LTC), homogeneous charge compression ignition (HCCI), premixed charge compression ignition (PCCI) etc. would be helpful for reducing the exhaust emissions and improving the engine performance. However, controlling of autoignition timing and achieving wider operating range are the major challenges with these techniques. A comprehensive review of diesel engine performance and emission characteristics is given in this paper.     

Computational and experimental investigation of the unsteady flow structures around automotive outside rear-view mirrors

The unsteady flow field around two automotive outside rear-view mirrors is investigated. This study includes comprehensive experimental and computational approaches in order to characterize the complex flow structures in the wake of the mirrors. The experiments were carried out in a wind tunnel which included the measurements of the instantaneous and averaged velocity fields as well as mean and unsteady surface pressure distributions. The simulations were performed using Large Eddy Simulation (LES). The LES approach (particularly with the dynamic subgrid viscosity model) provided good agreements with the experiments for the velocity and the surface pressure distributions. The experimental and the computational results of this study will be used as a benchmark to validate the current and the future CFD development and the subsequent aero-acoustic computations.     

A study of the environmental impacts of intelligent automated vehicle control at intersections via V2V and V2I communications

This article presents a novel intersection traffic management system for automated vehicles and quantifies its impact on fuel consumption and greenhouse gas emissions of CO₂ relative to traditional traffic signal and roundabout intersection control. The developed intelligent traffic management (ITM) techniques, which are based on a spatiotemporal reservation scheme, ensure that vehicles proceed through the intersection without colliding with other vehicles while at the same time reducing the intersection delay and environmental impacts. Specifically, the spatiotemporal reservation scheme provides each vehicle a collision-free path that is decomposed into a speed profile along with navigational instructions. The integration of the developed microscopic traffic simulator with instantaneous emission model, provides improved assessments of the environmental impact of traffic control strategies at intersections. The simulator architecture integrates several ITM algorithms, vehicle sensors, V2V/V2I communications, and emission and fuel consumption models. Each vehicle is modeled by an agent and each agent provides information depending on the specific vehicle sensors. The ITM system is supported by V2V and V2I communications, allowing the exchange of information among vehicles and infrastructure. The data include the estimated vehicle position and speed. Compared with traditional traffic management techniques, the simulation results prove that the proposed ITM system reduces CO₂ emissions significantly. The research also shows that these reductions are more significant when the traffic flow increases.