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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.

More stringent emissions regulations are continually being proposed to mitigate adverse human health and environmental impacts of internal combustion engines. With that in mind, it has been proposed that vehicular particulate matter (PM) emissions should be regulated based on particle number in addition to particle mass. One aspect of this project is to study different sample handling methods for number-based aerosol measurements, specifically, two different methods for removing volatile organic compounds (VOCs). One method is a thermodenuder (TD) and the other is an evaporative chamber/diluter (EvCh). These sample-handling methods have been implemented in an engine test cell with a spark-ignited direct injection (SIDI) engine. The engine was designed for stoichiometric, homogeneous combustion.

For optimizing the performance of SI engine such as engine torque, fuel consumption, and emissions, various types of system for variable valve timing were developed by many automotive researchers. In this paper, we investigated the relationship between valve timing and intake orifice noise, and suggested how to improve NVH (Noise, Vibration and Harshness) performance as well as engine torque. Some experiments using the engine dynamometer were carried over about 150 different operating conditions. BEM analysis was also conducted in order to calculate acoustic modes of intake system. The results show that the valve timing and overlap of breathing systems have influence on NVH behavior, especially intake orifice noise over whole range of operating conditions. Valve timing and overlap of intake and exhaust valve were optimized in the view of sound quality as well as overall noise level.

In this study a new model is proposed for turbulent premixed combustion in a spark-ignition engine. An independent transport equation is solved for the mean reaction progress variable in a propagation form in KIVA-3V. An expression for turbulent burning velocity was previously given as a product of turbulent diffusivity in unburned gas, laminar flame speed and maximum flame surface density. The model has similarity with the G equation approach, but originates from zone conditionally averaged formulation for unburned gas. A spark kernel grows initially as a laminar flame and becomes a fully developed turbulent flame brush according to a transition criterion in terms of the kernel size and the integral length scale. Simulation of a homogeneous charge pancake chamber engine showed good agreement with measured flame propagation and pressure trace. The model was also applied against experimental data of Hyundai θ-2.0L SI engine.

Stochastic pre-ignition (SPI) has been commonly observed in turbocharged spark-ignition direct-injection (SIDI) engines at low-speed and high-load conditions, which causes extremely high cylinder pressures that can damage an engine immediately or degrade the engine life. The compositions and properties of fuels and lubricants have shown a strong impact on SPI frequency. This study experimentally evaluated SPI behaviors on a 2.0-liter 4-cylinder turbocharged SIDI engine with China V market fuel and China fuel blended to US Tier II fuel specifications. China V market fuel showed significantly higher SPI frequency and severity than China blended US Tier II fuel, which was attributed to its lower volatility between 100 °C to 150 °C (or lower T60 to T90 in the distillation curve). Two different formulations of lubricant oils were also tested and their impact on SPI were compared.

The objective of this research is a detailed investigation of particulate sizing and number count from a spark-ignited, direct-injection (SIDI) engine at different operating conditions. The engine is a 549 [cc] single-cylinder, four-valve engine with a flat-top piston, fueled by Tier II EEE. A baseline engine operating condition, with a low number of particulates, was established and repeatability at this condition was ascertained. This baseline condition is specified as 2000 rpm, 320 kPa IMEP, 280 [°bTDC] end of injection (EOI), and 25 [°bTDC] ignition timing. The particle size distributions were recorded for particle sizes between 7 and 289 [nm]. The baseline particle size distribution was relatively flat, around 1E6 [dN/dlogDp], for particle diameters between 7 and 100 [nm], before dropping off to decreasing numbers at larger diameters. Distributions resulting from a matrix of different engine conditions were recorded.

For the lightweight and compact cylinder block, new cast iron liner was developed, which has counter spiny form on the out side of the liner. Additionally, the outer surface was spray-coated with Aluminum in order to enhance the heat conductivity and to increase the grip force between the liner and the block. Without any redesign of cylinder block or crankshaft, the displacement of the engine could be increased from 1.25ℓ to 1.4ℓ by adapting this new liner only. This liner enabled to expand the engine displacement without both great dimension changes and production facility changes.

