Sample size requirements for stated choice experiments

Stated choice (SC) experiments represent the dominant data paradigm in the study of behavioral responses of individuals, households as well as other organizations, yet in the past little has been known about the sample size requirements for models estimated from such data. Traditional orthogonal designs and existing sampling theories does not adequately address the issue and hence researchers have had to resort to simple rules of thumb or ignore the issue and collect samples of arbitrary size, hoping that the sample is sufficiently large enough to produce reliable parameter estimates, or are forced to make assumptions about the data that are unlikely to hold in practice. In this paper, we demonstrate how a recently proposed sample size computation can be used to generate so-called S-efficient designs using prior parameter values to estimate panel mixed multinomial logit models. Sample size requirements for such designs in SC studies are investigated. In a numerical case study is shown that a D-efficient and even more an S-efficient design require a (much) smaller sample size than a random orthogonal design in order to estimate all parameters at the level of statistical significance. Furthermore, it is shown that wide level range has a significant positive influence on the efficiency of the design and therefore on the reliability of the parameter estimates.     

Review on characterization of nano-particle emissions and PM morphology from internal combustion engines: Part 1

This paper is review of the characterization of exhaust particles from state-of-the-art internal combustion engines. We primarily focus on identifying the physical and chemical properties of nano-particles, i.e., the concentration, size distribution, and particulate matter (PM) morphology. Stringent emissions regulations of the Euro 6 and the LEV III require a substantial reduction in the PM emissions from vehicles, and improvements in human health effects. Advances in powertrains with sophisticated engine control strategies and engine after-treatment technologies have significantly improved PM emission levels, motivating the development of new particle measurement instruments and chemical analysis procedures. In this paper, recent research trends are reviewed for physical and chemical PM characterization methods for gasoline and diesel fueled engines under various vehicle certification cycles and real-world driving conditions. The effects of engine technologies, fuels, and engine lubricant oils on exhaust PM morphology and compositions are also discussed.     

Node-based scheduling method for easy migration from CAN to FlexRay in in-vehicle networking systems

As vehicles become more intelligent, in-vehicle networking (IVN) systems such as controller area network (CAN) are essential for the convenience and safety of drivers. To expand the applicability of IVN systems, attention is currently being focused on chassis networking systems that require increased network capacity and real-time capabilities. FlexRay was developed to replace CAN protocol in chassis networking systems, to remedy the shortage of transmission capacity and unsatisfactory real-time transmission delay of conventional CAN. However, FlexRay network systems require a complex scheduling method, which is a barrier to their implementation as chassis networking systems. In particular, if we want to migrate from a CAN network to a FlexRay network using the well-defined CAN message database, which has been specifically constructed for chassis networking systems by automotive vendors, a new type of scheduling method is necessary to reduce scheduling efforts during the software development process. This paper presents a node-based scheduling method for easy migration from a CAN network to a FlexRay network system. To demonstrate the feasibility of the technique, its performance is evaluated in terms of various software complexity indices.     

Comparison study on characteristics of nano-sized particle number distribution by using condensation particle counter calibrated with spray and soot type particle generation methods

In the year 2011, the Particle Measurement Program (PMP) in Europe started the regulation of the diesel vehicle’s nano-sized particle number density (PN) due to its high degree of harm to the human body. Concretely, the standard level of PN emission was introduced in the Euro 5+ and 6 emissions regulation with a limit (<6.0 × 10¹¹#/km) for diesel light-duty vehicle. Therefore, the determination of suitable and sophisticated instruments for reliable particle sampling and analysis was essential in taking exact experimental data. Now, among the PN emission measuring devices suggested by the PMP, condensation particle counter (CPC) is a key equipment for measuring the particle number density in real time and it has been used extensively. However, CPC can cause different results depending on operating conditions of the saturator and condensation that induce different rates of particle growth. This study was conducted to analyze the effect of CPC calibrated by a two-particle generator with spray and soot type methods applied on the nano-sized particle distribution’s parameters such as number concentration and linearity. Also, in order to ensure the reliability for particle sensor system named as PPS, which had emerged as a useful diagnostic to making spatially and temporally resolved quantitative measurements of diesel PN concentration, it was compared with calibrated CPC system. As a result, nano-sized particle measuring system with CPC calibrated by spray type particle generator had a much higher counting efficiency, indicating a larger nano size available than soot type particle generator. And, comparative experimental results on the correlation between the particle number of CPC to a reflectance PPS system showed that above 5,000 #/cm ³ in number concentrations measured by CPC as well as PPS were found to be similar with good linear relationship.     

