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Precise cycle-to-cycle control of combustion is the major challenge to reduce fuel consumption in Homogenous Charge Compression Ignition (HCCI) engines, while maintaining low emission levels. This paper outlines a framework for simultaneous control of HCCI combustion phasing and Indicated Mean Effective Pressure (IMEP) on a cycle-to-cycle basis. A dynamic control model is extended to predict behavior of HCCI engine by capturing main physical processes through an HCCI engine cycle. Performance of the model is validated by comparison with the experimental data from a single cylinder Ricardo engine. For 60 different steady state and transient HCCI conditions, the model predicts the combustion phasing and IMEP with average errors less than 1.4 CAD and 0.2 bar respectively. A two-input two-output controller is designed to control combustion phasing and IMEP by adjusting fuel equivalence ratio and blending ratio of two Primary Reference Fuels (PRFs).

The fluid flow characteristics inside compound silicon micro machined port fuel injector nozzles were analyzed through the use of computational fluid dynamics (CFD). This study was undertaken in order to gain a better understanding of the fluid mechanics taking place in the compound orifice plate. In addition, the calculated computational results will be used to predict the fuel spray patterns and sauter mean diameters of the sprays. The influence of orifice plate geometry on calculated turbulent kinetic energies and fuel spray patterns was also studied and will be discussed. The results of this investigation indicate that the fluid flow characteristics inside the compound silicon micro machined port fuel injector nozzle are influenced by the geometries of the compound orifice plate, and that the flow characteristic inside the orifice plate effect the type of spray produced by the injector.

A study was undertaken to investigate the affect of exhaust gas recirculation (EGR) on engine wear and lubricating oil degradation in a heavy duty diesel engine using a newly developed methodology that uses analytical ferrography in conjunction with short term tests. Laboratory engine testing was carried out on a Cummins NTC-300 Big Cam II diesel engine at rated speed (1800 RPM) and 75% rated load with EGR rates of 0, 5, and 15% using a SAE 15W40 CD/SF/EO-K oil. Dynamometer engine testing involved collecting oil samples from the engine sump at specified time intervals through each engine test. These oil samples were analyzed using a number of different oil analysis techniques that provide information on the metal wear debris and also on the lubricating oil properties. The results from these oil analysis techniques are the basis of determining the effect of EGR on engine wear and lubricating oil degradation, rather than an actual engine tear down between engine tests.

This study examines the feasibility of broadening the fuel capabilities of a direct-injected two-stroke engine with stratified combustion. A three cylinder, direct-injected two-stroke engine was modified to operate on JP-5, a kerosene-based jet fuel that is heavier, more viscous, and less volatile than gasoline. Demonstration of engine operation with such a fuel after appropriate design modifications would significantly enhance the utilization of this engine in a variety of applications. Results have indicated that the performance characteristics of this engine with jet fuel are similar to that of gasoline with respect to torque and power output at low speeds and loads, but the engine's performance is hampered at the higher speeds and loads by the occurrence of knock.

The U.S. Bureau of Mines and Michigan Technological University are collaborating to conduct laboratory evaluations of oxidation catalytic converters (OCCs) and diesel fuels to identify combinations which minimize potentially harmful emissions. The purpose is to provide technical information concerning diesel exhaust emission control to the mining industry, regulators, and vendors of fuel and emission control devices. In this study, an Engelhard PTX 10 DVC (Ultra-10)* OCC was evaluated in the exhaust stream of an indirect injection Caterpillar 3304 PCNA mining engine using a light-duty laboratory transient cycle. This cycle was selected because it causes high emissions of particle-associated organics. Results are also reported for two different fuels with similar sulfur contents (0.03-0.04 wt pct) and a cetane number of 53, but different aromatic contents (11 vs. 20 wt pct).

Exhaust gas recirculation (EGR) has been employed in a diesel engine to reduce NOx emissions by diluting the fresh air charge with gases composed of primarily N2, CO2, H2O, and O2 from the engines exhaust stream. The addition of EGR reduces the production of NOx by lowering the peak cylinder gas temperature and reducing the concentration of O2 molecules, both of which contribute to the NOx formation mechanism. The amount of EGR has been typically controlled using an open loop control strategy where the flow of EGR was calibrated to the engine speed and load and controlled by the combination of an EGR valve and the ratio of the boost and exhaust back pressures. When oxygenated biofuels with lower specific energy are used, the engine control unit (ECU) will demand a higher fuel rate to maintain power output, which can alter the volumetric flow rate of EGR. In addition, oxygenated biofuels affect the oxygen concentration in the intake manifold gas stream.

A computer simulation model to predict the thermal responses of an on-highway heavy duty diesel truck in transient operation was used to study several important cooling system design and operating variables. The truck used in this study was an International Harvester COF-9670 cab-over-chassis vehicle equipped with a McCord radiator, Cummins NTC-350 diesel engine, Kysor fan-clutch and shutter system, aftercooler, and standard cab heater and cooling system components. Input data from several portions of a Columbus to Bloomington, Indiana route were used from the Vehicle Mission Simulation (VMS) program to determine engine and vehicle operating conditions for the computer simulation model. The thermostat-fan, thermostat-shutter-fan, and thermostat-winterfront-fan systems were studied.

