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In-cylinder pressure measurement is an important tool in internal combustion engine research and development for combustion, cycle performance, and knock analysis in spark-ignition engines. In a typical laboratory setup, a sub crank angle resolved (typically between 0.1o and 0.5o) optical encoder is installed on the engine crankshaft, and a piezoelectric pressure transducer is installed in the engine cylinder. The charge signal produced by the transducer due to changes in cylinder pressure during the engine cycle is converted to voltage by a charge amplifier, and this analog voltage is read by a high-speed data acquisition (DAQ) system at each encoder trigger pulse. The high speed of engine operation and the need to collect hundreds of engine cycles for appropriate cycle-averaging requires significant processor speed and memory, making typical data acquisition systems very expensive.

Spark ignition engines utilize catalytic converters to reform harmful exhaust gas emissions such as carbon monoxide, unburned hydrocarbons, and oxides of nitrogen into less harmful products. Aftertreatment devices require the use of expensive catalytic metals such as platinum, palladium, and rhodium. Meanwhile, tightening automotive emissions regulations globally necessitate the development of high-performance exhaust gas catalysts. So, automotive manufactures must balance maximizing catalyst performance while minimizing production costs. There are thousands of different recipes for catalytic converters, with each having a different effect on the various catalytic chemical reactions which impact the resultant tailpipe gas composition. In the development of catalytic converters, simulation models are often used to reduce the need for physical parts and testing, thus saving significant time and money.

In the automotive industry, performing steady-state tests on an internal combustion engine can be a time consuming and costly process, but it is necessary to ensure the engine meets performance and emissions criteria set by the manufacturer and regulatory agencies. Any measures that can reduce the amount of time required to complete these testing campaigns provides significant benefits to manufacturers. The purpose of this work is then to develop a systematic approach to minimize the time required to conduct a steady-state engine test campaign using a Savitsky-Golay filter to calculate measured signal gradients for continuous steady-state detection. Experiments were conducted on an Armfield CM11-MKII Gasoline Engine test bench equipped with a 1.2L 3-cylinder Volkswagen EA111 R3 engine. The test bench utilizes throttle position control and an eddy current dynamometer braking system with automatic PID control of engine speed.

Hybrid powertrain has been proven to be an effective fuel-saving technology in commercial vehicles, but many hybrid commercial vehicles still use conventional diesel engines, resulting in limited fuel savings. The main purpose of this study is to enhance the thermal efficiency of a dedicated hybrid diesel engine focusing on the characteristic operating conditions. Via fundamental thermodynamics process analysis of internal combustion engine, steel piston with high compression ratio, air system involving two-stage turbocharger(2TC) with an intercooler, and late intake valve closing(IVC) timing are proposed to improve the thermal efficiency of the engine. Experimental results show that high compression ratio and lower thermal conductivity of the combustion chamber surface lead to lower heat release rates, requiring optimization of piston profile to accelerate the mixing rate. Besides, high compression ratio also leads to higher mechanical losses.

Mobility in the automotive and transportation sectors has been experiencing a period of unprecedented evolution. A growing need for efficient, clean and safe mobility has increased momentum toward sustainable technologies in these sectors. Toward this end, battery electric vehicles have drawn keen interest and their market share is expected to grow significantly in the coming years, especially in light-duty applications such as passenger cars. Although the battery electric vehicles feature high performance and zero tailpipe emission characteristics, economic and technical issues such as battery cost, driving range, recharging time and infrastructure remain main hurdles that need to be fully addressed. In particular, the low power density of the battery limits its broad adoption in heavy-duty applications such as class 8 semi-trailer trucks due to the required size and weight of the battery and electric motor.

Spray-wall interactions in diesel engines have a strong influence on turbulent flow evolution and mixing, which influences the engine’s thermal efficiency and pollutant-emissions behavior. Previous optical experiments and numerical investigations of a stepped-lip diesel piston bowl focused on how spray-wall interactions influence the formation of squish-region vortices and their sensitivity to injection timing. Such vortices are stronger and longer-lived at retarded injection timings and are correlated with faster late-cycle heat release and soot reductions, but are weaker and shorter-lived as injection timing is advanced. Computational fluid dynamics (CFD) simulations predict that piston bowls with more space in the squish region can enhance the strength of these vortices at near-TDC injection timings, which is hypothesized to further improve peak thermal efficiency and reduce emissions. The dimpled stepped-lip (DSL) piston is such a design.

G-Equation models represent propagating flame fronts with an implicit two-dimensional surface representation (level-set). Level-set methods are fast, as transport source terms for the implicit surface can be solved with finite-volume operators on the finite-volume domain, without having to build the actual surface. However, they include approximations whose practical effects are not properly understood. In this study, we improved the numerics of the FRESCO CFD code’s G-Equation solver and developed a new method to simulate kernel growth using signed distance functions and the analytical sphere-mesh overlap. We analyzed their role for simulating propane/air flames, using three well-established constant-volume configurations: a one-dimensional, freely propagating laminar flame; a disc-shaped, constant-volume swirl combustor; and torch-jet flame development through an orifice from a two-chamber device.

