Search Results

The objective of this investigation is to optimize a light-duty diesel engine in order to minimize soot, NOx, carbon monoxide (CO), unburned hydrocarbon (UHC) emissions and peak pressure rise rate (PPRR) while improving fuel economy in a low oxygen environment. Variables considered are the injection timings, fractional amount of fuel per injection, half included spray angle, swirl, and stepped-bowl piston geometry. The KIVA-CHEMKIN code, a multi-dimensional computational fluid dynamics (CFD) program with detailed chemistry is used and is coupled to a multi-objective genetic algorithm (MOGA) along with an automated grid generator. The stepped-piston bowl allows more options for spray targeting and improved charge preparation. Results show that optimal combinations of the above variables exist to simultaneously reduce emissions and fuel consumption. Details of the spray targeting were found to have a major impact on the combustion process.

This study explores an Adaptive Injection Strategy (AIS) that employs multiple injections at both low and high pressures to reduce spray-wall impingement, control combustion phasing, and limit pressure rise rates in a Premixed Compression Ignition (PCI) engine. Previous computational studies have shown that reducing the injection pressure of early injections can prevent spray-wall impingement caused by long liquid penetration lengths. This research focuses on understanding the performance and emissions benefits of low and high pressure split injections through experimental parametric sweeps of a 0.48 L single-cylinder test engine operating at 2000 rev/min and 5.5 bar nominal IMEP. This study examines the effects of 2nd injection pressure, EGR, swirl ratio, and 1st and 2nd injection timing, for both single heat release and two-peak high temperature heat release cases. In order to investigate the AIS concept experimentally, a Variable Injection Pressure (VIP) system was developed.

The present work proposes a methodology for diesel engine development using multi-dimensional CFD and computer optimization. A multi-objective genetic algorithm coupled with the KIVA3V Release 2 code was used to optimize a high speed direct injection (HSDI) diesel engine for passenger car applications. The simulations were conducted using high-throughput computing with the CONDOR system. An automated grid generator was used for efficient mesh generation with 11 variable piston bowl geometry parameters. The first step in the procedure was to search for an optimal nozzle and piston bowl design. In this case, spray targeting, swirl ratio, and piston bowl shape were optimized separately for two full-load cases using simpler efficient combustion models (the characteristic time scale model and the shell ignition model). The optimal designs from the two optimizations were then validated using a combustion model with detailed chemistry (KIVA-CHEMKIN model and ERC n-heptane mechanism).

This study investigates the potential of controlling premixed charge compression ignition (PCCI and HCCI) combustion strategies by varying fuel reactivity. In-cylinder fuel blending using port fuel injection of gasoline and early cycle direct injection of diesel fuel was used for combustion phasing control at both high and low engine loads and was also effective to control the rate of pressure rise. The first part of the study used the KIVA-CHEMKIN code and a reduced primary reference fuel (PRF) mechanism to suggest optimized fuel blends and EGR combinations for HCCI operation at two engine loads (6 and 11 bar net IMEP). It was found that the minimum fuel consumption could not be achieved using either neat diesel fuel or neat gasoline alone, and that the optimal fuel reactivity required decreased with increasing load. For example, at 11 bar net IMEP, the optimum fuel blend and EGR rate for HCCI operation was found to be PRF 80 and 50%, respectively.

The goal of this research is to investigate the physical parameters of stoichiometric operation of a diesel engine under a light load operating condition (6∼7 bar IMEP). This paper focuses on improving the fuel efficiency of stoichiometric operation, for which a fuel consumption penalty relative to standard diesel combustion was found to be 7% from a previous study. The objective is to keep NOx and soot emissions at reasonable levels such that a 3-way catalyst and DPF can be used in an aftertreatment combination to meet 2010 emissions regulation. The effects of intake conditions and the use of group-hole injector nozzles (GHN) on fuel consumption of stoichiometric diesel operation were investigated. Throttled intake conditions exhibited about a 30% fuel penalty compared to the best fuel economy case of high boost/EGR intake conditions. The higher CO emissions of throttled intake cases lead to the poor fuel economy.

A multi-objective genetic algorithm coupled with the KIVA3V release 2 code was used to optimize the piston bowl geometry, spray targeting, and swirl ratio levels of a high speed direct injected (HSDI) diesel engine for passenger cars. Three modes, which represent full-, mid-, and low-loads, were optimized separately. A non-dominated sorting genetic algorithm II (NSGA II) was used for the optimization. High throughput computing was conducted using the CONDOR software. An automated grid generator was used for efficient mesh generation with variable geometry parameters, including open and reentrant bowl designs. A series of new spray models featuring reduced mesh dependency were also integrated into the code. A characteristic-time combustion (CTC) model was used for the initial optimization for time savings. Model validation was performed by comparison with experiments for the baseline engine at full-, mid-, and low-load operating conditions.

