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Reactivity-controlled compression ignition (RCCI) has been shown to be capable of providing improved engine efficiencies coupled with the benefit of low emissions via in-cylinder fuel blending. Much of the previous body of work has studied the benefits of RCCI operation using high injection pressures (e.g., 500 bar or greater) with common rail injection (CRI) hardware. However, low-pressure fueling technology is capable of providing significant cost savings. Due to the broad market adoption of gasoline direct injection (GDI) fueling systems, a market-type prototype GDI injector was selected for this study. Single-cylinder light-duty engine experiments were undertaken to examine the performance and emissions characteristics of the RCCI combustion strategy with low-pressure GDI technology and compared against high injection pressure RCCI operation. Gasoline and diesel were used as the low-reactivity and high-reactivity fuels, respectively.

This paper investigates flow and combustion in a full-cycle simulation of a four-stroke, three-valve HCCI engine by visualizing the flow with pathlines. Pathlines trace massless particles in a transient flow field. In addition to visualization, pathlines are used here to trace the history, or evolution, of flow fields and species. In this study evolution is followed from the intake port through combustion. Pathline analysis follows packets of intake charge in time and space from induction through combustion. The local scalar fields traversed by the individual packets in terms of velocity magnitude, turbulence, species concentration and temperatures are extracted from the simulation results. The results show how the intake event establishes local chemical and thermal environments in-cylinder and how the species respond (chemically react) to the local field.

The purpose of this research is to develop a prediction technique that can be used in the development of port fuel-injection (hereinafter called PFI) gasoline engines, especially for general purpose small utility engines. Utility engines have two contradictory desirable aspects: compactness and high-power at wide open throttle. Therefore, applying the port fuel injector to utility engines presents a unique intractableness that is different from application to automobiles or motorcycles. At the condition of wide open throttle, a large amount of fuel is required to output high power, and injected fuel is deposited as a wall film on the intake port wall. Despite the fuel rich condition, emissions are required to be kept under a certain level. Thus, it is significant to understand the wall film phenomenon and control film thickness in the intake ports.

A transport equation residual model incorporating refined G-equation and detailed chemical kinetics combustion models has been developed and implemented in the ERC KIVA-3V release2 code for Gasoline Direct Injection (GDI) engine simulations for better predictions of flame propagation. In the transport equation residual model a fictitious species concept is introduced to account for the residual gases in the cylinder, which have a great effect on the laminar flame speed. The residual gases include CO2, H2O and N2 remaining from the previous engine cycle or introduced using EGR. This pseudo species is described by a transport equation. The transport equation residual model differentiates between CO2 and H2O from the previous engine cycle or EGR and that which is from the combustion products of the current engine cycle.

An investigation of high speed direct injection (DI) compression ignition (CI) engine combustion fueled with gasoline injected using a triple-pulse strategy in the low temperature combustion (LTC) regime is presented. This work aims to extend the operation ranges for a light-duty diesel engine, operating on gasoline, that have been identified in previous work via extended controllability of the injection process. The single-cylinder engine (SCE) was operated at full load (16 bar IMEP, 2500 rev/min) and computational simulations of the in-cylinder processes were performed using a multi-dimensional CFD code, KIVA-ERC-Chemkin, that features improved sub-models and the Chemkin library. The oxidation chemistry of the fuel was calculated using a reduced mechanism for primary reference fuel combustion chosen to match ignition characteristics of the gasoline fuel used for the SCE experiments.

Many recent studies have shown that the Reactivity Controlled Compression Ignition (RCCI) combustion strategy can achieve high efficiency with low emissions. However, it has also been revealed that RCCI combustion is difficult at high loads due to its premixed nature. To operate at moderate to high loads with gasoline/diesel dual fuel, high amounts of EGR or an ultra low compression ratio have shown to be required. Considering that both of these approaches inherently lower thermodynamic efficiency, in this study natural gas was utilized as a replacement for gasoline as the low-reactivity fuel. Due to the lower reactivity (i.e., higher octane number) of natural gas compared to gasoline, it was hypothesized to be a better fuel for RCCI combustion, in which a large reactivity gradient between the two fuels is beneficial in controlling the maximum pressure rise rate.

In multidimensional modeling, fuels have been represented predominantly by single components, such as octane for gasoline. Several bicomponent studies have been performed, but these are still limited in their ability to represent real fuels, which are blends of as many as 300 components. This study outlines a method by which the fuel composition is represented by a distribution function of the fuel molecular weight. This allows a much wider range of compositions to be modeled, and only requires including two additional “species” besides the fuel, namely the mean and second moment of the distribution. This approach has been previously presented but is applied here to multidimensional calculations. Results are presented for single component droplet vaporization for comparison with single component fuel predictions, as well as results for a multicomponent gasoline and a diesel droplet.

