Experimental study on macroscopic spray characteristics after impingement in a slit-type GDI injector

In this paper, an experimental study on the wall-impinging spray of the slit-type GDI injector is presented. To examine the effects of various factors on the development of a spray impinging on the wall, experiments were conducted at various injection pressures, ambient pressures, wall distances from the injector tip, wall temperatures, and wall inclination angles. Behavior of the impinging spray was visualized using a planar laser scattering method. It is shown that the spray path penetration of the wall-impinging spray increases with increases in injection pressure, wall distance, wall temperature, or wall angle. On the other hand, the spray path penetration of the wall-impinging spray decreases with increases in ambient pressure. The predicted spray path penetration calculated by the empirical equation estimates the spray path penetration in all cases, and the empirical equation is optimized for the total injection pressure.     

Experimental investigation and comparison of nanoparticle emission characteristics in light-duty vehicles for two different fuels

In recent years, particle number emissions rather than particulate mass emissions in automotive engines have become the subject with controversial discussions. Recent results from studies of health effects imply that it is possible that particulate mass does not properly correlate with the variety of health effects attributed to engine exhaust. The concern is now focusing on nano-sized particles emitted from I. C. engines. In this study, particulate mass and particle number concentration emitted from light-duty vehicles were investigated for a better understanding of the characteristics of the engine PM from different types of fuels, such as gasoline and diesel fuel. Engine nano-particle mass and size distributions of four test vehicles were measured by a condensation particle counter system, which is recommended by the particle measurement program in Europe (PMP), at the end of a dilution tunnel along a NEDC test mode on a chassis dynamometer. We found that particle number concentrations of diesel passenger vehicles with DPF system are lower than gasoline passenger vehicles, but PM mass has some similar values. However, in diesel vehicles with DPF system, PM mass and particle number concentrations were greatly influenced by PM regeneration. Particle emissions in light-duty vehicles emitted about 90% at the ECE15 cycle in NEDC test mode, regardless of vehicle fuel type. Particle emissions at the early cold condition of engine were highly emitted in the test mode.     

Estimation of battery state-of-charge using ν-support vector regression algorithm

Accurately estimating the SOC of a battery during the electric vehicle drive cycle is a vital issue that currently remains unresolved. A support vector regression algorithm (SVR), which has good nonlinear approximation ability, a quick convergence rate and global optimal solution, is proposed to estimate the battery SOC. First, the training data and the test data required in the estimation operation are collected using the ADVISOR software, followed by normalization of the data above. Then, cross validation and grid search methodologies are used to determine the parameters in the ν-SVR model. Finally, simulation experiments have been carried out in the LIBSVM simulator. The simulation results show that, compared to the BP neural network algorithm, the ν-Support Vector Regression algorithm performs better in estimating the battery SOC.     

Experimental investigation of nozzle cavitating flow characteristics for diesel and biodiesel fuels

This study was performed to clarify criteria for cavitation inception and the relationship between flow conditions and cavitation flow patterns of diesel and biodiesel fuels. The goal was to analyze the effects of injection conditions and fuel properties on cavitating flow and disintegration phenomena of flow after fuel injection. To accomplish this goal, it was utilized a test nozzle with a cylindrical cross-sectional orifice and a flow visualization system composed of a fuel supply system and an image acquisition system. In order to analyze the rate of flow and injection pressure of the fuel, a flow rate meter and pressure gauge were installed at the entrance of the nozzle. A long distance microscope device equipped with a digital camera and a high resolution ICCD camera were used to acquire flow images of diesel and biodiesel, respectively. The effects of nozzle geometry on the cavitating flow were also investigated. Lastly, a detailed comparison of the nozzle cavitation characteristics of both fuel types was conducted under a variety of fuel injection parameters. The results of this analysis revealed that nozzle cavitation flow could be divided into four regimes: turbulent flow, beginning of cavitation, growth of cavitation, and hydraulic flip. The velocity coefficient of diesel fuel was greatly altered following an increase in flow rate, although for biodiesel, the variation of the velocity coefficient relative to the rate of flow was mostly constant. The cavitation number decreased gradually with an increase in the Reynolds number and Weber number, and the discharge coefficient was nearly equal to one, regardless of cavitation number. Lastly, it could not observe cavitation growth in the tapered nozzle despite an increase in fuel injection pressure.     

Children’s mode choice for the school trip: the role of distance and school location in walking to school

Rising levels of childhood obesity in the United States and a 75% decline in the proportion of children walking to school in the past 30 years have focused attention on school travel. This paper uses data from the US Department of Transportation’s 2001 National Household Travel Survey to analyze the factors affecting mode choice for elementary and middle school children. The analysis shows that walk travel time is the most policy-relevant factor affecting the decision to walk to school with an estimated direct elasticity of −0.75. If policymakers want to increase walking rates, these findings suggest that current policies, such as Safe Routes to School, which do not affect the spatial distribution of schools and residences will not be enough to change travel behavior. The final part of the paper uses the mode choice model to test how a land use strategy—community schools—might affect walking to school. The results show that community schools have the potential to increase walking rates but would require large changes from current land use, school, and transportation planning practices.

