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This paper will discuss the fundamentals of the Bosch rate of injection meter which has been the standard measurement tool for the last 25 years and a newly developed tool which uses the Zuech constant volume technique. A fundamental and experimental comparison is presented. Using a high pressure accumulator type injector, each of the injection systems produced almost identical injection rate shapes. The integrated values of these traces (injection quantity) were within a few percent of the physically measured quantities.

Multi-dimensional computational efforts using comprehensive and skeletal kinetics have been made to investigate the cool flame region in HCCI combustion. The work was done in parallel to an experimental study that showed the impact of the negative temperature coefficient and the cool flame on the start of combustion using different fuels, which is now the focus of the simulation work. Experiments in a single cylinder CFR research engine with n-butane and a primary reference fuel with an octane number of 70 (PRF 70) were modeled. A comparison of the pressure and heat release traces of the experimental and computational results shows the difficulties in predicting the heat release in the cool flame region. The behavior of the driving radicals for two-stage ignition is studied and is compared to the behavior for a single-ignition from the literature. Model results show that PRF 70 exhibits more pronounced cool flame heat release than n-butane.

A procedure has been developed to build system level predictive models that incorporate physical laws as well as information derived from experimental data. In particular a soot model was developed, trained and tested using experimental data. It was seen that the model could fit available experimental data given sufficient training time. Future accuracy on data points not encountered during training was estimated and seen to be good. The approach relies on the physical phenomena predicted by an existing system level phenomenological soot model coupled with ‘weights’ which use experimental data to adjust the predicted physical sub-model parameters to fit the data. This approach has developed from attempts at incorporating physical phenomena into neural networks for predicting emissions. Model training uses neural network training concepts.

A single cylinder CFR research engine has been run in HCCI combustion mode for a range of temperatures and fuel compositions. The data indicate that the best HCCI operation, as measured by a combination of successful combustion with low ISFC, occurs at or near the rich limit of operation. Analysis of the pressure and heat release histories indicated the presence, or absence, and impact of the fuel's NTC ignition behavior on establishing successful HCCI operation. The auto-ignition trends observed were in complete agreement with previous results found in the literature. Furthermore, analysis of the importance of the fuel's octane sensitivity, through assessment of an octane index, successfully explained the changes in the fuels auto-ignition tendency with changes in engine operating conditions.

A series of engine experiments have been performed to explore the impact intake temperature, engine speed and fuel composition on the HCCI operating range of a CFR engine. The experimental matrix covers a range of engine speeds 600 - 2000 RPM), intake temperatures (300 K - 400 K), and four different fuels. Three of the fuels had different chemical composition but had equivalent research octane numbers of 91.8. The fourth fuel, a blend of primary reference fuels had a research octane number of 70. The acceptable HCCI operating range of the engine was defined through two criteria; the rate of pressure rise needed to be less than 10 MPa per crank angle and the covariance of the indicated mean effective pressure needed to be less than 10 percent. Using these limits the HCCI operating range for the engine was evaluated for the experimental matrix. Data for emissions, and fuel consumption as well as in-cylinder pressure were recorded.

The applicability of several popular diesel particulate matter (PM) measurement techniques to low temperature combustion is examined. The instruments' performance in measuring low levels of PM from advanced diesel combustion is evaluated. Preliminary emissions optimization of a high-speed light-duty diesel engine was performed for two conventional and two advanced low temperature combustion engine cases. A low PM (<0.2 g/kg_fuel) and NOx (<0.07 g/kg_fuel) advanced low temperature combustion (LTC) condition with high levels of exhaust gas recirculation (EGR) and early injection timing was chosen as a baseline. The three other cases were selected by varying engine load, injection timing, injection pressure, and EGR mass fraction. All engine conditions were run with ultra-low sulfur diesel fuel. An extensive characterization of PM from these engine operating conditions is presented.