In this paper, knock in a Ford single cylinder direct-injection spark-ignition (DISI) engine was modeled and investigated using the KIVA-3V code with a G-equation combustion model coupled with detailed chemical kinetics. The deflagrative turbulent flame propagation was described by the G-equation combustion model. A 22-species, 42-reaction iso-octane (iC8H18) mechanism was adopted to model the auto-ignition process of the gasoline/air/residual-gas mixture ahead of the flame front. The iso-octane mechanism was originally validated by ignition delay tests in a rapid compression machine. In this study, the mechanism was tested by comparing the simulated ignition delay time in a constant volume mesh with the values measured in a shock tube under different initial temperature, pressure and equivalence ratio conditions, and acceptable agreements were obtained.

A global optimization method has been developed for an engine simulation code and utilized in the search of optimal fuel injection strategies. This method uses a Lagrange interpolation function which interpolates engine output data generated at the vertices and the intermediate points of the input parameters. This interpolation function is then used to find a global minimum over the entire parameter set, which in turn becomes the starting point of a CFD-based optimization. The CFD optimization is based on a steepest descent method with an adaptive cost function, where the line searches are performed with a fast-converging backtracking algorithm. The adaptive cost function is based on the penalty method, where the penalty coefficient is increased after every line search. The parameter space is normalized and, thus, the optimization occurs over the unit cube in higher-dimensional space.

The lift-off length plays a significant role in spray combustion as it influences the air entrainment upstream of the lift-off location and hence the soot formation. Accurate prediction of lift-off length thus becomes a prerequisite for accurate soot prediction in lifted flames. In the present study, KIVA-3v coupled with CHEMKIN, as developed at the Engine Research Center (ERC), is used as the CFD model. Experimental data from the Sandia National Labs. is used for validating the model predictions of n-heptane lift-off lengths and soot formation details in a constant volume combustion chamber. It is seen that the model predictions, in terms of lift-off length and soot mass, agree well with the experimental results for low ambient density (14.8 kg/m3) cases with different EGR rates (21% O2 - 8% O2). However, for high density cases (30 kg/m3) with different EGR rates (15% O2 - 8% O2) disagreements were found.

As we continue to create ever-lighter road vehicles, the challenge of balancing weight reduction and structural performance also continues. One of the key parts this occurs on is the hood, where lighter materials (e.g. aluminum) have been used. However, the aerodynamic loads, such as hood lift, are essentially unchanged and are driven by the front fascia and front grille size and styling shape. This paper outlines a combination CFD/FEA prediction method for hood deflection performance at high speeds, by using the surface pressures as boundary conditions for a FEA linear static deflection analysis. Additionally, custom post-processing methods were developed to enhance flow analysis and understanding. This enabled the modification of existing test methods to further improve accuracy to real world conditions. The application of these analytical methods and their correlation with experimental results are discussed in this paper.

The cost of fuel and the desire for fuel efficiency continue to drive automobile manufacturers to invest in and to prioritize vehicle designs and performance. There has long been a fundamental understanding that aerodynamic efficiency (drag) has an effect on this phenomenon. The focus of this paper is to demonstrate how emergent aerodynamic performance calculation tools can be efficiently and effectively utilized for realizing improvements to vehicle performance, thereby enhancing customer satisfaction and societal acceptance. These tools include Computational Fluid Dynamic analysis (CFD) which further includes visualization techniques, shape deformation, DOE, and optimization methods, among others.

Multi-zone CFD simulations with detailed kinetics were used to model iso-octane HCCI experiments performed on a single-cylinder research engine. The modeling goals were to validate the method (multi-zone combustion modeling) and the reaction mechanism (LLNL 857 species iso-octane) by comparing model results to detailed exhaust speciation data, which was obtained with gas chromatography. The model is compared to experiments run at 1200 RPM and 1.35 bar boost pressure over an equivalence ratio range from 0.08 to 0.28. Fuel was introduced far upstream to ensure fuel and air homogeneity prior to entering the 13.8:1 compression ratio, shallow-bowl combustion chamber of this 4-stroke engine. The CFD grid incorporated a very detailed representation of the crevices, including the top-land ring crevice and head-gasket crevice. The ring crevice is resolved all the way into the ring pocket volume. The detailed grid was required to capture regions where emission species are formed and retained.