Relationships between characteristics of motorcycles and hydrocarbon emissions in Taiwan: A note

Taiwan’s inspection and maintenance (I/M) programs identifies high-emission motorcycles but, although these help reduce air pollution, they have been criticized for being cost-ineffective. This study examines the relationship between characteristics of motorcycles and hydrocarbon emissions in the Central Air Quality Basin of Taiwan. It is shown that engine size and type, age and manufacturer of a motorcycle significantly affect HC emissions. Larger-size engines emit smaller amounts of HCs; whereas older motorcycles emitted greater amounts. In addition, two-stroke-engine machines produced significantly higher HC emission levels than four-strokes. Variations in HC emissions testing are a result of various I/M testing locations and efficiency may be improved by modifying these.     

Potential benefits of an adaptive forward collision warning system

Forward collision warning (FCW) systems can reduce rear-end vehicle collisions. However, if the presentation of warnings is perceived as mistimed, trust in the system is diminished and drivers become less likely to respond appropriately. In this driving simulator investigation, 45 drivers experienced two FCW systems: a non-adaptive and an adaptive FCW that adjusted the timing of its alarms according to each individual driver’s reaction time. Whilst all drivers benefited in terms of improved safety from both FCW systems, non-aggressive drivers (low sensation seeking, long followers) did not display a preference to the adaptive FCW over its non-adaptive equivalent. Furthermore, there was little evidence to suggest that the non-aggressive drivers’ performance differed with either system. Benefits of the adaptive system were demonstrated for aggressive drivers (high sensation seeking, short followers). Even though both systems reduced their likelihood of a crash to a similar extent, the aggressive drivers rated each FCW more poorly than their non-aggressive contemporaries. However, this group, with their greater risk of involvement in rear-end collisions, reported a preference for the adaptive system as they found it less irritating and stress-inducing. Achieving greater acceptance and hence likely use of a real system is fundamental to good quality FCW design.     

Two-port network based bilateral control of a steer-bywire system

Steer-by-wire (SBW) system which is characterized by variable steering feel, better active safety, unmanned drive, has been widely studied to realize a distinctive driving experience. Control strategy acts as a key part of SBW system to achieve the goals. In this paper, a control strategy by bilateral control structure for steer-by-wire system is proposed. To make SBW system has the same function of conventional steering systems, the controller is designed to realize desired tracking control and realistic road feel feedback. The control of position and torque for each actuator is taken as two ports for the control network. Based on different control loop, two kinds of bilateral control is investigated respectively. The hardwarein- the-loop experiment platform of SBW is developed by the reconfiguration of electric power steering system. The test results are compared to show the performance of different control loops.     

Network reliability‐based optimal toll design

Optimal toll design from a network reliability point of view is addressed in this paper. Improving network reliability is proposed as a policy objective of road pricing. A reliability‐based optimal toll design model, where on the upper level network performance including travel time reliability is optimized, while on the lower level a dynamic user‐equilibrium is achieved, is presented. Road authorities aim to optimize network travel time reliability by setting tolls in a network design problem. Travelers are influenced by these tolls and make route and trip decisions by considering travel times and tolls. Network performance reliability is analyzed for a degradable network with elastic and fluctuated travel demand, which integrates reliability and uncertainty, dynamic network equilibrium models, and Monte Carlo methods. The proposed model is applied to a small hypothesized network for which optimal tolls are derived. The network travel time reliability is indeed improved after implementing optimal tolling system. Trips may have a somewhat higher, but more reliable, travel time.     

A joint flexible econometric model system of household residential location and vehicle fleet composition/usage choices

Modeling the interaction between the built environment and travel behavior is of much interest to transportation planning professionals due to the desire to curb vehicular travel demand through modifications to built environment attributes. However, such models need to take into account self-selection effects in residential location choice, wherein households choose to reside in neighborhoods and built environments that are conducive to their lifestyle preferences and attitudes. This phenomenon, well-recognized in the literature, calls for the specification and estimation of joint models of multi-dimensional land use and travel choice processes. However, the estimation of such model systems that explicitly account for the presence of unobserved factors that jointly impact multiple choice dimensions is extremely complex and computationally intensive. This paper presents a joint GEV-based logit regression model of residential location choice, vehicle count by type choice, and vehicle usage (vehicle miles of travel) using a copula-based framework that facilitates the estimation of joint equations systems with error dependence structures within a simple and flexible closed-form analytic framework. The model system is estimated on a sample derived from the 2000 San Francisco Bay Area Household Travel Survey. Estimation results show that there is significant dependency among the choice dimensions and that self-selection effects cannot be ignored when modeling land use-travel behavior interactions.