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Advances in information technologies and vehicle automation have birthed new transportation services, including shared autonomous vehicles (SAVs). Shared autonomous vehicles are on-demand self-driving taxis, with flexible routes and schedules, able to replace personal vehicles for many trips in the near future. The siting and density of pick-up and drop-off (PUDO) points for SAVs, much like bus stops, can be key in planning SAV fleet operations, since PUDOs impact SAV demand, route choices, passenger wait times, and network congestion. Unlike traditional human-driven taxis and ride-hailing vehicles like Lyft and Uber, SAVs are unlikely to engage in quasi-legal procedures, like double parking or fire hydrant pick-ups. In congested settings, like central business districts (CBD) or airport curbs, SAVs and others will not be allowed to pick up and drop off passengers wherever they like. This paper uses an agent-based simulation to model the impact of different PUDO locations and densities in the Austin, Texas CBD, where land values are highest and curb spaces are coveted. In this paper 18 scenarios were tested, varying PUDO density, fleet size and fare price. The results show that for a given fare price and fleet size, PUDO spacing (e.g., one block vs. three blocks) has significant impact on ridership, vehicle-miles travelled, vehicle occupancy, and revenue. A good fleet size to serve the region’s 80 core square miles is 4000 SAVs, charging a $1 fare per mile of travel distance, and with PUDOs spaced three blocks of distance apart from each other in the CBD.

 

Understanding the preferences for new and future transportation technologies is important to ensure an efficient and equitable future transportation system. A survey was conducted of Americans’ preferences for several such technologies. Americans are concerned about vehicle range and charging station availability for electric vehicles (EVs) and hesitant about autonomous vehicle (AV) safety. Opinions about many transportation technologies, such as vertical takeoff and landing (i.e., air taxis), shared parking, and air-drone delivery are mixed. These less familiar technologies require continued tracking of preferences. A 55% increase is estimated in the probability of an individual choosing a battery electric vehicle (BEV) pickup truck if its fuel economy increases by about 9%. This result supports a market for BEV pickup trucks currently under development by many automakers. The preference for vehicle autonomation appears to depend on the use case. Driving task automation is preferred by residents of low-density, car-dependent areas where long commutes are common. In contrast, automated parking technologies are favored by those living in denser communities. Intermittent bus lanes are favored by those living in high population density areas, but not among those in areas with high shares of zero-vehicle households. These results provide indications of where to direct future research in the field.

 

A fractal engine simulation (FES) sub-model was integrated into three-dimensional simulations for modeling turbulent combustion for a gasoline direct injection (GDI) engine. The FES model assumes that the effects of turbulence on flame propagation are to wrinkle and stretch the flame, and fractal geometry is used to predict the surface area increase and thus the turbulent burning velocity. Different formulas for the four sequential stages of combustion in SI engines are proposed to account for the changing effects of turbulence throughout the combustion process. However, most prior studies related to the FES model were quasi-dimensional simulations, with few found in multi-dimensional studies, and none under cold start conditions or stratified charges. This paper describes how the model was implemented into multidimensional simulations in CONVERGE CFD, and what the formulas are in the four sequential stages of combustion in SI engines. The capabilities of the FES model for simulating the cold start cases, under the conditions of the dramatically changing engine speed and mixture stratification in a complex engine geometry, are presented in this study. The FES model was able to not only simulate the steady-state cases with constant engine speed, but also predict the in-cylinder pressure traces in all four cylinders for the very first firing cycle with transient engine speed, and gave good agreement with the experimental measurements under these extremely transient conditions. The uncertain maximum fractal dimension was chosen as 2.37 in this research, and a simple linear correlation with engine speed was used to obtain the coefficient used in calculating the kernel formation time which controls the so-called combustion or ignition delay.

 

A multi-dimensional model of the spark ignition process for SI engines was developed as a user defined function (UDF) integrated into the commercial engine simulation software CONVERGE CFD. The model simulates spark plasma movement in an inert flow environment without combustion. The UT model results were compared with experiments for arc movement in a crossflow and also compared with calorimeter measurements of thermal energy deposition under quiescent conditions. The arc motion simulation is based on a mean-free-path physical model to predict the arc movement given the contours of the crossflow velocity through the gap and the interaction of the spatially resolved electric field with the electrons making up the arc. A further development is the inclusion of a model for the thermal energy deposition of the arc as it is stretched by the interaction of the flow and the electric field. A novel feature of this model is that the thermal energy delivered to the gap at the start of the simulation is distributed uniformly along the arc rather than at discrete points along the arc, as is the case with the default CONVERGE CFD ignition models. This feature was found to greatly reduce the tendency of the arc to distort its shape and tangle itself in a non-physical way, as is the tendency when discrete energy input is used. It was found that the tangled distortion of the arc when using discrete energy input was due to perturbations along the arc caused by differential expansion of the gas along groups of adjacent mesh cells that either had energy input or did not. The distributed energy feature also gave arc temperature distributions that were more spatially uniform and had steeper temperature gradients, consistent with experimental arc images. The results are compared with experimental high-speed video images of arc movement for a spark plug of similar geometry and taken over a range of pressures and crossflow velocities in a high-pressure constant volume vessel. There is good agreement between the simulations and experimental images for the arc stretch distance in response to a crossflow. The simulations did not display as much lateral arc dispersion as seen in the experimental results, however, that were perhaps associated with flow recirculation zones downstream of the gap, present in the experiments. The influence of the electric field was shown by turning off the electric field effect in the simulations such that the arc movement was influenced by the flow field alone. The effect of the electric field was found to be more pronounced at lower crossflow velocities of 5 m/s and at lower pressures. 

