Experimental study on the characteristics of nano-particle emissions from a heavy-duty diesel engine using a urea-SCR system

Particulate matter in diesel engine exhaust, particularly nano-particles, can cause serious human health problems including diseases such as lung cancer. Because diesel nano-particle issues are of global concern, regulations on particulate matter emissions specify that not only the weight of particulate matter emitted but also the concentration of nanoparticles must be controlled. This study aimed to determine the effects on nano-particle and PM emissions from a diesel engine when applying a urea-SCR system for NO_x reduction. We found that PM weight increases by approximately 90% when urea is injected in ND-13 mode over the emission without urea injection. Additionally, PM weight increases as the NH₃/NO_x mole ratio is increased at 250 °C. In SEM scans of the collected PM, spherical particles were observed during urea injection, with sizes of approximately 200 nm to 1 μm. This study was designed to determine the conditions under which nano-particles and PM are formed in a urea-SCR system and to relate these conditions to particle size and shape via a quantitative analysis in ND-13 mode.     

Robust detection of preceding vehicles in crowded traffic conditions

This paper introduces an adaptive scheme for robustly detecting multiple preceding vehicles in crowded traffic conditions. The scheme focuses on issues frequently observed in the interpretation of traffic scenes recorded by cameras installed in vehicles: stable extraction of features and accurate classification in spite of the vehicle??s constant vibrations and dynamic changes in the distance between vehicles. To address these issues, we introduce the concept of integral features and a method of utilizing the scene geometry information. Each of the simple attributes, such as edges, shadows, and symmetry, is compiled in the window confined by the scene geometry to improve the expressiveness and robustness of the extracted features. The scene geometry information that is then estimated from the perspective view is extensively utilized in constituent system components, including not only feature extraction/integration but also neural network-based classification and distance-adaptive clustering. In addition, employing the Kalman filter along with a confidence measure makes the detection and tracking of potential vehicles robust. Experimental results prove that the system employing the proposed scheme detects and tracks multiple vehicles more effectively, even in crowded traffic conditions, with a lower rate of false positives.     

Predicting WCET of automotive software running on virtual machine monitors

Virtualization is attracting significant interest in the automotive industry because it enables a highly secure and reliable computing environment. More importantly, virtualization maintains the same operating environment for legacy automotive software while exploiting the benefits of widely adopted multicore platforms. To exploit the virtualization technology in an automotive system, it is important to predict the WCET of an automotive application running on a virtual machine monitor (VMM). Unfortunately, the task is challenging because of difficulties in analyzing complicated interactions between a VMM and a guest OS. There are no known attempts to predict the WCET of an application in such an environment. In this paper, we propose a hierarchical and parametric WCET prediction framework. We divide the problem into two subproblems. First, we model the WCET of an application as a function of WCETs of system calls provided by a guest OS. Second, we model WCETs of a system call as a function of WCETs of VMM services. To establish this framework, we clearly identify the places and times of VMM services invoked during the execution of an application. At the time of deployment, the WCET of an application is instantiated by composing the WCET models altogether. We have performed experiments with the proposed framework by predicting the WCETs of sample programs on various virtual and real machine platforms. These experimental results effectively demonstrate the viability of the proposed framework.     

Shape optimization of rubber isolators in automotive cooling modules for the maximization of vibration isolation and fatigue life

Rubber isolators are mounted between a cooling module and a carrier to isolate the car body from vibration due to the rotation of the cooling fan. The isolators should be durable against fatigue loads originating from fan rotation and road disturbance. Thus, the design of rubber isolators is required to maximize both vibration isolation and fatigue life. In this study, the shapes of the rubber isolators are optimally designed using a process integration and design optimization (PIDO) tool that integrates the various computer-aided engineering (CAE) tools necessary for vibration and fatigue analyses, automates the analysis procedure and optimizes the design solution. In this study, we use CAE models correlated to the experimental results. A regression-based sequential approximate optimizer incorporating Process Integration, Automation and Optimization (PIAnO), a commercial PIDO tool, is employed to handle numerically noisy responses with respect to the variation in design variables. Using the analysis and design procedure established in this study, we successfully obtained the optimal shapes of the rubber isolators in two different cooling modules; these shapes clearly have better vibration isolation capability and fatigue lives than those of the baseline designs used in industry.     

Expanding transmission capacity of can systems using dual communication channels with kalman prediction

The controller area network (CAN) protocol is widely used for in-vehicle network (IVN) systems, and many automotive companies also use the CAN in chassis network systems. However, the increasing number of electronic control units (ECUs) dictated by the need for more intelligent and fuel-efficient functions requires an IVN system with a greater transmission capacity and less network delay. Automotive companies have tried several approaches such as segmenting CAN systems and developing time-triggered protocols. This paper presents a practical method for increasing the transmission capacity and reducing the network delay in CAN systems using dual communication channels with a traffic-balancing algorithm based on Kalman prediction to forecast the traffic on each channel and allocate frames to the one that is most appropriate. An experimental testbed using commercial microcontrollers with two or more CAN protocol controllers was used to demonstrate the feasibility of the Kalman traffic-balancing algorithm. Experimental results show that the traffic-balancing CAN system with Kalman prediction reduced the transmission delay of all priority messages compared to that of a simple method, such as a channel-switching CAN, without sacrificing the performance for high-priority messages.     