Urea-SCR system optimization with various combinations of mixer types and decomposition pipe lengths

The demand for NO_x after-treatment system has increased dramatically due to the stricter NO_x emission regulations for diesel vehicles. The urea-SCR system is one of the NO_x after-treatment methods found to be quite effective to meet the regulation requirement enforced by various authorities including the Euro-6. In order to develop an effective urea-SCR system, it is critical to establish an even distribution of reductant over the catalyst surface since this favorable distribution can increase reduction reaction and in turn, improve NO_x conversion efficiencies. In the current study, a number of design variations of the urea-SCR system which included two mixer types and three decomposition pipe lengths, were evaluated systematically using CFD analysis and experimental measurements. The purpose of the CFD analysis was to estimate the distribution of reductant within the urea-SCR system with a specific configuration and the purpose of the engine emission test was to measure the amount of NO_x reduction, respectively. The results from the systematic analysis revealed the relation between the reductant distribution over the SCR and the performance of the NO_x reduction.     

Evaluation and visualization of stratified ultra-lean combustion characteristics in a spray-guided type gasoline direct-injection engine

To comply with reinforced emission regulations for harmful exhaust gases, including carbon dioxide (CO₂) emitted as a greenhouse gas, improved technologies for reducing CO₂ and fuel consumption are being developed. Stable lean combustion, which has the advantage of improved fuel economy and reduced emission levels, can be achieved using a sprayguided-type direct-injection (DI) combustion system. The system comprises a centrally mounted injector and closely positioned spark plugs, which ensure the combustion reliability of a stratified mixture under ultra-lean conditions. The aim of this study is to investigate the combustion and emission characteristics of a lean-burn gasoline DI engine. At an excess air ratio of 4.0, approximately 23% improvement in fuel economy was achieved through optimal event timing, which was delayed for injection and advanced for ignition, compared to that under stoichiometric conditions, while NO_x and HC emissions increased. The combustion characteristics of a stratified mixture in a spray-guided-type DI system were similar to those in DI diesel engines, resulting in smoke generation and difficulty in three-way catalystutilization. Although a different operating strategy might decrease fuel consumption, it will not be helpful in reducing NO_x and smoke emissions; therefore, alternatives should be pursued to achieve compliance with emission regulations.     

Simulation of flow in diesel particulate filter system using metal fiber filter media

Metal fiber is introduced as a new filter media in wall-flow Diesel Particulate Filter (DPF) system. This technology has high temperature durability which is required for filter regeneration, and can maintain the mechanical strength even in the extreme exhaust-related vibrations of vehicles. However, the regeneration near the wall (outer layer) is more difficult because of the heat loss and reduced gas flow near the wall. In this study, a flow is simulated to determine the flow control method for the more uniform flow in all filter layer. By using Star CCM+ commercial software, we obtain local velocity, streamline, and pressure distributions in the filter, which are typically difficult to obtain from measurements. The major control factors are the filter porosity, size and location of the distribution plate, and the number of blades of the swirler. By placing the distribution plate in front of the filter, the flow velocity near the wall was increased. The optimum location and size of the flat plate were chosen. By attaching the blade on the plate the flow velocity near the wall was increased more. Therefore, the regeneration efficiency is increased by using the swirler-type metal fiber DPF system.     