A parametric study was carried out for the first firing cycle of a 4-cylinder, 2.0-liter, turbocharged gasoline direct injection (GDI) engine. The primary goal was to see how changes in the fuel injection parameters would affect the GDI engine combustion and emissions for the first four combustion events that constitute the first firing cycle. Experimental studies were carried out with a custom-designed powertrain control system to measure the HC emissions and pressure development for the first firing cycle. The quantitative experimental results were accompanied by simulations of the detailed temporal and spatial fuel concentration profiles using Converge CFD engine simulation software. An alternative calculation method was used to calculate the average combustion equivalence ratio for each of the four cylinders. This method showed that the majority of the cold start HC emissions during the first firing cycle was unburned gasoline and its possible decomposition products, which did not contribute significantly to the combustion and heat release. For the same amount of fuel injected into a cylinder, increased fuel rail pressure resulted in better evaporation and combustion, while slightly increasing the HC emissions during the cold start process. A multiple injection strategy was studied that split the fuel delivery between the intake stroke and the compression stroke with either one or two injections in each of those strokes (two or four injections total). The quadruple injection strategy led to better first cycle combustion, with higher engine IMEP and lower HC emissions. This resulted from a richer fuel mixture in the region near the spark plug due to better fuel evaporation and a better spatial fuel distribution. While increasing fuel rail pressure with either injection strategy failed to significantly lower the HC emissions given the same amount of injected fuel mass, higher rail pressure with the quadruple injection strategy resulted in higher IMEP for the same amount of injected fuel; this may provide the possibility to reduce the total fuel injection mass which may have benefits for both fuel consumption and emissions. 

The unstretched laminar flame speed (LFS) plays a key role in engine models and predictions of flame propagation. It is also an essential parameter in the study of turbulent combustion and can be directly used in many turbulent combustion models. Therefore, it is important to predict the laminar flame speed accurately and efficiently. Two improved correlations for the unstretched laminar flame speed, namely improved power law and improved Arrhenius form correlations, are proposed for iso-octane/air mixtures in this study, using simulated results for typical operating conditions for spark-ignition engines: unburned temperatures of 300-950 K, pressures of 1-120 bar, and equivalence ratios of 0.6-1.5. The original data points used to develop the new correlations were obtained using the detailed combustion kinetics for iso-octane from Lawrence Livermore National Laboratory (LLNL). The three coefficients in the improved power law correlation were determined using a methodology different from previous approaches. The improved Arrhenius form correlation employs a function of unburned gas temperature to replace the flame temperature, making the expression briefer and making the coefficients easier to calculate. The improved Arrhenius method is able to predict the trends and the values of laminar flame speed with improved accuracy over a larger range of operating conditions. The improved power law method also works well but for a relatively narrow range of predictions. The improved Arrhenius method is recommended, considering its overall fitting error was only half of that using the improved power law correlation and it was closer to the experimental measurements. Even though ϕm, the equivalence ratio at which the laminar flame speed reaches its maximum, is not monotonic with pressure, this dependence is still included, since it produces least-rich best torque (LBT). The comparisons between the improved correlations in this study and the experimental measurements and the other correlations from various researchers are shown as well. 

Two improved correlations for the laminar flame speed, an improved power law correlation and an improved Arrhenius form correlation, are proposed for iso-octane in this study based on CONVERGE one-dimensional simulation results using the LLNL reaction mechanism. The typical working conditions for a spark-ignition engine, 300-950 K for unburned temperature, 1-120 bar for pressure, and 0.6-1.5 for equivalence ratio, were chosen to generate the results. Each of the two improved correlations has three parameters to be determined and these parameters are all shown as simple functions of equivalence ratio. The predicted unstretched laminar flame speeds using these two correlations were compared with the experimental measurements and with correlations from other researchers. In summary, both improved correlations, using simple and workable expressions, were able to predict the trends and the values of the unstretched laminar flame speed with improved accuracy. The improved Arrhenius form was more accurate and presented good predictions over a large range of operating conditions, and therefore is recommended for practical calculations and predictions.