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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.

In the present work the three-dimensional KIVA CFD code was used to simulate the combustion process in a HSDI diesel engine. State-of-the-art models, including the KH-RT spray breakup model, the RNG k-ε turbulence model, and a n-heptane reduced chemistry including reduced GRI NOx mechanism were used. The performances of two combustion models, KIVA-CHEMKIN and GAMUT (KIVA-CHEMKIN-G), coupled with 2-step and multi-step phenomenological soot models were compared. The numerical results were compared with available experimental data obtained from an optically accessible HSDI engine and good agreement was obtained. To assess the effects of the in-cylinder flow field on combustion and emissions, off-centered swirl flows were also considered. In these studies, the swirl center was initialized at different positions in the chamber for different cases to simulate the effects of different intake flow arrangements.

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 newly developed turbocharging system, named MIXPC, is proposed and the performance of the proposed system applied to diesel engines is evaluated. The aim of this proposed system is to reduce the scavenging interference between cylinders, and to lower the pumping loss in cylinders and the brake specific fuel consumption. In addition, exhaust manifolds of simplified design can be constructed with small dimensions, low weight and a single turbine entry. A simulation code based on a second-order FVM+TVD (finite volume method + total variation diminishing) is developed and used to simulate engines with MIXPC. By simulating a 16V280ZJG diesel engine using the MPC turbocharging system and MIXPC, it is found that not only the average scavenging coefficient of MIXPC is larger than that of MPC, but also cylinders of MIXPC have more homogeneous scavenging coefficients than that of MPC, and the pumping loss and BSFC of MIXPC are lower than those of MPC.

An integrated system model containing sub-models for diesel engine, emissions, and aftertreatment devices has been developed. The objective is to study engine-device and device-device interactions. The emissions sub-models used are for NOx and PM (particulate matter) prediction. The aftertreatment sub-models used include a diesel oxidation catalyst (DOC) and a diesel particulate filter (DPF). Controllers have also been developed to allow for transient simulations, active DPF regeneration, and prevention/control of runaway DPF regenerations. The integrated system-level model has been used to simulate DPF regeneration via exhaust fuel injection ahead of the DOC. In addition, the controller model can use intake throttling to assist in active DPF regeneration if needed. Regeneration studies have been done for both steady engine load and with load transients. High to low engine load transients are of particular interest because they can lead to runaway DPF regeneration.

Gasoline fueled Homogeneous Charge Compression Ignition (HCCI) combustion with internal exhaust gas re-circulation using Negative Valve Overlap (NOL) was investigated by means of calculation and experiment in order to apply this technology to practical use with sufficient operating range and with acceptable emission and fuel consumption. In this paper we discuss the basic characteristics of NOL-HCCI with emphasis on the influence of intake valve timing on load range, residual gas fraction and induction air flow rate. Emission and fuel consumption under various operation conditions are also discussed. A water-cooled 250cc single cylinder engine with a direct injection system was used for this study. Three sets of valve timing were selected to investigate the effect of intake valve opening duration. Experimental results demonstrated that an engine speed of approximately 2000rpm yields an NMEP (Net Mean Effective Pressure) range from 200kPa to 400kPa.

The effects of residual gas mixing were studied in a single-cylinder, air-cooled utility engine using both external exhaust gas recirculation (EGR) and internal residual retention. EGR was introduced far upstream of the throttle to ensure proper mixing. Internal residual was changed by varying the length of the valve overlap period. EGR was measured in the intake system; the total in-cylinder diluent was directly measured using a skip-fire, cylinder dumping technique. A sweep of diluent fraction was performed at different engine speeds, engine loads, fuel mixture preparation systems, and ignition timings. An optimum level of diluent, where the combined hydrocarbon and NOx emissions were minimal, was found to exist for each operating condition. Higher levels of diluent, either through internal retention or external recirculation, caused the combined emissions to increase.