Technology analysis and low-cost design of automotive radar for adaptive cruise control system

Recently, the advanced driver assistance system (ADAS), which helps mitigate car accidents, has been developed using environmental detection sensors, such as long and short range radar, lidar, wide dynamic range cameras, ultrasonic sensors and laser scanners. Among these detection sensors, radars can quickly provide drivers with reliable information about the velocity, distance and direction of a target obstacle, as well as information about the vehicle in changing weather conditions. In the adaptive cruise control system (ACCS), three radar sensors are usually needed because two short range radars are used to detect objects in the adjacent lane and one long range radar is used to detect objects in-path. In this paper, low-cost radar based on a single sensor, which can detect objects in both the adjacent lane and in-path, is proposed for use in the ACCS. Before designing the proposed radar, we analyzed the world-wide radar technology and market trends for ACCS. Based on this analysis, we designed a novel radar sensor for the ACCS using radar components, such as an antenna, transceiver module, transceiver control module and signal processing algorithm. Finally, target detection experiments were conducted. In the experimental results, the proposed single radar can successfully complete the detection required for the ACCS. In the conclusion, the perspective and issues in the future development of the ACCS radar are described.     

Investigation of the effectiveness of tandem oil fences under currents

The behavior of the flow passing a tandem oil fence, and the performance of the fence, were investigated by experimental and numerical methods. The flow characteristics between tandem fences were measured by the particle image velocimetry (PIV) method for the rigid and open free surface between the two fences in order to gather reference data for numerical investigations. A method of assessing a tandem fence by tracing the movement of an oil droplet around the fence is introduced. The effect of the current speed, the separation distance between the two fences, the relative draft of the two fences, and the water depth on the oil containment between the fences was investigated.     

An empirical investigation on the dynamic processes of activity scheduling and trip chaining

Investigation of the dynamic processes of activity scheduling and trip chaining has been an interest of transportation researchers over the past decade because of its relevance to the effectiveness of congestion management and intelligent transportation systems. To empirically examine the processes, a computerized survey instrument is developed to collect household activity scheduling data. The instrument is unique in that it records the evolution of activity schedules from intentions to final outcomes for a weekly period. This paper summarizes the investigation on the dynamic processes of activity scheduling and trip chaining based on data collected from a pilot study of the instrument. With the data, ordered logit models are applied to identify factors that are pertinent to the scheduling horizon of activities. Results of the empirical analysis show that a daily schedule often starts with certain activities occupying a portion of the schedule and other activities are then arranged around these pre-occupants. Activities of shorter duration are more likely to be opportunistically inserted in a schedule already anchored by their longer duration counterparts. Persons with children often expect more constraining activities than those with no children. The analysis also shows that female respondents tend to be more structured in terms of how the week is planned. Additionally, analysis of travel patterns reveals that many trip-chains are formed opportunistically. Travel time required to reach an activity is positively related to the scheduling horizon for the activity, with more distant stops being planned earlier than closer locations.     

H8 Control Performance of a Full-Vehicle Suspension Featuring Magnetorheological Dampers

Summary This paper presents an investigation of the feedback control performance of a full-vehicle suspension system featuring magnetorheological (MR) dampers. A cylindrical MR damper is designed and manufactured by incorporating a Bingham model of aMR fluid which is commercially available. After evaluating the field-dependent damping characteristics of the MR damper, a full-vehicle suspension system installed with 4 independent MR dampers is constructed and its governing equations of motion which include vertical, pitch and roll motions are derived. A H 8 controller which has inherent robustness against system uncertainties is formulated by treating the sprung mass of the vehicle as uncertain parameter. This is accomplished by adopting the loop shaping design procedure. For the demonstration of a practical feasibility, control performance characteristics for vibration suppression of the proposed MR suspension system are evaluated under various road conditions through the hardware-in-the-loop simulation (HILS) methodology.     

Numerical Modelling for the Hydraulic Performance Prediction of Automotive Monotube Dampers

A computer model of an automotive monotube damper is developed based on fundamental principles of mechanics. The model can identify the required damper valve and/or size for the desired performance and hence speed the design process. Also, a parametric study can be easily conducted to understand the effects of parameters on the performance. A typical monotube damper is introduced and numerical formulations are described. Satisfactory agreement is achieved between model results and test data for a wide range of parameters including stroke conditions, valve combinations, and gas charge pressure. Some of these results are presented including the correlation at low and high speed strokes, cavitation simulation, and thermal effects on the performance.