The effect of truck dieselization for three levels of diesel penetration into each of the eight classes of trucks is modeled. Diesel and total truck sales, population, mileage and yearly fuel usage data are aggregated by four truck classes representing light, medium, light-heavy and heavy-heavy classes. Four fuel economy scenario's for different technological improvements were studied. Improvement of fuel economy for light and heavy-heavy duty vehicle classes provides significant total fuel savings. Truck dieselization of light and light-heavy duty vehicle classes provides the largest improvement of fuel usage due to the fact that they have large numbers of vehicles and presently have few diesels. Total car and truck fuel usage in the 1980's shows roughly a constant demand with cars decreasing due to improved new fleet fuel economy and trucks increasing due to a larger population with better fuel economy due to dieselization and improved technology.

This paper covers the development of Ferrographic oil analysis techniques for the study of diesel engine wear. A brief overview of the various wear analysis techniques now commonly used in laboratory and field engine wear studies is discussed. Also included in this paper is an in depth description of the Ferrographic oil analysis techniques and the various applications of the techniques to the study of engine wear. A comparison of the commonly used wear measurement methods, Ferrography, spectroscopy and the radioactive tracer methods, and their abilities to measure wear is also discussed. A direct injection, 4-cycle, turbocharged diesel engine was used in the testing and data are presented indicating the abilities of the Ferrographic oil analysis techniques to detect changes in wear rates. The effects of operating time on engine oil and the effects of the variation of oil and coolant temperatures on engine wear is presented.

The ability to operate a spark-ignition (SI) engine near the knock limit provides a net reduction of engine fuel consumption. This work presents a real-time knock control system based on stochastic knock detection (SKD) algorithm. The real-time stochastic knock control (SKC) system is developed in MATLAB Simulink, and the SKC software is integrated with the production engine control strategy through ATI's No-Hooks. The SKC system collects the stochastic knock information and estimates the knock level based on the distribution of knock intensities fitting to a log-normal (LN) distribution. A desired knock level reference table is created under various engine speeds and loads, which allows the SKC to adapt to changing engine operating conditions. In SKC system, knock factor (KF) is an indicator of the knock intensity level. The KF is estimated by a weighted discrete FIR filter in real-time.

This paper presents the development of a Stochastic Knock Detection (SKD) method for combustion knock detection in a spark-ignition engine using a model based design approach. The SKD set consists of a Knock Signal Simulator (KSS) as the plant model for the engine and a Knock Detection Module (KDM). The KSS as the plant model for the engine generates cycle-to-cycle accelerometer knock intensities following a stochastic approach with intensities that are generated using a Monte Carlo method from a lognormal distribution whose parameters have been predetermined from engine tests and dependent upon spark-timing, engine speed and load. The lognormal distribution has been shown to be a good approximation to the distribution of measured knock intensities over a range of engine conditions and spark-timings for multiple engines in previous studies.

This investigation focuses on conventional powertrain technologies that provide operational synergy based on customer utilization to reduce fuel consumption for a heavy-duty, nonroad (off-road) material handler. The vehicle of interest is a Pettibone Cary-Lift 204i, with a base weight of 50,000 lbs. and a lift capacity of 20,000 lbs. The conventional powertrain consists of a US Tier 4 Final diesel engine, a non-lockup torque converter, a four-speed powershift automatic transmission, and all-wheel drive. The paper will present a base vehicle energy/fuel consumption breakdown of propulsion, hydraulic and idle distribution based on a representative end-user drive cycle. The baseline vehicle test data was then used to develop a correlated lumped parameter model of the vehicle-powertrain-hydraulic system that can be used to explore technology integration that can reduce fuel consumption.

Energy management is one of the key challenges for the development of Hybrid Electric Vehicle (HEV) due to its complex powertrain structure. Hardware-In-the-Loop (HIL) simulation provides an open software architecture which enables rapid prototyping HEV energy management system. This paper presents the investigation of the energy management system for a single shaft parallel hybrid electric vehicle using dSPACE eDrive HIL system. The parallel hybrid electric vehicle, energy management system, and low-level Electronic Control Unit (ECU) were modeled using dSPACE Automotive Simulation Models and dSPACE blocksets. Vehicle energy management is achieved by a vehicle-level controller called hybrid ECU, which controls vehicle operation mode and torque distribution among Internal Combustion Engine (ICE) and electric motor. The individual powertrain components such as ICE, electric motor, and transmission are controlled by low-level ECUs.