Transient engine operations are modeled and simulated with a 1-D code (GT Power) using heat release and emission data computed by a 3-D CFD code (Kiva3). During each iteration step of a transient engine simulation, the 1-D code utilizes the 3-D data to interpolate the values for heat release and emissions. The 3-D CFD computations were performed for the compression and combustion stroke of strategically chosen engine operating points considering engine speed, torque and excess air. The 3-D inlet conditions were obtained from the 1-D code, which utilized 3-D heat release data from the previous 1-D unsteady computations. In most cases, only two different sets of 3-D input data are needed to interpolate the transient phase between two engine operating points. This keeps the computation time at a reasonable level. The results are demonstrated on the load response of a generator which is driven by a medium-speed diesel engine.

Predictive models of soot formation during Diesel combustion are of great practical interest, particularly in light of newly proposed strict regulations on particulate emissions. A modified version of the phenomenological model of soot formation developed previously has been implemented in KIVA-II CFD code. The model includes major generic processes involved in soot formation during combustion, i.e., formation of soot precursors, formation of surface growth species, soot particle nucleation, coagulation, surface growth and oxidation. The formulation of the model within the KIVA-II is fully coupled with the mass and energy balances in the system. The model performance has been tested by comparison with the results of optical in-cylinder soot measurements in a single cylinder Cummins NH Diesel engine. The predicted soot volume fraction, number density and particle size agree reasonably well with the experimental data.

Improvement of engine cycle thermal efficiency is an effective way to increase engine torque and to reduce fuel consumption simultaneously. However, the extent of the improvement is limited by engine knock, which is more evident at low engine speeds when combustion flame propagation is relatively slow. To prevent engine damage due to knock, the spark ignition timing of a gasoline engine is usually controlled by a knock sensor. Therefore, an engine's ignition timing cannot be set freely to achieve best engine performance and fuel economy. Whether ignition timings for a multi-cylinder engine are the same or can be set differently for each cylinder, it is not desirable for each cylinder has big deviation from the median with respect to knock tendency. It is apparent that effective measures to improve engine knock toughness should address both uniformity of all cylinders of a multi-cylinder engine and improvement of median knock toughness.

Neural networks are useful tools for optimization studies since they are very fast, so that while capturing the accuracy of multi-dimensional CFD calculations or experimental data, they can be run numerous times as required by many optimization techniques. This paper describes how a set of neural networks trained on a multi-dimensional CFD code to predict pressure, temperature, heat flux, torque and emissions, have been used by a genetic algorithm in combination with a hill-climbing type algorithm to optimize operating parameters of a diesel engine over the entire speed-torque map of the engine. The optimized parameters are mass of fuel injected per cycle, shape of the injection profile for dual split injection, start of injection, EGR level and boost pressure. These have been optimized for minimum emissions. Another set of neural networks have been trained to predict the optimized parameters, based on the speed-torque point of the engine.

Neural networks have been used for engine computations in the recent past. One reason for using neural networks is to capture the accuracy of multi-dimensional CFD calculations or experimental data while saving computational time, so that system simulations can be performed within a reasonable time frame. This paper describes three methods to improve upon neural network predictions. Improvement is demonstrated for in-cylinder pressure predictions in particular. The first method incorporates a physical combustion model within the transfer function of the neural network, so that the network predictions incorporate physical relationships as well as mathematical models to fit the data. The second method shows how partitioning the data into different regimes based on different physical processes, and training different networks for different regimes, improves the accuracy of predictions.

The present study investigated HCCI combustion in a heavy-duty diesel engine both experimentally and numerically. The engine was equipped with a hollow-cone pressure-swirl injector using gasoline direct injection. Characteristics of HCCI combustion were obtained by very early injection with a heated intake charge. Experimental results showed an increase in NOx emission and a decrease in UHC as the injection timing was retarded. It was also found that optimization can be achieved by controlling the intake temperature together with the start-of-injection timing. The experiments were modeled by using an engine CFD code with detailed chemistry. The CHEMKIN code was implemented into KIVA-3V such that the chemistry and flow solutions were coupled. The model predicted ignition timing, cylinder pressure, and heat release rates reasonably well. The NOx emissions were found to increase as the injection timing was retarded, in agreement with experimental results.

Diesel engine in-cylinder combustion processes have been studied using computational models with particular attention to spray development, vaporization, fuel/air mixture formation and combustion. A thermodynamic zero-dimensional cycle analysis program was used to determine initial conditions for the multidimensional calculations. A modified version of the time-dependent, three-dimensional computational fluid dynamics code KIVA-II was used for the computations, with a detailed treatment for the spray calculations and a simplified model for combustion. The calculations were used to obtain an understanding of the potential predictive capabilities of the models. It was found that there is a strong sensitivity of the results to numerical grid resolution. With proper grid resolution, the calculations were found to reproduce experimental data for non- vaporizing and vaporizing sprays. However, for vaporizing sprays with combustion, extremely fine grids are needed.