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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.

System level modeling was used to develop a suitable control strategy for Diesel Homogeneous Charge Compression Ignition (HCCI) transient operation. Intake temperature and pressure, engine speed, engine load, cylinder wall temperature, exhaust gas recirculation, etc. all significantly affect combustion phasing generating a scenario where simple ECU mapping techniques prove inadequate. Two-stage fuels such as diesel fuel pose additional challenges for accurate combustion control. Low-temperature cool-flame chemical heat release can significantly alter the thermodynamic state of the trapped gaseous mixture and hence combustion phasing. Operator and environmentally induced transients can rapidly alter combustion phasing parameters suggesting a need for model-based control. A model-based control strategy featuring the identified essential physics has been developed to control diesel HCCI combustion phasing through transient operation.

An integrated system model containing sub-models for a multi-cylinder diesel engine, NOx and soot(PM) emissions, diesel oxidation catalyst (DOC) and diesel particulate filter (DPF) has been developed to simulate the engine and aftertreatment systems at transient engine operating conditions. The objective of this work is two-fold; ensure correct implementation of the integrated system level model and apply the integrated model to understand the fuel economy trade-off for various DPF regeneration strategies. The current study focuses on a 1.9L turbocharged diesel engine and its exhaust system. The engine model was built in GT-Power and validated against experimental data at full-load conditions. The DPF model is calibrated for the current engine application by matching the clean DPF pressure drop for different mass flow rates. Load, boost pressure, speed and EGR controllers are tuned and linked with the current engine model.

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.

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.

A comprehensive system level modeling approach is used to understand the effects of the various physical actuators during diesel HCCI transients. Control concepts during transient operations are simulated using a set of actuators suitable for combustion control in diesel HCCI engines (intake valve actuation, injection timing, cooled EGR, intake boost pressure and droplet size). The impact of these actuating techniques on the overall engine performance is quantified by investigating the amount of actuation required, timing of actuation and the use of a combination of actuators. Combined actuation improved actuation space that can be used to phase combustion timing better and in extending the operating range. The results from transient simulations indicate that diesel HCCI operation would benefit from the combined actuation of intake valve closure, injection timing, boost and cooled EGR.

The three-dimensional CFD codes KIVA-II and KIVA-3 have been used together to study the effects of intake generated in-cylinder flow structure on fuel-air mixing and combustion in a direct injected (DI) Diesel engine. In order to more accurately account for the effect of intake flow on in-cylinder processes, the KIVA-II code has been modified to allow for the use of data from other CFD codes as initial conditions. Simulation of the intake and compression strokes in a heavy-duty four-stroke DI Diesel engine has been carried out using KIVA-3. Flow quantities and thermodynamic field information were then mapped into a computational grid in KIVA-II for use in the study of mixing and combustion. A laminar and turbulent timescale combustion model, as well as advanced spray models, including wave breakup atomization, dynamic drop drag, and spray-wall interaction has been used in KIVA-II.

Previous studies have shown the importance of the in-cylinder flow field which exists prior to fuel injection on performance and emissions behavior of direct injected (DI) diesel engines. Key parameters in the flow field are the turbulence level and the resolved structures, such as swirl and tumble flow. These characteristics are known to have significant effects on the fuel vaporization, droplet break-up, and fuel-air mixing. The relative importance of these effects is investigated through simulation of injection into a stirred, heated, constant volume combustion bomb, using the computational fluid dynamics codes KIVA-3 [9] and KIVA-II [10]. Initial conditions for these simulations are based on in-cylinder conditions which exist in a heavy duty DI diesel engine immediately prior to fuel injection.

Early direct injection with HCCI like properties is characterized by the presence of an ignition dwell - the interval between end of fuel injection and start of combustion, during which fuel-air mixing occurs. Previous work by Jhavar and Rutland (2005) has focused on investigating different methods to affect fuel-air mixing during the ignition dwell. That study helped to evaluate the relative influence of various mixing control strategies to achieve ignition control. In this study, we attempt to look into the mixture preparation process in more detail. Therefore, turbulence is studied using Large Eddy Simulation (LES) models in place of Reynolds Averaged Navier Stokes (RANS) models. While LES is computationally more expensive than RANS, it depicts the flow structure more accurately. Therefore, it can be applied to engines in order to gain a better representation of local mixing as well as accurately simulate unsteady flow behavior in engines.

An approach to accurately capture overall behavior in a system level model of DI Diesel HCCI engine operation is presented. The modeling methodology is an improvement over the previous effort [36], where a multi-zone model with detailed chemical kinetics was coupled with an engine cycle simulation code. This multi-zone technique was found to be inadequate in capturing the fuel spray dynamics and its impact on mixing. An improved methodology is presented in this paper that can be used to model fully and partially premixed charge compression ignition engines. A Computational Fluid Dynamics (CFD) driven model is used where the effects of fuel injection, spray evolution, evaporation, and turbulent mixing are considered. The modeling approach is based on the premise that once the initial spray dynamics are correctly captured, the overall engine predictions during the combustion process can be captured with good accuracy.

An integrated system based modeling approach has been developed to understand early Direct Injection (DI) Diesel Homogeneous Charge Compression Ignition (HCCI) process. GT-Power, a commercial one-dimensional (1-D) engine cycle code has been coupled with an external cylinder model which incorporates sub-models for fuel injection, vaporization, detailed chemistry calculations (Chemkin), heat transfer, energy conservation and species conservation. In order to improve the modeling accuracy, a multi-zone model has been implemented to account for temperature and fuel stratifications in the cylinder charge. The predictions from the coupled simulation have been compared with experimental data from a single cylinder Caterpillar truck engine modified for Diesel HCCI operation. A parametric study is conducted to examine the effect of combustion timing on four major control parameters. Overall the results show good agreement of the trends between the experiments and model predictions.

Ignition dwell is defined as the interval between end of fuel injection and start of combustion in early injection diesel combustion that exhibits HCCI-like characteristics. In this project, the impact of in-cylinder temperature and fuel-air mixing on the ignition dwell was investigated. The engine cycle was simulated using the 3-D CFD code KIVA-3V. Work done by Klingbeil (2002) has shown that ignition dwell allows more time for fuel and air to mix and drastically reduces emissions of NOX and particulate matter. Temperature is known to have a direct impact on the duration of ignition dwell. However, initial fuel-air distribution and mixing (i.e. at the end of fuel injection) may also impact the duration of ignition dwell. To investigate this, variations in EGR, fuel injection timing, engine valve actuation and swirl were simulated. The aim was to use these techniques to generate varying levels of fuel-air mixing and to check if ignition dwell was affected.