In current systems, for a given nozzle and injection pressure (pump speed), the shape of the injection rate is fixed and the injection timing is the only variable the engine designer can vary. For this non-interactive injection system, changing the injector nozzle (number and diameter of holes) will proportionately change the injection shape. New injection systems in which the rate of injection is a controlled variable are being developed. Results from one such injector, called the UCORS (Universal Combustion Optimization and Rate Shaping), are reported in this paper. The system can dynamically control its injection rate shape by controlling the position and size of a pilot injection relative to the main injection. Data and analysis from an out-of-engine and combustion chamber study of the UCORS injection system are presented.

Three distinct types of diesel particulate matter (PM) are generated in selected engine operating conditions of a single-cylinder heavy-duty diesel engine. The three types of PM are trapped using typical Cordierite diesel particulate filters (DPF) with different washcoat formulations and a commercial Silicon-Carbide DPF. Two systems, an external electric furnace and an in-situ burner, were used for regeneration. Furnace regeneration experiments allow the collected PM to be classified into two categories depending on oxidation mechanism: PM that is affected by the catalyst and PM that is oxidized by a purely thermal mechanism. The two PM categories prove to contribute differently to pressure drop and transient filtration efficiency during in-situ regeneration.

An experimental study was performed to investigate diesel particulate filter (DPF) performance during filtration with the use of real-time measurement equipment. Three operating conditions of a single-cylinder 2.3-liter D.I. heavy-duty diesel engine were selected to generate distinct types of diesel particulate matter (PM) in terms of chemical composition, concentration, and size distribution. Four substrates, with a range of geometric and physical parameters, were studied to observe the effect on filtration characteristics. Real-time filtration performance indicators such as pressure drop and filtration efficiency were investigated using real-time PM size distribution and a mass analyzer. Types of filtration efficiency included: mass-based, number-based, and fractional (based on particle diameter). In addition, time integrated measurements were taken with a Rupprecht & Patashnick Tapered Element Oscillating Microbalance (TEOM), Teflon and quartz filters.

The objective of this research is a detailed investigation of unburned hydrocarbon (UHC) in a highly-dilute diesel low temperature combustion (LTC) regime. This research concentrates on understanding the mechanisms that control the formation of UHC via experiments and simulations in a 0.48L signal-cylinder light duty engine operating at 2000 r/min and 5.5 bar IMEP with multiple injections. A multi-gas FTIR along with other gas and smoke emissions instruments are used to measure exhaust UHC species and other emissions. Controlled experiments in the single-cylinder engine are then combined with three computational tools, namely heat release analysis of measured cylinder pressure, analysis of spray trajectory with a phenomenological spray model using in-cylinder thermodynamics [1], and KIVA-3V Chemkin CFD computations recently tested at LTC conditions [2].

A two dimensional CFD model has been developed to study the mechanism of soot deposition on the porous wall surface in a Diesel Particulate Filter (DPF). The goal is to improve understanding of the soot deposition and its interaction with the hydrodynamic behaviour of the device. The KIVA3V CFD code and pre-processor were modified to simulate a single channel in a DPF. The code was extended to solve the conservation equations in porous media materials, to account for the sticking of particles on a porous surface and to evaluate the increasing resistance to the flow as the soot inside the trap accumulates. The code is already configured to track Lagrangian particles and these were modified to represent the soot particles in the flow. The code pre-processor was modified to allow definition of a double-symmetric geometry and to specify porous cells.

A Soot-NOx Trap (SNT) is a combinatorial aftertreatment device intended to decrease both particulate and NOx emissions simultaneously. A system-level Soot-NOx Trap model was developed by adding Lean NOx Trap kinetics to a 1D Diesel Particulate Filter model. The hybrid model was validated against each parent model for the limiting cases, then exercised to investigate the interacting redox behavior. Modulations in temperature and exhaust air-fuel ratio were investigated for their ability to facilitate particulate oxidation and NOx reduction in the trap.