This paper studies model predictive control algorithm for Hybrid Electric Vehicle (HEV) energy management to improve HEV fuel economy. In this paper, Model Predictive Control (MPC), a predictive control method, is applied to improve the fuel economy of power-split HEV. A dedicated model predictive control method is developed to predict vehicle speed, battery state of charge (SOC), and engine fuel consumption. The power output from the engine, motor, and the mechanical brake will be adjusted to match driver's power request at the end of the prediction window while minimizing fuel consumption. The controller model is built on Matlab® MPC toolbox® and the simulations are based on MY04 Prius vehicle model using Autonomie®, a powertrain and fuel economy analysis software, developed by Argonne National Laboratory. The study compares the performance of MPC and conventional rule-base control methods.

Two modern light-duty passenger vehicles were selected for chassis dynamometer testing to evaluate differences in performance end efficiency resulting from CNG and gasoline combustion in a vehicle-based context. The vehicles were chosen to be as similar as possible apart from fuel type, sharing similar test weights and identical driveline configurations. Both vehicles were tested over several chassis dynamometer driving cycles, where it was found that the CNG vehicle exhibited 3-9% lower fuel economy than the gasoline-fueled subject. Performance tests were also conducted, where the CNG vehicle's lower tractive effort capability and longer acceleration times were consistent with the lower rated torque and power of its engine as compared to the gasoline model. The vehicles were also tested using quasi-steady-state chassis dynamometer techniques, wherein a series of engine operating points were studied.

One-dimensional simulation methods for unsteady (transient) engine operations have been developed and published in previous studies. These 1-D methods utilize heat release and emissions results obtained from 3-D CFD simulations which are stored in a data library. The goal of this study is to improve the 1-D methodology by optimizing the control strategies. Also, additional independent parameters are introduced to extend the 3-D data library, while, as in the previous studies, the number of interpolation points for each parameter remains small. The data points for the 3-D simulations are selected in the vicinity of the expected trajectories obtained from the independent parameter changes, as predicted by the transient 1-D simulations. By this approach, the number of time-consuming 3-D simulations is limited to a reasonable amount.

Spray structure has a significant effect on emissions and performance of an internal combustion engine. The main objective of this study is to investigate spray structures based on four different multiple jet impingement injectors. These four different multiple jet-to-jet impingement injectors include 1). 4-hole injector (Case 1), which has symmetric inwardly opening nozzles; 2). 5-1-hole (Case 2); 3). 6-2-hole (Case 3); and 4). 7-3-hole (Case 4) which corresponding to 1, 2, 3 numbers of adjacent holes blocked in a 5-hole, 6-hole, and 7-hole symmetrical drill pattern, respectively. All these configurations are basically 4-holes but with different post collision spray structure. Computational Fluid Dynamics (CFD) work of these sprays has been performed using an Eulerian-Lagrangian modelling approach.

A numerical simulation of autoignition of gasoline-ethanol/air mixtures has been performed using the closed homogeneous reactor model in CHEMKIN® to compute the dependence of autoignition time with ethanol concentration, pressure, temperature, dilution, and equivalence ratio. A semi-detailed validated chemical kinetic model with 142 species and 672 reactions for a gasoline surrogate fuel with ethanol has been used. The pure components in the surrogate fuel consisted of n-heptane, isooctane and toluene. The ethanol volume fraction is varied between 0 to 85%, initial pressure is varied between 20 to 60 bar, initial temperature is varied between 800 to 1200K, and the dilution is varied between 0 to 32% at equivalence ratios of 0.5, 1.0 and 1.5 to represent the in-cylinder conditions of a spark-ignition engine. The ignition time is taken to be the point where the rate of change of temperature with respect to time is the largest (temperature inflection point criteria).

A numerical analysis was performed to study the variation of the laminar burning speed of gasoline-ethanol blend, pressure, temperature and dilution using the one-dimensional premixed flame code CHEMKIN™. A semi-detailed validated chemical kinetic model (142 species and 672 reactions) for a gasoline surrogate fuel was used. The pure components in the surrogate fuel consist of n-heptane, isooctane and toluene. The ethanol mole fraction was varied from 0 to 85 percent, initial pressure from 4 to 8 bar, initial temperature from 300 to 600K, and the EGR dilution from 0 to 32% to represent the in-cylinder conditions of a spark-ignition engine. The laminar flame speed is found to increase with ethanol concentration and temperature but decrease with pressure and dilution.

Battery management system (BMS) plays a key role in the power management of hybrid electric vehicles (HEV). It measures the state of charge (SOC), state of health (SOH) of the battery, protects the battery package and extends cells' life cycles. For HEV applications, lithium-ion battery is usually selected as electric power source due to its high specific energy, high energy density, and long life cycle. However, the non-linear characteristic of a Li-ion battery, complicated electro-chemical model, and environmental factors, raises the difficulties in the real-time estimation of the SOC for a Li-ion battery. To address this challenge, a BMS for HEVs is modeled with MATLAB/Simulink. In addition, a regenerative braking control strategy is proposed to determine the magnitude of the regenerative torque based on the battery SOC.