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A kinetic carbon monoxide (CO) emission model is developed to simulate engine out CO emissions for conventional diesel combustion. The model also incorporates physics governing CO emissions for low temperature combustion (LTC). The emission model will be used in an integrated system level model to simulate the operation and interaction of conventional and low temperature diesel combustion with aftertreatment devices. The Integrated System Model consists of component models for the diesel engine, engine-out emissions (such as NOx and Particulate Matter), and aftertreatment devices (such as DOC and DPF). The addition of CO emissions model will enhance the capability of the Integrated System Model to predict major emission species, especially for low temperature combustion. In this work a CO emission model is developed based on a two-step global kinetic mechanism [8].

Two different types of mesh used for diesel combustion with the KIVA-4 code are compared. One is a well established conventional KIVA-3 type polar mesh. The other is a non-polar mesh with uniform size throughout the piston bowl so as to reduce the number of cells and to improve the quality of the cell shapes around the cylinder axis which can contain many fuel droplets that affect prediction accuracy and the computational time. This mesh is specialized for the KIVA-4 code which employs an unstructured mesh. To prevent dramatic changes in spray penetration caused by the difference in cell size between the two types of mesh, a recently developed spray model which reduces mesh dependency of the droplet behavior has been implemented. For the ignition and combustion models, the Shell model and characteristic time combustion (CTC) model are employed.

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.

Fuel-air mixing in a direct-injection SI engine was studied to further improve full-load torque output. The fuel-injection location of DI vs. PFI results in different heat sources for fuel evaporation, hence a DI engine has been found to exhibit higher volumetric efficiency and lower knocking tendency, resulting in higher full-load torque output [1]. The ability to change injection timing of the DI engine affects heat transfer and mixture temperature, hence later injection results in lower knocking tendency. Both the higher volumetric efficiency and the lower knocking tendency can improve engine torque output. Improving volumetric efficiency requires that the fuel is injected during the intake stroke. Reducing knocking tendency, in contrast, requires that the fuel is injected late during the compression stroke. Thus, a strategy of split injection was proposed to compromise the two competing requirements and further increase direct-injection SI engine torque output.

A super-microcomputer is utilized in an engine-dynamometer facility to create a comprehensive engine evaluation system. A unique feature of this system is the combination of experimental and modelling activities in evaluating engine designs. The system acquires engine operating conditions, emissions, and dynamic cylinder and manifold pressures via the data acquisition interface. After acquisition, the computer is also capable of providing engine model predictions from either an empirical model or a zero-dimensional thermodynamic model. The data gathering process is speed limited by the settling time of the engine-dynamometer system. The acquisition and modelling procedures are controlled by an internally developed, menu driven, software package. Features of the system include commercial relational database software for rapid storage and retrieval of acquired data and a high resolution graphics monitor for immediate display of analyzed pressure data.

Two turbulent combustion modeling approaches, which were large eddy simulations in conjunction with detailed kinetics (LES-CHEMKIN) and Reynolds Averaged Navier Stokes with detailed kinetics (RANS-CHEMKIN), were used to model two partially premixed engine conditions. The results were compared with average pressure and heat release data, as well as images of in-cylinder ignition chemiluminescence and OH radical distributions. Both LES-CHEMKIN and RANS-CHEMKIN match well with experimental average data. However, LES-CHEMKIN has advantages over RANS-CHEMKIN in predicting the details of location of ignition sites, temperature as well as OH radical distributions. Therefore, LES offers more realistic representations of the combustion process. As a further improvement aiming at saving computational cost and accounting for turbulence-chemistry interactions, a flamelet time scale (FTS) combustion model is coupled with CHEMKIN to predict the entire combustion process. In this new approach (i.e.

A general combustion model, in the context of large eddy simulations, was developed to simulate the full range of combustion in conventional diesel-type and HCCI-type diesels. The combustion model consisted of a Chemkin sub-model and an Extended Flamelet Time Scale (EFTS) sub-model. Specifically, Chemkin was used to simulate auto-ignition process. In the post-ignition phase, the combustion model was switched to EFTS. In the EFTS sub-model, combustion was assumed to be a combination of two elementary combustion modes: homogeneous combustion and flamelet combustion. The combustion index acted as a weighting factor blending the contributions from these two modes. The Chemkin sub-model neglected the subgrid scale turbulence-chemistry interactions whereas the EFTS model took them into account through a presumed PDF approach. The model was used to simulate an early injection mode of a Cummins DI diesel engine and a mode of a Caterpillar DI diesel engine.