The development of the Diesel Exhaust Filtration Analysis system (DEFA), which utilizes a rectangular wafer of the same substrate material as used in a full-scale Diesel Particulate Filter (DPF), is presented in this paper. Washcoat variations of the wafer substrate (bare, washcoat, and catalyzed washcoat) were available for testing. With this setup, the complications of flow and temperature distribution that arise in the full-scale DPF can be significantly minimized while critical parameters that affect the filtration performance can be fully controlled. Cold flow experiments were performed to test the system's reliability, and determine the permeability of each wafer type. A Computational Fluid Dynamics (CFD) package was utilized to ensure the flow uniformity inside the filter holder during the cold flow test.

Three Cordierite diesel particulate filters (DPF) with variations in the washcoat† (bare, washcoat-only, and catalyzed washcoat) were filled with equal amounts of PM (∼2 g/l) from a single steady-state engine operating condition (30% load, 1800 rpm). Two regeneration systems were used: an electrical furnace to extract the kinetic parameters by performing Temperature Programmed Oxidation (TPO) experiments and an inline burner to study how DPF washcoat variations affect active regeneration performance. Detailed emissions measurements were performed upstream and downstream of the DPF during the filtration and regeneration processes to quantify DPF filtration and regeneration performance. These measurements included gaseous emission, PM mass concentration, and particle size distribution.

Low pressure EGR offers greater effectiveness and flexibility for turbocharging and improved heat transfer compared to high pressure EGR systems. These characteristics have been shown to provide potential for further NOx, soot, and fuel consumption reductions in modern diesel engines. One of the drawbacks is reduced transient response capability due to the long EGR path. This can be largely mitigated by combining low pressure and high pressure loops in a hybrid EGR system, but the changes in transient response must be considered in the design of an effective control strategy. The effect of low pressure EGR on transient emissions was evaluated using two different combustion strategies over a variety of transient events. Low pressure EGR was found to significantly lengthen the response time of intake oxygen concentration following a transient event, which can have a substantial effect on emissions formation.

The light-medium load operating range (4-7 bar net IMEP) presents many challenges for advanced low temperature combustion strategies utilizing low cetane fuels (specifically, 87-octane gasoline) in light-duty, high-speed engines. The overly lean overall air-fuel ratio (Φ≺0.4) sometimes requires unrealistically high inlet temperatures and/or high inlet boost conditions to initiate autoignition at engine speeds in excess of 1500 RPM. The objective of this work is to identify and quantify the effects of variation in input parameters on overall engine operation. Input parameters including inlet temperature, inlet pressure, injection timing/duration, injection pressure, and engine speed were varied in a ~0.5L single-cylinder engine based on a production General Motors 1.9L 4-cylinder high-speed diesel engine.

The light-medium load operating regime (4-8 bar net IMEP) presents many challenges for advanced low temperature combustion strategies (e.g. HCCI, PPC) in light-duty, high speed engines. In this operating regime, lean global equivalence ratios (Φ<0.4) present challenges with respect to autoignition of gasoline-like fuels. Considering this intake temperature sensitivity, the objective of this work was to investigate, both experimentally and computationally, gasoline compression ignition (GCI) combustion operating sensitivity to inlet swirl ratio (Rs) variations when using a single fuel (87-octane gasoline) in a 0.475-liter single-cylinder engine based on a production GM 1.9-liter high speed diesel engine. For the first part of this investigation, an experimental matrix was developed to determine how changing inlet swirl affected GCI operation at various fixed load and engine speed operating conditions (4 and 8 bar net IMEP; 1300 and 2000 RPM).

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.

An overall diesel engine and aftertreatment system model has been created that integrates diesel engine, exhaust system, engine emissions, and diesel particulate filter (DPF) models using MATLAB Simulink. The 1-D engine and exhaust system models were developed using WAVE. The engine emissions model combines a phenomenological soot model with artificial neural networks to predict engine out soot emissions. Experimental data from a light-duty diesel engine was used to calibrate both the engine and engine emissions models. The DPF model predicts the behavior of a clean and particulate-loaded catalyzed wall-flow filter. Experimental data was used to validate this sub-model individually. Several model integration issues were identified and addressed. These included time-step selection, continuous vs. limited triggering of sub-models, and code structuring for simulation speed. Required time-steps for different sub models varied by orders of magnitude.

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.