The use of low temperature combustion (LTC) modes has demonstrated abilities to lower diesel engine emissions while maintaining good fuel consumption. LTC is assumed to be a viable solution to assist in meeting stringent upcoming diesel engine emissions targets, particularly nitric oxides (NOx) and particulate matter (PM). However, LTC is currently limited to low engine loads and is not a feasible solution at higher loads on production engines. A mixed mode combustion strategy must be implemented to take advantage of the benefits offered from LTC at the low loads and speeds while switching to a conventional diesel combustion strategy at higher loads and speeds and thus allowing full range use of the engine under realistic driving conditions. Experiments were performed to characterize engine out emissions during transient engine operating conditions involving LTC combustion strategies.

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.

The scavenging process in a direct-injection two-stroke research engine was examined by using an electromagnetically controlled poppet valve to sample the trapped charge. A physical model was developed to characterize the scavenging based solely on the measured trapped gas composition. This method obviates the need to measure the post-combustion composition of the trapped charge, which significantly eases the sampling valve requirements. The valve that was developed proved to be very robust and was able to sample over 30% of the trapped mass at 3000 rpm. The measured scavenging efficiency was found to agree well with the non-isothermal two-zone perfect mixing limit of scavenging. The scavenging efficiency was found to increase with delivery ratio, and was nearly independent of speed.

This paper is a continuation of an earlier paper, which examined the steady-state internal heat transfer in the exhaust system of a diesel powered, light-duty vehicle. The present paper deals with the heat transfer of the exhaust system during two types of transient testing, as well as, the estimation of the exhaust systems external heat transfer. Transient heat transfer was evaluated using: a simple fuel-step transient under constant speed and the New European Driving Cycle (NEDC). The thermal response of the external walls varied considerably for the various components of the exhaust system. The largest percent difference between the measured temperatures and the corresponding quasi-steady estimates were about 10%, which is attributed to thermal storage. Allowing for thermal storage resulted in an excellent agreement between measurements and analysis.

A cylinder model was developed using artificial neural networks (ANN). The cylinder model utilized the trained ANN models to predict engine parameters including cylinder pressures, cylinder temperatures, cylinder wall heat transfer, NOx and soot emissions. The ANN models were trained to approximate CFD simulation results of an engine. The ANN cylinder model was then applied to predict engine performance and emissions over the standard heavy-duty FTP transient cycle. The engine responses varying over the engine speed and torque range were simulated in the course of the transient test cycle. It was demonstrated that the ANN cylinder model is capable of simulating the characteristics of the engine operating under transient conditions reasonably well.

The KIVA 3V code has been applied to predict combustion chamber heat flux in an air-cooled utility engine. The KIVA heat flux predictions were compared with experimentally measured data in the same engine over a wide range of operating conditions. The measured data were found to be approximately two times larger than the predicted results, which is attributed to the omission of chemical heat release in the near-wall region for the heat transfer model applied. Modifying the model with a simple scaling factor provided a good comparison with the measured data for the full range of engine load, heat flux sensor location, air-fuel ratio and spark timings tested. The detailed spatially resolved results of the KIVA predictions were then used to develop a simplified model of the combustion chamber temporally integrated heat flux using an artificial neural network (ANN).

A spray model for pressure-swirl atomizers that is based on a linearized instability analysis of liquid sheets has been combined with an ignition and combustion model for stratified charge spark ignition engines. The ignition model has been advanced, such that the presence of dual spark plugs can now be accounted for. Independent validation of the spray model is achieved by investigating a pressure-swirl injector inside a pressure bomb containing air at ambient temperature. In a second step, the complete model is used to estimate the performance of a small marine DISI Two-Stroke engine operating in stratified charge mode. Simulation results and experimental data are compared for several different injection timings and the agreement is generally good such that there is confidence in the predictive quality of the combustion model. Finally the model is applied in a conceptual study to investigate possible benefits of split injections.

