Modern gearboxes are meticulously engineered with three primary objectives: enhancing load-carrying capacity, minimizing noise, vibration, and harshness (NVH), and optimizing efficiency. Efficiency, in particular, holds paramount significance due to gearboxes’ substantial influence on energy consumption. One effective strategy for boosting efficiency involves curbing churning losses, stemming from the movement of oil within the gearbox housing. Computational fluid dynamics (CFD) techniques have emerged as invaluable tools for visualizing oil flow dynamics within gearboxes and pinpointing avenues for mitigating churning losses. In the context of electric vehicles (EVs), specifically battery electric vehicles (BEVs), extending their driving range is a top priority. Achieving this hinges on the design of an efficient gearbox. This study employs an oil/air multi-phase volume of fluid (VOF) method in a commercial CFD solver known as Simerics-MP+ to model the oil flow and churning losses within a single-stage gearbox. The model’s predictions are validated against previously published highspeed camera footage and measurements derived from the FZG noload power loss test rig’s single-stage gearbox. The simulation results underscore the potential of CFD simulations in providing an exceptionally detailed portrayal of oil flow behavior, while also aligning closely with experimental measurements concerning churning losses. Additionally, two different modeling approaches for gearbox simulations are compared and the advantages are discussed. This study provides engineers with a new tool that can be used to improve the efficiency and reliability of gearboxes in BEVs.

Effective design of the lubrication path greatly influences the durability of any transmission system. However, it is experimentally impossible to estimate the internal distribution of the automotive transmission fluid (ATF) to different parts of the transmission system due to its structural complexities. Hybrid vehicle transmission systems usually consist of different types of bearings (ball bearings, thrust bearings, roller bearings, etc.) in conjunction with gear systems. It is a perennial challenge to computationally simulate such complicated rotating systems. Hence, one-dimensional models have been the state of the art for designing these intricate transmission systems. Though quantifiable, the 1D models still rely heavily on some testing data. Furthermore, HEVs (hybrid electric vehicles) desire a more efficient lubrication system compared to their counterparts (Internal combustion engine vehicles) to extend the range of operation on a single charge. Thus, this paper includes a detailed, transient, three-dimensional CFD analysis of the lubricating oil flow path in an HEV transmission system using the commercial CFD software Simerics-MP+. The modeled transmission system includes scores of bearings, rotating components, and planetary gear systems. Using this modeling framework, we can predict the lubrication state of the various components of the transmission system. Furthermore, this paper reveals the effect of the centrifugal force on the oil distribution and the wetting fraction of different components. Additionally, two different designs of lubricating flow paths inside the roller bearings are explored to study the effect on the wetting of the rollers. The current simulation framework adopts the volume of fluid (VOF) technique to accurately model the two-phase interface development in the rotating systems.

The study focuses on understanding the air and oil flow characteristics within a ball bearing during high-speed rotation, with a particular emphasis on optimizing frictional heat dissipation and oil lubrication methods. Computational fluid dynamics (CFD) techniques are employed to analyze the intricate three-dimensional airflow and oil flow patterns induced by the motion of rotating and orbiting balls within the bearing. A significant challenge in conducting three-dimensional CFD studies lies in effectively resolving the extremely thin gaps existing between the balls, races, and cages within the bearing assembly. In this research, we adopt the ball-bearing structured meshing strategy offered by Simerics-MP+ to meticulously address these micron-level clearances, while also accommodating the rolling and rotation of individual balls. Furthermore, we investigate the impact of different designs of the lubrication ports to channel oil to other locations compared to the ball bearings. This analysis is pivotal, as it allows us to assess the effects of these bearing weirs on spin loss, which, in turn, has a substantial influence on the overall efficiency of an electric motor. This holistic understanding of spin loss is crucial in the context of battery electric vehicles (BEVs), as it directly affects the vehicle’s range and energy efficiency. In conclusion, this research not only sheds light on the intricate airflow dynamics within ball bearings but also underscores the practical significance of mitigating spin loss in electric motors, thus contributing to the advancement of BEV technology and its environmental sustainability.

The internal details of fuel injectors have a profound impact on the emissions from gasoline direct injection engines. However, the impact of injector design features is not currently understood, due to the difficulty in observing and modeling internal injector flows. Gasoline direct injection flows involve moving geometry, flash boiling, and high levels of turbulent two-phase mixing. In order to better simulate these injectors, five different modeling approaches have been employed to study the engine combustion network Spray G injector. These simulation results have been compared to experimental measurements obtained, among other techniques, with X-ray diagnostics, allowing the predictions to be evaluated and critiqued. The ability of the models to predict mass flow rate through the injector is confirmed, but other features of the predictions vary in their accuracy. The prediction of plume width and fuel mass distribution varies widely, with volume-of-fluid tending to overly concentrate the fuel. All the simulations, however, seem to struggle with predicting fuel dispersion and by inference, jet velocity. This shortcoming of the predictions suggests a need to improve Eulerian modeling of dense fuel jets.

The early and late portions of transient fuel injection have proven to be a rich area of research, especially since the end of injection can cause a disproportionate amount of emissions in direct injection internal combustion engines. The presented work simulates a gasoline direct injector operating under cavitating conditions by employing a more gradual and easily implemented model of closure that avoids spurious water-hammer effects. The results show cavitation at low valve lift for both flash-boiling and nonflash-boiling conditions. Further, this study reveals post-closure dynamics that result in dribble, which is expected to contribute to unburnt hydrocarbon emissions. Flashing versus nonflashing conditions are shown to cause different sac and nozzle behaviors after needle closure. In particular, a slowly boiling sac is observed for the flash-boiling condition which causes spurious postinjection behaviors. However, post-needle closure, traces of ambient gas and liquid fuel, which are the main source of dribble, are observed for the nonflashing condition. The current work indicates more tip wetting for the flash-boiling condition compared to the nonflashing condition during both pre-and post-needle closure phases.