Realization of pmp-based control for hybrid electric vehicles in a backward-looking simulation

Optimal control is generally not possible without information about the future coming up, and it is not easy to obtain an optimal solution even though the information is given a priori. In this paper, a control concept based on Pontryagin’s Minimum Principle (PMP) is introduced as an efficient solution to generate an optimal control trajectory for Hybrid Electric Vehicles (HVEs) when the performance of the vehicles is evaluated on scheduled driving cycles at a simulation level. The main idea of the control concept is to minimize Hamiltonian, which is interpreted as equivalent fuel consumption, and the Hamiltonian is characterized by a co-state, which is interpreted as a weighting factor for the electrical usage. A key aspect of the control problem is that an appropriate initial condition of the co-state is required to satisfy the boundary condition of the problem. In this study, techniques to calculate the Hamiltonian in different hybrid configurations are introduced, and a methodology to look for the initial condition of the co-state is studied, so that the controller is able to realize a desired State Of Charge (SOC) trajectory. To address the issue, we utilize a shooting method with multiple initial conditions based on the concept of the Newton-Raphson method, and all these techniques are realized in a backward looking simulator. The simulation results show that the PMP-based control is a very efficient approach to produce the optimal control trajectory, and the performance is compared to the optimal solution solved by Dynamic Programming (DP).     

Analysis of the shifting behavior of a novel clutchless geared smart transmission

Conventional geared transmissions use some kinds of clutches to control the power flow from an internal combustion engine to the driveline while shifting gears. However, the shifting performance is seriously affected by the clutch engagement and an unavoidable drop in the torque may occur when the clutch is disconnected. Moreover, wear of the clutch, the need for hydraulic equipment, and the load limit may together aggravate the limits of the clutch system. For this reason, as a novel transmission without a clutch, the clutchless geared smart transmission (henceforth CGST) is proposed by our research team. The CGST controls the power flow in a multiple-input gear-train by controlling the electric motor attached to the planetary gear system. However, no CGST has been realized in an actual vehicle thus far, and the performance has been predicted only theoretically. In this research, we analyzed the achievable performance based on a developed CGST dynamic model with a typical CGST structure. In addition, a CGST gear-shifting algorithm is proposed for use with the dynamic model. From the simulation results, the CGST does not show an abrupt drop in its torque or oscillation while shifting gears due to the absence of a discontinuous power flow. The developed dynamic model can serve as a performance reference for the CGST. Moreover, it can be used as a simulation tool for developing a gear-shifting control logic scheme.     

Enhanced traffic information dissemination to facilitate toll road utilization: a nested logit model of a stated preference survey in Texas

This paper investigates the effects of the provision of traffic information on toll road usage based on a stated preference survey conducted in central Texas. Although many researchers have studied congestion pricing and traffic information dissemination extensively, most of them focused on the effects that these instruments individually produce on transportation system performance. Few studies have been conducted to elaborate on the impacts of traffic information dissemination on toll road utilization. In this study, 716 individuals completed a survey to measure representative public opinions and preferences for toll road usage in support of various traffic information dissemination classified by different modes, contents, and timeliness categories. A nested logit model was developed and estimated to identify the significant attributes of traffic information dissemination, traveler commuting patterns, routing behavior, and demographic characteristics, and analyze their impacts on toll road utilization. The results revealed that the travelers using dynamic message sign systems as their primary mode of receiving traffic information are more likely to choose toll roads. The potential toll road users also indicated their desire to obtain traffic information via internet. Information regarding accident locations, road hazard warnings, and congested roads is frequently sought by travelers. Furthermore, high-quality congested road information dissemination can significantly enhance travelers’ preferences of toll road usage. Specifically the study found that travelers anticipated an average travel time saving of about 11.3 min from better information; this is about 30 % of travelers’ average one-way commuting time. The mean value of the time savings was found to be about $11.82 per hour, close to ½ of the average Austin wage rate. The model specifications and result analyses provide in-depth insights in interpreting travelers’ behavioral tendencies of toll road utilization in support of traffic information. The results are also helpful to shape and develop future transportation toll system and transportation policy.