A one-dimensional, non-equilibrium, compressible law of the wall model is proposed to increase the accuracy of heat transfer predictions from computational fluid dynamics (CFD) simulations of internal combustion engine flows on engineering grids. Our 1D model solves the transient turbulent Navier-Stokes equations for mass, momentum, energy and turbulence under the thin-layer assumption, using a finite-difference spatial scheme and a high-order implicit time integration method. A new algebraic eddy-viscosity closure, derived from the Han-Reitz equilibrium law of the wall, with enhanced Prandtl number sensitivity and compressibility effects, was developed for optimal performance. Several eddy viscosity sub-models were tested for turbulence closure, including the two-equation k-epsilon and k-omega, which gave insufficient performance.

Recent research on thermal reciprocating engines has focused on the influence of lubricant oil on the combustion process, which can lead to highly undesired super-knock events. Low-Speed Pre-Ignition (LSPI) events severely limit the further development of Direct Injection Spark Ignition Engines (DISI), preventing high efficiencies from being achieved. However, there is still a lack of knowledge about the fundamental mechanisms leading to LSPI, due to the complex phenomena involved and the interaction between lubricant oil and fuel. Understanding how the presence of lubricant oil traces affects gasoline chemical reactivity is an essential step for performing successful numerical simulations aimed at predicting the onset of LSPI phenomena. Reaction mechanisms able to predict oil-fuel interaction have been proposed, but they are computationally demanding.

Expanding upon the authors’ previous work which utilized a GT-Power model of the Cooperative Fuels Research (CFR) engine under Research Octane Number (RON) conditions, this work defines the boundary conditions of the CFR engine under Motored Octane Number (MON) test conditions. The GT-Power model was validated against experimental CFR engine data for primary reference fuel (PRF) blends between 60 and 100 under standard MON conditions, defining the full range of interest of MON for gasoline-type fuels. The CFR engine model utilizes a predictive turbulent flame propagation sub-model, and a chemical kinetic solver for the end-gas chemistry. The validation was performed simultaneously for thermodynamic and chemical kinetic parameters to match in-cylinder pressure conditions, burn rate, and knock point prediction with experimental data, requiring only minor modifications to the flame propagation model from previous model iterations.

Appropriate spray modeling in multidimensional simulations of diesel engines is well known to affect the overall accuracy of the results. More and more accurate models are being developed to deal with drop dynamics, breakup, collisions, and vaporization/multiphase processes; the latter ones being the most computationally demanding. In fact, in parallel calculations, the droplets occupy a physical region of the in-cylinder domain, which is generally very different than the topology-driven finite-volume mesh decomposition. This makes the CPU decomposition of the spray cloud severely uneven when many CPUs are employed, yielding poor parallel performance of the spray computation. Furthermore, mesh-independent models such as collision calculations require checking of each possible droplet pair, which leads to a practically intractable O(np2/2) computational cost, np being the total number of droplets in the spray cloud, and additional overhead for parallel communications.

This work numerically investigates the detailed combustion kinetics of partially premixed combustion (PPC) in a diesel engine under three different premixed ratio fuel conditions. A reduced Primary Reference Fuel (PRF) chemical kinetics mechanism was coupled with CONVERGE-SAGE CFD model to predict PPC combustion under various operating conditions. The experimental results showed that the increase of premixed ratio (PR) fuel resulted in advanced combustion phasing. To provide insight into the effects of PR on ignition delay time and key reaction pathways, a post-process tool was used. The ignition delay time is related to the formation of hydroxyl (OH). Thus, the validated Converge CFD code with the PRF chemistry and the post-process tool was applied to investigate how PR change the formation of OH during the low-to high-temperature reaction transition. The reaction pathway analyses of the formations of OH before ignition time were investigated.

Lagrangian spray modeling represents a critical boundary condition for multidimensional simulations of in-cylinder flow structure, mixture formation and combustion in internal combustion engines. Segregated models for injection, breakup, collision and vaporization are usually employed to pass appropriate momentum, mass, and energy source terms to the gas-phase solver. Careful calibration of each sub-model generally produces appropriate results. Yet, the predictiveness of this modeling approach has been questioned by recent experimental observations, which showed that at trans- and super-critical conditions relevant to diesel injection, classical atomization and vaporization behavior is replaced by a mixing-controlled phase transition process of a dense fluid. In this work, we assessed the shortcomings of classical spray modeling with respect to real-gas and phase-change behavior, employing a multicomponent phase equilibrium solver and liquid-jet theory.