Stochastic Preignition (SPI) is an abnormal combustion phenomenon for internal combustion engines (ICE), which has been a significant impact to automotive companies developing high efficiency, turbocharged, direct fuel injection, spark ignited engines. It is becoming clearer what fuel properties are related to the cause of SPI, whether directly with fuel preparation in the cylinder, or mechanisms related to the deposit build-up which contributes to initial and follow-on SPI events. The purpose of this paper is to provide a summary of global market gasoline fuel properties with special attention given to properties and specific compounds from the fuel and fuel additives that can contribute to SPI and the deposit build-up in engines. Based on a review of the global fuel quality, it appears that the fuel quality has not caught up to meet the technology requirements for fuel economy from modern technology engines.

On the basis of the newly-developed fractal combustion model, the engine-thermodynamic-cycle simulations were conducted with the 1D engine-cycle-simulation program AVL-BOOST for a passenger-car SI engine with a fully-variable valve train. Results of the simulations showed a good agreement with measurements for both full and part load at various engine speeds. On the basis of the thermodynamic model for the engine, the valve event optimization was carried out for both full and part load with a partial factorial DoE plan consisting of various valve event durations and timings. For each of the selected cases, an independent optimization for the ignition timing was performed to determine the minimum BSFC under a constraint on specified knock criteria. Satisfactory results for the valve event optimization were achieved.

Gasoline Direct Injection (GDI) has become the preferred technology for spark-ignition engines resulting in greater specific power output and lower fuel consumption, and consequently reduction in CO2 emission. However, GDI engines face a substantial challenge in meeting new and future emission limits, especially the stringent particle number (PN) emissions recently introduced in Europe and China. Studies have shown that the fuel used by a vehicle has a significant impact on engine out emissions. In this study, nine fuels with varying chemical composition and physical properties were tested on a modern turbo-charged side-mounted GDI engine with design changes to reduce particulate emissions. The fuels tested included four fuels meeting US certification requirements; two fuels meeting European certification requirements; and one fuel meeting China 6 certification requirements being proposed at the time of this work.

High speed natural light motion picture records synchronized with head gasket ionization probe and in-cylinder pressure data have been made in the transparent engine of different combustion chamber configurations. For knocking cycles, the head gasket ionization current method simultaneously taken with pressure data was able to find the location of knocking occurrence. To investigate the effects of combustion chamber configurations, the flame propagation experiments for pent-roof combustion chamber with center ignition ( Modified Type I engine ) and modified pent-roof ( Type II engine ) combustion chamber were performed with high speed natural light photography technique. The flame propagation of Modified Type I engine represents more uniform patterns than that of Type II engine. The investigation of knocking combustion was also made possible by observing flame propagation with the measuring techniques that use head gasket ionization probe and in-cylinder pressure data.

Conventional combustion models are suitable for predicting flame propagation for a wrinkled flamelet configuration. But they cannot predict the burned gas composition. This causes the overestimation of burned gas temperature and pressure. A modified method of combustion simulation was established to calculate the chemical composition and to investigate their ultimate fate in the burned gas region. In this work, the secondary products of combustion process, like CO and H2, were considered as well as the primary products like CO2 and H2O. A 3-dimensional CFD program was used to simulate the turbulent combustion and a zero dimensional equilibrium code was used to predict the chemical composition of burned gas. With this simple connection, more reasonable temperature and pressure approaching the real phenomena were predicted without additional time costs.

Stochastic Preignition (SPI) is an abnormal combustion event that occurs in a turbocharged engine and can lead to the loss in fuel economy and engine hardware damage, and in turn result in customer dissatisfaction. It is a significant limiting factor on the use and continued downsizing of turbocharged spark ignited direct injection (SIDI) gasoline engines. Understanding and mitigating all the factors that cause and influence the rate and severity of SPI occurrence are of critical importance to the engine’s continued use and fuel economy improvements for future designs. Previous studies have shown that the heavy molecular weight components of the fuel formulations are one factor that influences the rate of SPI from a turbocharged SIDI gasoline engine. All the previous studies have involved analyzing the fuel’s petroleum hydrocarbon chemistry, but not specifically the additives that are put in the fuel to protect and clean the internal components over the life of the engine.

A gasoline’s chemical composition impacts a vehicle’s sooting tendency and therefore has been the subject of numerous emissions studies. From these studies, several mathematical correlation equations have been developed to predict a gasoline’s sooting tendency in modern spark-ignited internal combustion engine vehicles. This paper reviews the recently developed predictive tool methods and summarizes five years of global market fuel survey data to characterize gasoline sooting tendency trends around the world. Additionally, the paper will evaluate and suggest changes to the predictive methods to improve emissions correlations.