An experimental study was carried out to investigate the effects of fuel injection timing on the spatial and temporal development of injected fuel sprays within a firing direct-injection spark-ignition (DISI) engine. It was found that the structure of the injected fuel sprays varied significantly with the timing of the injection event. During the induction stroke and the early part of the compression stroke, the development of the injected fuel sprays was shown to be controlled by the state of the intake and intake-generated gas flows at the start of injection (SOI).The relative influence of these two flow regimes on the injected fuel sprays during this period was also observed to change with injection timing, directly affecting tip penetration, spray/wall impingement and air-fuel mixing. Later in the compression stroke, the results show the development of the injected fuel sprays to be dominated by the increased cylinder pressure at SOI.

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.

System-level models containing engine model, emission models, and aftertreatment device models have been developed. All the sub-models have been developed separately and come from a variety of different sources. A new phenomenological CO model recently has been coupled into the previous integrated model. The emission models, including PM (particulate matter), NOx, and CO are also calibrated from experimental data. Some modification has been added to improve the integrated model and accept different aftertreatment device models for future work. The objective of this work is to study the DPF (Diesel Particulate Filter) regeneration during transient operating conditions using the integrated model. The integrated system-level model is used to studying the dynamic performance between engine and aftertreatment system. In this study, the calibrated emission models are validated at transient operating conditions.

This work integrated a CA10 (crank angle at 10% heat release) controller into an integrated engine, emissions and aftertreatment model platform. Two CA10 phasing targets were chosen to analyze how advancing (or retarding) the target combustion phasing (CA10) affect the formation of NO and CO. The effect of intake valve closure (IVC) timing, which is the control mechanism for maintaining the target combustion phasing, on the cylinder trapped mass, and hence the charge temperature after compression is detailed. Finally, the relation between combustion phasing and the blow-down process leading to the exhaust process is discussed. Retarding the target combustion phasing by two degrees saw a 330 K drop in compressed charge temperature and a quadrupled reduction of peak NO emitted. Peak NO₂ emission reduced three times on account of the same. However, an increase in CO emission was observed when the combustion phasing was advanced.

This article presents nondestructive neutron computed tomography (nCT) measurements of Diesel Particulate Filters (DPFs) as a method to measure ash and soot loading in the filters. Uncatalyzed and unwashcoated 200cpsi cordierite DPFs exposed to 100% biodiesel (B100) exhaust and conventional ultra low sulfur 2007 certification diesel (ULSD) exhaust at one speed-load point (1500 rpm, 2.6 bar BMEP) are compared to a brand new (never exposed) filter. Precise structural information about the substrate as well as an attempt to quantify soot and ash loading in the channel of the DPF illustrates the potential strength of the neutron imaging technique.

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.

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.

A modeling study has been conducted in order to characterize the heat transfer in an automotive diesel exhaust system. The exhaust system model, focusing on 2 exhaust pipes, has been created using a transient 1-D engine flow network simulation program. Model results are in excellent agreement with experimental data gathered before commencement of the modeling study. Predicted pipe exit stream temperatures are generally within one percent of experimental values. Sensitivity analysis of the model was the major focus of this study. Four separate variables were chosen for the sensitivity analysis. These being the external convective heat transfer coefficient, external emissivity, mass flow rate of exhaust gases, and amplitude of incoming pressure fluctuations. These variables were independently studied to determine their contribution to changes in exhaust gas stream temperature and system heat flux. There are two primary benefits obtained from conducting this analysis.

A fiber optic infrared spectroscopic sensor was developed to measure the crank angle resolved residual fraction of burned gas retained in the cylinder of a four-stroke SI engine. The sensor detected the attenuation of infrared radiation in the 4.3 μm infrared vibrational-rotational absorption band of CO2. The residual fraction remaining in the cylinder is proportional to the CO2 concentration. The sensor was tested in a single-cylinder CFR spark ignition engine fired on propane at a speed of 700 rpm. The sensor was located in one of two spark plug holes of the CFR engine. A pressure-transducer-type spark plug was used to record the cylinder pressure and initiate the spark. The temporal resolution of the measurements was 540 μs (equivalent to 2.3 crank angle degrees) and the spatial resolution was 6 mm. Measurements were made during the intake and compression stroke for several intake manifold pressures. The compression ratio of the engine was varied from 6.3 to 9.5.

This paper presents results from a comprehensive experimental study of high-pressure pressure-swirl gasoline injectors tested under a range of simulated operating conditions. This study encompassed photographic analysis of single spray sequences and simultaneous measurement of axial velocity, radial velocity and diameter at point locations using the phase-doppler technique. The combination of these measurement techniques permitted an insight into the fluid dynamics of the injected spray and its development with time. Five primary stages in the spray-history were identified and numerated with experimental data.