Artificial neural networks (ANN) have been recognized as universal approximators for nonlinear continuous functions and actively applied in engine research in recent years [1, 2, 3, 4, 5, 6, 7 and 8]. This paper describes the methodology and results of using the ANN to model a turbocharged DI diesel engine. The engine was simulated using the CFD code (KIVA-ERC) over a wide range of operating conditions, and numerical simulation results were used to train the ANN. An efficient data collection methodology using the Design of Experiments (DOE) techniques was developed to select the most characteristic engine operating conditions and hence the most informative data to train the ANN. This approach minimizes the time and cost of collecting training data from either computational or experimental resources. The trained ANN was then used to predict engine parameters such as cylinder pressure, cylinder temperature, NOx and soot emissions, and cylinder heat transfer.

An experimental and numerical characterization has been conducted for high-pressure hydraulically actuated fuel injection systems. One single and one double-guided multi-hole Valve-Covered-Orifice (VCO) type injector was used with a Common Rail (CR) injection system, and two mini-sac injectors for Hydraulic electronic Unit Injection system (HEUI) were used with different orifice diameters. The purpose of the study was to explore the effects of the injection system and the operating conditions on the engine emissions for a direct injection small bore diesel engine. The diesel spray was injected into a pressurized chamber with optical access at ambient temperature. The gas density inside the chamber was representative of the density in a High Speed Direct Injection (HSDI) diesel engine at the time of injection. The experimental spray parameters included: injection pressure, injection duration, nozzle type, and nozzle diameter.

This study considers combustion processes in a heavy-duty diesel engine at various low emissions operating conditions. The start-of-injection timings varied from -20 to 5 ATDC while the EGR levels varied from 6% to 44%. At certain conditions, HCCI-like combustion characteristics were observed under which low emissions could be achieved. The numerical model used is an improved version of KIVA-3V that can simulate spray breakup and mixture autoignition over a wide range of conditions. The ignition and combustion processes were simulated using both detailed and standard (simplified) chemistry models. Model results show that engine combustion and emissions can be predicted reasonably well under the current conditions. The trends of NOx and soot emissions with respect to the injection timings and EGR levels were well captured. However, it was found that the model over-predicted the NOx emissions in certain early injection cases.

The present study uses a numerical model to investigate the effects of flow turbulence on premixed iso-octane HCCI engine combustion. Different levels of in-cylinder turbulence are generated by using different piston geometries, namely a disc-shape versus a square-shape bowl. The numerical model is based on the KIVA code which is modified to use CHEMKIN as the chemistry solver. A detailed reaction mechanism is used to simulate the fuel chemistry. It is found that turbulence has significant effects on HCCI combustion. In the current engine setup, the main effect of turbulence is to affect the wall heat transfer, and hence to change the mixture temperature which, in turn, influences the ignition timing and combustion duration. The model also predicts that the combustion duration in the square bowl case is longer than that in the disc piston case which agrees with the measurements.

An optimization study combining multidimensional CFD modeling and a global, evolutionary search technique known as the Genetic Algorithm has been carried out. The subject of this study was a 2-stroke, spark-ignited, direct-injection, single-cylinder research engine (SCRE). The goal of the study was to optimize the part load operating parameters of the engine in order to achieve the lowest possible emissions, improved fuel economy, and reduced wall heat transfer. Parameters subject to permutation in this study were the start-of-injection (SOI) timing, injection duration, spark timing, fuel injection angle, dwell between injections, and the percentage of fuel mass in the first injection pulse. The study was comprised of three cases. All simulations were for a part load, intermediate-speed condition representing a transition operating regime between stratified charge and homogeneous charge operation.

A radiation model based on the Discrete Ordinates Method (DOM) was incorporated into the KIVA3v multidimensional code to study the effects of soot and radiation on diesel engine performance at high load. A thermophoretic soot deposition model was implemented to predict soot concentrations in the near-wall region, which was found to affect radiative heat flux levels. Realistic, non-uniform combustion chamber wall surface temperature distributions were predicted using a finite-element-based heat conduction model for the engine metal components that was coupled with KIVA3v in an iterative scheme. The more accurate combustion chamber wall temperatures enhanced the accuracy of both the radiation and soot deposition models as well as the convective heat transfer model. For a basline case, (1500 rev/min, 100% load) it was found that radiation can account for as much as 30% of the total wall heat loss and that soot deposition in each cycle is less than 3% of the total in-cylinder soot.