A study of partially premixed combustion (PPC) with non-oxygenated 91 pump octane number1 (PON) commercially available gasoline was performed using a heavy-duty (HD) compression-ignition (CI) 2.44 l Caterpillar 3401E single-cylinder oil test engine (SCOTE). The experimental conditions selected were a net indicated mean effective pressure (IMEP) of 11.5 bar, an engine speed of 1300 rev/min, an intake temperature of 40°C with intake and exhaust pressures of 200 and 207 kPa, respectively. The baseline case for all studies presented had 0% exhaust gas recirculation (EGR), used a dual injection strategy a -137 deg ATDC pilot SOI and a -6 deg ATDC main start-of-injection (SOI) timing with a 30/70% pilot/main fuel split for a total of 5.3 kg/h fueling (equating to approximately 50% load). Combustion and emissions characteristics were explored relative to the baseline case by sweeping main and pilot SOI timings, injection split fuel percentage, intake pressure, load and EGR levels.

Two advanced combustion models have been validated with the KIVA-3V Release 2 code in the context of two-stage combustion in a heavy duty diesel engine. The first model uses CHEMKIN to directly integrate chemistry in each computational cell. The second model accounts for flame propagation with the G-equation, and CHEMKIN predicts autoignition and handles chemistry ahead of and behind the flame front. A Damköhler number criterion was used in flame containing cells to characterize the local mixing status and determine whether heat release and species change should be a result of flame propagation or volumetric heat release. The purpose of this criterion is to make use of physical and chemical time scales to determine the most appropriate chemistry model, depending on the mixture composition and thermodynamic properties of the gas in each computational cell.

A multi-objective genetic algorithm methodology was applied to a heavy-duty diesel engine at three different operating conditions of interest. Separate optimizations were performed over various fuel injection nozzle parameters, piston bowl geometries and swirl ratios (SR). Different beginning of injection (BOI) timings were considered in all optimizations. The objective of the optimizations was to find the best possible fuel economy, NOx, and soot emissions tradeoffs. The input parameter ranges were determined using design of experiment methodology. A non-dominated sorting genetic algorithm II (NSGA II) was used for the optimization. For the optimization of piston bowl geometry, an automated grid generator was used for efficient mesh generation with variable geometry parameters. The KIVA3V release 2 code with improved ERC sub-models was used. The characteristic time combustion (CTC) model was employed to improve computational efficiency.

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.

In the present paper optimization tools are used to recommend low-emission engine combustion chamber designs, spray targeting and swirl ratio levels for a heavy-duty diesel engine operated at high-load. The study identifies aspects of the combustion and pollution formation that are affected by mixing processes, and offers guidance for better matching of the piston geometry with the spray plume geometry for enhanced mixing. By coupling a GA (genetic algorithm) with the KIVA-CFD code, and also by utilizing an automated grid generation technique, multi-objective optimizations with goals of low emissions and fuel economy were achieved. Three different multi-objective genetic algorithms including a Micro-Genetic Algorithm (μGA), a Nondominated Sorting Genetic Algorithm II (NSGA II) and an Adaptive Range Multi-Objective Genetic Algorithm (ARMOGA) were compared for conducting the optimization under the same conditions.

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.

Homogeneous Charge Compression Ignition (HCCI) combustion is being considered as a practical solution for diesel engines due to its high efficiency and low NOx and PM emissions. However, for diesel HCCI operation, there are still several problems that need to be solved. One is the spay-wall impingement issue associated with early injection, and a further problem is the extension of HCCI operation from low load to higher engine loads. In this study, a combination of Adaptive Injection Strategies (AIS) and a Two-Stage Combustion (TSC) strategy are proposed to solve the aforementioned problems. A multi-dimensional Computational Fluid Dynamics (CFD) code with detailed chemistry, the KIVA-CHEMKIN-GA code, was employed in this study, where Genetic Algorithms (GA) were used to optimize heavy-duty diesel engine operating parameters. The TSC concept was applied to optimize the combustion process at high speed (1737 rev/min) and medium load (57% load).