As global emission standards are becoming more stringent, it is necessary to increase thermal efficiency through the high compression ratio in spark-ignited engines. Various studies are being conducted to mitigate knocking caused by an increased compression ratio, which requires an understanding of the combustion phenomena inside the combustion chamber. In particular, the in-cylinder flow is a major factor affecting the entire combustion process from the generation to the propagation of flames. In the field of spark-ignited engine research, where interest in the concept of lean combustion and the expansion of the EGR supply is increasing, flow analysis is essential to ensure a rapid flame propagation speed and stable combustion process. In this study, the flow around the spark plug was measured by the Laser Doppler Velocimetry system, and the correlation with combustion in spark-ignited engines was analyzed.

This article presents experimental results obtained with a disruptive engine platform, designed to maximize the engine efficiency through a synergetic implementation of downsizing, high compression-ratio, and importantly exhaust-heat energy recovery in conjunction with advanced lean/dilute low-temperature type combustion. The engine architecture is a supercharged high-power output, 1.1-liter engine with two-firing cylinders and a high compression ratio of 13.5: 1. The integrated exhaust heat recovery system is an additional, larger displacement, non-fueled cylinder into which the exhaust gas from the two firing cylinders is alternately transferred to be further expanded. The main goal of this work is to implement in this engine, advanced lean/dilute low-temperature combustion for low-NOx and high efficiency operation, and to address the transition between the different operating modes.

Stochastic or Low-Speed Preignition (SPI or LSPI) is an undesirable abnormal combustion phenomenon encountered in spark-ignition engines. It is characterized by very early heat release and high cylinder pressure and can cause knock, noise and ultimately engine damage. Much of the focus on mitigating SPI has been directed towards the engine oil formulation, leading to the emergence of the Sequence IX test and second-generation GM dexos® oil requirements. Engine design, calibration and fuels also contribute to the prevalence of SPI. As part of a recently completed research consortium, a series of engine tests were completed to determine the impact of fuel composition on SPI frequency. The fuel blends had varying levels of paraffins, olefins, aromatics and ethanol.

The establishment of highly-diluted combustion strategies is one of the major challenges that the next generation of sustainable internal combustion engines must face. The desirable use of high EGR rates and of lean mixtures clashes with the tolerable combustion stability. To this aim, the development of numerical models able to reproduce the degree of combustion variability is crucial to allow the virtual exploration and optimization of a wide number of innovative combustion strategies. In this study ignition experiments using a conventional coil system are carried out in a closed volume combustion vessel with side-oriented flow generated by a speed-controlled fan. Acquisitions for four combinations of premixed propane/air mixture quality (Φ=0.9,1.2), dilution rate (20%-30%) and lateral flow velocity (1-5 m/s) are used to assess the modelling capabilities of a newly developed spark-ignition model for large-eddy simulation (GLIM, GruMo-UniMORE LES Ignition Model).

An experimental piston compounded engine was designed with guidance from thermodynamic modeling, then was built and tested to compare the model predictions to measured results. The piston-compounded concept has shown great potential for improvements in efficiency over current state-of-the-art light-duty engines through the use of an efficient second expansion process to more fully recover energy still present in the exhaust gasses, and was further developed into the Downsized Boosted Dilute Combustion, Exhaust Compounded (DBDC+EC) engine presented here. This paper documents some of the more unique design elements of this engine as well as a performance comparison between test data and modeling expectations. Ultimately, an experimental stoichiometric spark-ignited piston compounded engine was designed, five blocks were built, and collectively they were run for thousands of hours.

In order to further understand the sequence of events leading to stochastic preignition in a spark-ignition engine, a methodology previously developed by the authors was used to evaluate the propensity of a wide range of fuels to establishing propagating flames under conditions representative of those at which stochastic preignition (SPI) occurs. The fuel matrix included single component hydrocarbons, binary mixtures, and real fuel blends. The propensity of each fuel to establish a flame was correlated to multiple fuel properties and shown to exhibit consistent blending behaviors. No single parameter strongly predicted a fuel’s propensity to establish a flame, while multiple reactivity-based parameters exhibited moderate correlation. A two-stage model of the flame establishment process was developed to interpret and explain these results.