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Analysis-driven pre-calibration of a modern automotive engine is extremely valuable in significantly reducing hardware investments and accelerating engine designs compliant with stricter emission regulations. Advanced modelling tools, such as a Virtual Engine Model (VEM) using Computational Fluid Dynamics (CFD), are often used within the framework of a Design of Experiments for Powertrain Engineering (DEPE) with the goal of streamlining significant portions of the calibration process. The success of the methodology largely relies on the accuracy of analytical predictions, especially engine-out emissions. Results show excellent agreements in engine performance parameters (with R2 > 98%) and good agreements in NOx and combustion noise (with R2 > 87%), while the Carbon Monoxide (CO), Unburned Hydrocarbons (HC) and Smoke emissions predictions remain a challenge even with a large n-heptane mechanism consisting of 144 species and 900 reactions and refined mesh resolution.

A Machine Learning (ML) approach is presented to correlate in-cylinder images of early flame kernel development within a spark-ignited (SI) gasoline engine to early-, mid-, and late-stage flame propagation. The objective of this study was to train machine learning models to analyze the relevance of flame surface features on subsequent burn rates. Ultimately, an approach of this nature can be generalized to flame images from a variety of sources. The prediction of combustion phasing was formulated as a regression problem to train predictive models to supplement observations of early flame kernel growth. High-speed images were captured from an optically accessible SI engine for 357 cycles under pre-mixed operation. A subset of these images was used to train three models: a linear regression model, a deep Convolutional Neural Network (CNN) based on the InceptionV3 architecture and a CNN built with assisted learning on the VGG19 architecture.

Understanding the complex, transient spray phenomena associated with Gasoline Direct Injection (GDI) technologies continues to be key when designing injection systems to meet the stringent performance and emissions standards of modern internal combustion engines. Internal flow phenomena, such as string cavitation and hole-to-hole flow variations, are often highly transient and affected by turbulence. To better understand the current degree to which turbulence modeling influences simulations of GDI sprays, RANS and LES simulations have been performed on the multi-hole Spray G injector through the start of injection phase, with results compared to previously available X-Ray radiography data. Specifically, the k-ω SST RANS model and the k-equation LES model with a WALE sub-grid scale stress model have been tested on grids generated with the Generation 3 Spray G geometry, which includes as-produced injector dimensions based on X-Ray radiography measurements.

Increasing the injection pressure in DISI engine is an efficient way to obtain finer droplets but it will also potentially cause spray impingement on the cylinder wall and piston. Consequently, the fuel film sticking on the wall can dramatically increase the soot emission of the engine especially in a cold start condition. On the other hand, ethanol is widely used as an alternative fuel in DI engine due to its sustainable nature and high octane number. In this study, the fuel film characteristics of single-plume ethanol impinging spray was investigated. The experiments were performed under ultra-low fuel/plate temperature to simulate the cold start condition in cold areas. A low temperature thermostatic bath combined with specially designed heat exchangers were used to achieve ultra-low temperature for both the impinging plate and the fuel. Laser induced fluorescence (LIF) technique was employed to measure the thickness of fuel film deposited on the impinging plate.

A computational and experimental study was performed to characterize the flow within a gasoline injector and the ensuing sprays. The computations included the effects of turbulence, cavitation, flash-boiling, compressibility, and the presence of non-condensible gases. The flow domain corresponded to the Engine Combustion Network's Spray G, an eight-hole counterbore injector operating in a variety of conditions. First, a rate tube method was used to measure the rate of injection, which was then used to define inlet boundary conditions for simulation. Correspondingly, injection under submerged conditions was simulated for direct comparison with experimental measurements of discharge coefficient. Next, the internal flow and external spray into pressurized nitrogen were simulated under the base spray G conditions. Finally, injection under flashing conditions was simulated, where the ambient pressure was below the vapor pressure of the fuel.

A numerical and corresponding experimental study was undertaken to identify the ability to accurately predict combustion performance using our 3-D numerical tools for a direct-injection homogeneous-charge engine. To achieve a significant range of combustion rates, the evaluation was conducted for the engine operating with and without enhanced charge motion. Five charge motion configurations were examined, each having different levels of swirl and tumble flow leading to different turbulence generation and decay characteristics. A detailed CFD analysis provides insight into the in-cylinder flow requirements as well as the accuracy of the submodels. The in-cylinder air-fuel distribution, the mass-averaged swirl and tumble levels along with mean flow and turbulent kinetic energies are calculated throughout the induction and compression processes.

Recently, high-speed optical imaging data for a single operating point of a spray-guided gasoline engine has, along with the flamelet model and the G-equation theory, enabled the development of the new spark-ignition model SparkCIMM. Within its framework, detailed chemistry flamelet models capture the experimental feature of multiple localized ignition events along the excessively stretched and restriking spark channel, as well as the observations of non-spherical highly corrugated early turbulent flame fronts. The developed flamelet models account for the substantial turbulent fluctuations in equivalence ratio and enthalpy present under spray-guided conditions. A non-unity Lewis number formulation captures the deficient species diffusion into the highly curved flame reaction zone.

The internal flow in an injector is greatly affected by cavitation formation, and this in turn impacts the spray characteristics of diesel injectors. In the current work, the performance of the Homogeneous Relaxation Model (HRM) in simulating cavitation inside a diesel injector is evaluated. This model is based on the assumption of homogeneous flow, and was originally developed for flash boiling simulations. However, the model can potentially simulate the spectrum of vaporization mechanisms ranging from cavitation to flash boiling through the use of an empirical time scale which depends on the thermodynamic conditions of the injector fuel. A lower value of this time scale represents a lower deviation from thermal equilibrium conditions, which is an acceptable assumption for small-scale cavitating flows. Another important advantage is the ability of this model to be easily coupled with real fuel models.

A CFD code is enhanced with a fuel tracer diagnostic to track the liquid and vapor fuel mass separately from individual spray plumes of a multi-hole injector and the wall film. The approach works by solving a set of additional scalar transport equations for fuel vapor generated from individual nozzle hole and the wall film. The diagnostic tool is first validated against experiments from a 4-valve, wall-guided spark-ignition direct-injection (SIDI) engine. A CFD analysis is carried out to understand the experimentally observed trade-offs in combustion stability and smoke emissions between a 70degree hollow-cone swirl injector and a 40 degree, 5-hole, circular-type multi-hole injector at a lean, stratified idle operating condition. Engine tests show that the multi-hole injector results in lower COV of IMEP than the hollow-cone swirl injector at the expense of significantly higher smoke emissions.

The transient cone angle of pressure swirl sprays from injectors intended for use in gasoline direct injection engines was measured from 2D Mie scattering images. A variety of injectors with varying nominal cone angle and flow rate were investigated. The general cone angle behavior was found to correlate well qualitatively with the measured fuel line pressure and was affected by the different injector specifications. Experimentally measured modulations in cone angle and injection pressure were forced on a comprehensive spray simulation to understand the sensitivity of pulsating injector boundary conditions on general spray structure. Ignoring the nozzle fluctuations led to a computed spray shape that inadequately replicated the experimental images; hence, demonstrating the importance of quantifying the injector boundary conditions when characterizing a spray using high-fidelity simulation tools.