A computational study was performed to evaluate the effects of bowl geometry, fuel spray targeting and swirl ratio under highly diluted, low-temperature combustion conditions in a heavy-duty diesel engine. This study is used to examine aspects of low-temperature combustion that are affected by mixing processes and offers insight into the effect these processes have on emissions formation and oxidation. The foundation for this exploratory study stems from a large data set which was generated using a genetic algorithm optimization methodology. The main results suggest that an optimal combination of spray targeting, swirl ratio and bowl geometry exist to simultaneously minimize emissions formation and improve soot and CO oxidation rates. Spray targeting was found to have a significant impact on the emissions and fuel consumption performance, and was furthermore found to be the most influential design parameter explored in this study.

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.

Stoichiometric combustion could enable a three-way catalyst to be used for treating NOx emissions of diesel engines, which is one of the most difficult species for diesel engines to meet future emission regulations. Previous study by Lee et al. [1] showed that diesel engines can operate with stoichiometric combustion successfully with only a minor impact on fuel consumption. Low NOx emission levels were another advantage of stoichiometric operation according to that study. In this study, the characteristics of stoichiometric diesel combustion were evaluated experimentally to improve fuel economy as well as exhaust emissions The effects of fuel injection pressure, boost pressure, swirl, intake air temperature, combustion regime (injection timing), and engine load (fuel mass injected) were assessed under stoichiometric conditions.

High-speed video imaging in a swirl-supported (Rs = 1.7), direct-injection heavy-duty diesel engine operated with moderate-to-high EGR rates reveals a distinct correlation between the spatial distribution of luminous soot and mean flow vorticity in the horizontal plane. The temporal behavior of the experimental images, as well as the results of multi-dimensional numerical simulations, show that this soot-vorticity correlation is caused by the presence of a greater amount of soot on the windward side of the jet. The simulations indicate that while flow swirl can influence pre-ignition mixing processes as well as post-combustion soot oxidation processes, interactions between the swirl and the heat release can also influence mixing processes. Without swirl, combustion-generated gas flows influence mixing on both sides of the jet equally. In the presence of swirl, the heat release occurs on the leeward side of the fuel sprays.

Parametric tests using various EGR amounts, boost intake pressures, fueling rates, intake valve closings (IVC), injection pressures, and start-of-injection timings were executed to explore the limitations and potential of an intake valve actuation system on a heavy-duty diesel engine. At high-speed, intermediate load (56%) operation, constant airflow and no EGR, the use of late intake valve closing enabled a 70% NOx reduction while maintaining PM levels. Through an investigation using low load operation, late IVC, and reduced intake pressure, 2010 not-to-exceed NOx and PM emissions (0.25 g/kW-hr NOx, 0.02 g/kW-hr PM) were achieved with 40% EGR. At medium load, constant air flow, and early SOI, it was found that the NOx, HC and BSFC levels at a late IVC with 30%EGR were comparable to those with the stock camshaft IVC timing of 143°BTDC with 40%EGR. In comparison, the CO and PM levels decreased by nearly 70% with the use of late IVC timing and less EGR.

Sustainable PCI combustion was achieved in a light-duty diesel engine through the installation of a 120° spray angle nozzle and modeling-generated piston bowl geometry developed for compatibility with early start-of-injection timings. Experimental studies were conducted to determine favorable settings for boost pressure, SOI timing, and EGR rate at 2000 rev/min, 5 bar BMEP. An optimal SOI timing was discovered at 43° BTDC where soot and NOx emissions were reduced 89% and 86%, respectively. A 10% increase in fuel consumption was attributed to increased HC and CO emissions as well as non-optimal combustion phasing. Combustion noise was sufficiently attenuated through the use of high EGR rates. The maximum attainable load for PCI combustion was limited by the engine's peak cylinder pressure and cylinder pressure rise rate constraints.

A new search technique, called Non-Gradient Step-Controlled algorithm (NGSC), is presented. The NGSC was applied independently from pre-selected starting points and as a supplement to a Genetic Algorithm (GA) to optimize a HSDI diesel engine using split injection strategies. It is shown that the NGSC handles well the challenges of a complex response surface and factor high-dimensionality, which demonstrates its capability as an efficient and accurate tool to seek “local” convergence on complex surfaces. By directly tracking the change of a merit function, the NGSC places no requirement on response surface continuity / differentiability, and hence is more robust than gradient-dependent search techniques. The directional search mechanism takes factor interactions into consideration, and search step size control is adopted to facilitate search efficiency.