OH, soot and temperature distributions of wall-impinging diesel fuel spray were investigated in a high-temperature high-pressure constant volume combustion vessel. The ambient temperature (Ta) was set as 773 K, and the wall temperature (Tw) was set as 523 K, 673 K, 773 K, respectively. Three different injection pressures (Pi) of 60 MPa, 100 MPa, 160 MPa, and the ambient pressures (Pa) of 4 MPa were applied. The OH spatial distributions of wall-impinging spray were measured by the method of OH chemiluminescence imaging. Two-color pyrometry was applied to evaluate the spatial distributions of KL factor and flame temperature of wall-impinging spray. The results reveal that, OH chemiluminescence is observed in the region near the impingement point firstly. The regions of high OH chemiluminescence intensity and high KL factor appear in the location near the wall surface along the whole combustion process.

In this work we studied the effects of piston bowl design on combustion in a small-bore direct-injection diesel engine. Two bowl designs were compared: a conventional, omega-shaped bowl and a stepped-lip piston bowl. Experiments were carried out in the Sandia single-cylinder optical engine facility, with a medium-load, mild-boosted operating condition featuring a pilot+main injection strategy. CFD simulations were carried out with the FRESCO platform featuring full-geometric body-fitted mesh modeling of the engine and were validated against measured in-cylinder performance as well as soot natural luminosity images. Differences in combustion development were studied using the simulation results, and sensitivities to in-cylinder flow field (swirl ratio) and injection rate parameters were also analyzed.

Machine learning methods, such as decision trees and deep neural networks, are becoming increasingly important and useful for data analysis in various scientific fields including dynamics and control, signal processing, pattern recognition, fluid mechanics, and chemical synthesis, etc. For future engine design and performance optimization, there is an urgent need for a robust predictive model which could capture the major combustion properties such as autoignition and flame propagation of multicomponent fuels under a wide range of engine operating conditions, without massive experimental measurement or computational efforts. It will be shown that these long-held limitations and challenges related to complex fuel combustion and engine research could be readily solved by implementing machine learning methods.

Sector mesh modeling is the dominant computational approach for combustion system design optimization. The aim of this work is to quantify the errors descending from the sector mesh approach through three geometric modeling approaches to an optical diesel engine. A full engine geometry mesh is created, including valves and intake and exhaust ports and runners, and a full-cycle flow simulation is performed until fired TDC. Next, an axisymmetric sector cylinder mesh is initialized with homogeneous bulk in-cylinder initial conditions initialized from the full-cycle simulation. Finally, a 360-degree azimuthal mesh of the cylinder is initialized with flow and thermodynamics fields at IVC mapped from the full engine geometry using a conservative interpolation approach. A study of the in-cylinder flow features until TDC showed that the geometric features on the cylinder head (valve tilt and protrusion into the combustion chamber, valve recesses) have a large impact on flow complexity.

The long-term goal of this work is to develop a conceptual model for multiple injections of diesel jets. The current work contributes to that effort by performing a detailed modeling investigation into mechanisms that are predicted to control 1st and 2nd stage ignition in single-pulse diesel (n-dodecane) jets under different conditions. One condition produces a jet with negative ignition dwell that is dominated by mixing-controlled heat release, and the other, a jet with positive ignition dwell and dominated by premixed heat release. During 1st stage ignition, fuel is predicted to burn similarly under both conditions; far upstream, gases at the radial-edge of the jet, where gas temperatures are hotter, partially react and reactions continue as gases flow downstream. Once beyond the point of complete fuel evaporation, near-axis gases are no longer cooled by the evaporation process and 1st stage ignition transitions to 2nd stage ignition.

Liquefied natural gas (LNG) engine could provide both reduced operating cost and reduction of greenhouse gas (GHG) emissions. Stoichiometric operation with EGR and the three-way catalyst has become a potential approach for commercial LNG engines to meet the Euro VI emissions legislation. In the current study, numerical investigations on the knocking tendency of several combustion chambers with different geometries and corresponding performances were conducted using CONVERGE CFD code with G-equation flame propagation model coupled with a reduced natural gas chemical kinetic mechanism. The results showed that the CFD modeling approach could predict the knock phenomenon in LNG engines reasonably well under different thermodynamic and flow field conditions.

Engine experiments have revealed the importance of fuel condensation on the emission characteristics of low temperature combustion. However, direct in-cylinder experimental evidence has not been reported in the literature. In this paper, the in-cylinder condensation processes observed in optically accessible engine experiments are first illustrated. The observed condensation processes are then simulated using state-of-the-art multidimensional engine CFD simulations with a phase transition model that incorporates a well-validated phase equilibrium numerical solver, in which a thermodynamically consistent phase equilibrium analysis is applied to determine when mixtures become unstable and a new phase is formed. The model utilizes fundamental thermodynamics principles to judge the occurrence of phase separation or combination by minimizing the system Gibbs free energy.