Long-term petroleum prices and increasingly-stringent emissions regulations are driving manufacturers and users alike to consider alternatives to diesel-fueled engines. Mixing controlled combustion of alcohol fuels, such as ethanol, has been identified as a promising technology based the low propensity for particulate and NOx production, but the higher heats of vaporization and auto-ignition temperatures of these fuels make their direct use in diesel engine architectures a challenge. However, because alcohol fuels do not form appreciable levels of soot even in mixing-controlled (MCCI) mode, and because stoichiometric air/fuel ratios (AFR) can be used to simplify NOx aftertreatment, engine design optimization efforts can be targeted to maximize thermal efficiency. Therefore, to realize the potential of alcohol-fueled combustion, engineering insight is required to understand how design parameters, such as increased engine insulation, piston bowl geometry, or spray targeting, should be optimally utilized. In this work, a computational fluid dynamics (CFD) modeling framework is developed and validated in order to identify pathways to improve the performance of an ethanol-fueled engine operating in an MCCI mode at a stoichiometric AFR. To evaluate the use of TBCs as an engine insulation method, a simplified 1-D conjugate heat transfer (CHT) modeling framework is employed. The CFD model is first validated against baseline engine data over selected inlet air heating temperatures for two piston bowl-injector configurations that define the extrema of the design space. The addition of the 1-D CHT model only increases the computational expense by 15% relative to traditional approaches, yet offers more accurate heat transfer predictions over constant temperature boundary conditions. The model is then used to explore the efficacy of injector orientations and piston bowl geometries in improving the indicated thermal efficiency of alcohol fueled compression ignition engines. Using a design of experiments approach, several candidate designs were identified that improved fuel-air mixing, shortened the combustion duration, and increased thermal efficiency. The most promising design was then fabricated and tested in a Caterpillar 1Y3700 Single Cylinder Oil Test Engine (SCOTE). The engine testing confirmed the findings from the CFD simulations, and found that the co-optimized injector and piston bowl design yielded over 2-percentage point increase in thermal efficiency at the same equivalence ratio (0.96) and over 6-percentage point increase at the same engine load (10.1 bar indicated mean effective pressure), while satisfying design constraints for peak pressure and maximum pressure rise rate.

The internal details of fuel injectors have a profound impact on the emissions from gasoline direct injection (GDI) engines. However, the impact of injector design features is not currently understood, due to the difficulty in observing and modeling internal injector flows. GDI flows involve moving geometry, flash-boiling, and high levels of turbulent two-phase mixing. In order to better simulate these injectors, five different modeling approaches have been employed to study the Engine Combustion Network (ECN) Spray G injector. These simulation results have been compared to experimental measurements obtained, among other techniques, with X-ray diagnostics, allowing the predictions to be evaluated and critiqued. The ability of the models to predict mass flow rate through the injector is confirmed, but other features of the predictions vary in their accuracy. The prediction of plume width and fuel mass distribution vary widely, with Volume-of-Fluid (VOF) tending to overly concentrate the fuel. All the simulations, however, seem to struggle with predicting fuel dispersion and by inference, jet velocity. This shortcoming of the predictions suggest a need to improve Eulerian modeling of dense fuel jets.

The early and late portions of transient fuel injection have proven to be a rich area of research, especially since the end of injection can create a disproportionate amount of emissions in direct injection internal combustion engines. A perennial challenge in simulating the internal flow of fuel injectors is the valve opening and closure event. In a typical adaptive-mesh CFD simulation, the small gap between the needle valve and the seat must be resolved with very small cells, resulting in extremely expensive computations. Capturing complete closure usually involves a topological change in the computational domain. In this work we present a more gradual and easily-implemented model of closure that avoids spurious water-hammer effects. The algorithm is demonstrated with a simulation of a gasoline direct injector operating under cavitating conditions. The results include the the first simulation of a multiple injection event known to the authors. The results show cavitation at low valve lift. Further, they reveal post-closure dynamics that result in dribble, which is expected to contribute to unburned hydrocarbon emissions.

Computational simulations of two-phase laminar flow in effervescent atomizers have been carried out. The flow is considered in the annular flow regime. A non-uniform, structured computational grid of 48000 cells is used for an axisymmetric effervescent atomizer consisting of a mixing chamber, convergence section and an orifice section. Volume of Fluid (VOF) model is used to investigate the water-air two-phase flow. The flow is considered compressible and the formulation is axisymmetric. The Gas-to-Liquid Ratio or GLR is varied from 0.005 to 0.07, with a liquid flow rate variation from 0.14 l/min to 0.27 l/min. For each case, the liquid sheet thickness and velocity at the orifice exit are obtained from the numerical solutions. At a constant liquid flow rate, the liquid sheet thickness varies inversely with gas-to-liquid ratio (GLR). Moreover the decrease in the sheet thickness is sharper at lower values of GLR and the variation becomes more gradual as GLR increases. Furthermore, an increase in liquid flow rate results in an increase in the sheet thickness. With an increase in the orifice diameter, non-dimensionalized sheet thickness increases. Sheet thickness varies marginally with changes in orifice length, angle of the convergence section, and liquid surface tension. Based upon the computational study, an empirical correlation to predict the sheet thickness as a function of the exit Reynolds number and GLR is proposed. ∗Corresponding Author: Milind.Jog@uc.edu