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A computer simulation of the Homogenous Charge Compression Ignition (HCCI) four-stroke engine has been developed for combustion and performance studies. The simulation couples models for mass, species, and energy within a zero-dimensional framework. The combustion process is described via a user-defined chemical kinetic mechanism. The CHEMKIN libraries have been used to formulate a stiff chemical kinetic solver suitable for integration within a complete engine cycle simulation, featuring models of gas exchange, turbulence and wall heat transfer. For illustration, two chemical kinetics schemes describing hydrogen and natural gas chemistry have been implemented in the code. The hydrogen scheme is a reduced one, consisting of 11 species and 23 reactions. The natural gas chemistry is described via the GRI-mechanism 3.0 that considers 53 species and 325 reactions, including NOx chemistry.

An early-design methodology for predicting both expected fuel economy and catalyst-out CO, HC and NOx concentrations during arbitrarily-defined transient cycles is presented. The methodology is based on utilizing a vehicle-powertrain model with embedded maps of fully warmed up engine-out performance and emissions, and appropriate temperature-dependent correction factors to account for not fully warmed up conditions during transients. Similarly, engine-out emissions are converted to catalyst-out emissions using conversion efficiencies based on the catalyst brick temperature. A crucial element of the methodology is hence the ability to predict heat flows and component temperatures in the engine and the exhaust system during transients, consistent with the data available during concept definition and early design phases.

Stringent fuel economy and emissions regulations have driven development of new mixture preparation technologies and increased spark-ignition engine complexity. Additional degrees of freedom, brought about by devices such as cam phasers and charge motion control valves, enable greater range and flexibility in engine control. This permits significant gains in fuel efficiency and emission control, but creates challenges related to proper engine control and calibration techniques. Accurate experimental characterization of high degree of freedom engines is essential for addressing the controls challenge. In particular, this paper focuses on the evaluation of three experimental residual gas fraction measurement techniques for use in a spark ignition engine equipped with dual-independent variable camshaft phasing (VVT).

Homogenous Charge Compression Ignition (HCCI) engines offer a good potential for achieving high fuel efficiency while virtually eliminating NOx and soot emissions from the exhaust. However, realizing the full fuel economy potential at the vehicle level depends on the size of the HCCI operating range. The usable HCCI range is determined by the knock limit on the upper end and the misfire limit at the lower end. Previously proven high sensitivity of the HCCI process to thermal conditions leads to a hypothesis that combustion chamber deposits (CCD) could directly affect HCCI combustion, and that insight about this effect can be helpful in expanding the low-load limit. A combustion chamber conditioning process was carried out in a single-cylinder gasoline-fueled engine with exhaust re-breathing to study CCD formation rates and their effect on combustion. Burn rates accelerated significantly over the forty hours of running under typical HCCI operating conditions.

This paper discusses the compression ratio influence on maximum load of a Natural Gas HCCI engine. A modified Volvo TD100 truck engine is controlled in a closed-loop fashion by enriching the Natural Gas mixture with Hydrogen. The first section of the paper illustrates and discusses the potential of using hydrogen enrichment of natural gas to control combustion timing. Cylinder pressure is used as the feedback and the 50 percent burn angle is the controlled parameter. Full-cycle simulation is compared to some of the experimental data and then used to enhance some of the experimental observations dealing with ignition timing, thermal boundary conditions, emissions and how they affect engine stability and performance. High load issues common to HCCI are discussed in light of the inherent performance and emissions tradeoff and the disappearance of feasible operating space at high engine loads.

The thermal conditions of an engine structure, in particular the wall temperatures, have been shown to have a great effect on the HCCI engine combustion timing and burn rates through wall heat transfer, especially during transient operations. This study addresses the effects of thermal inertia on combustion in an HCCI engine. In this study, the control of combustion timing in an HCCI engine is achieved by modulating the residual gas fraction (RGF) while considering the wall temperatures. A multi-cylinder engine simulation with detailed geometry is carried out using a 1-D system model (GT-Power®) that is linked with Simulink®. The model includes a finite element wall temperature solver and is enhanced with original HCCI combustion and heat transfer models. Initially, the required residual gas fraction for optimal BSFC is determined for steady-state operation. The model is then used to derive a map of the sensitivity of optimal residual gas fraction to wall temperature excursions.

This paper describes the concept and a practical implementation of piston-compounding. First, a detailed computer simulation of the piston-compounded engine is used to shed light into the thermodynamic events associated with the operation of this engine, and to predict the performance and fuel economy of the entire system. Starting from a baseline design, the simulation is used to investigate changes in system performance as critical parameters are varied. The latter include auxiliary cylinder and interconnecting manifold volumes for a given main cylinder volume, auxiliary cylinder valve timings in relation to main cylinder timings, and degree of heat loss to the coolant. Optimum designs for either highest power density or highest thermal efficiency (54%) are thus recommended. It is concluded that a piston-compounded adiabatic engine concept is a promising future powerplant.

Medium trucks constitute a large market segment of the commercial transportation sector, and are also used widely for military tactical operations. Recent technological advances in hybrid powertrains and fuel cell auxiliary power units have enabled design alternatives that can improve fuel economy and reduce emissions dramatically. However, deterministic design optimization of these configurations may yield designs that are optimal with respect to performance but raise concerns regarding the reliability of achieving that performance over lifetime. In this article we identify and quantify uncertainties due to modeling approximations or incomplete information. We then model their propagation using Monte Carlo simulation and perform sensitivity analysis to isolate statistically significant uncertainties. Finally, we formulate and solve a series of reliability-based optimization problems and quantify tradeoffs between optimality and reliability.

A regenerative braking model for a parallel Hybrid Electric Vehicle (HEV) is developed in this work. This model computes the line and pad pressures for the front and rear brakes, the amount of generator use depending on the state of deceleration (i.e. the brake pedal position), and includes a wheel lock-up avoidance algorithm. The regenerative braking model has been developed in the symbolic programming environment of MATLAB/SIMULINK/STATEFLOW for downloadability to an actual HEV's control system. The regenerative braking model has been incorporated in NREL's HEV system simulation called ADVISOR. Code modules that have been changed to implement the new regenerative model are described. Resulting outputs are compared to the baseline regenerative braking model in the parent code. The behavior of the HEV system (battery state of charge, overall fuel economy, and emissions characteristics) with the baseline and the proposed regenerative braking strategy are first compared.

A personal computer-based vehicle powertrain simulation (VPS) is developed to predict fuel economy and performance. This paper summarizes the governing equations used in the model. Then the different simulation techniques are described with emphasis on the more complicated time-dependent simulation. The simulation is validated against constant speed and variable cycle test track data obtained for a 5 ton army truck. Then the simulation is used to compare the performance of the 5 ton truck when powered by a cooled and natually aspirated engine, a cooled and turbocharged engine, and an uncooled and turbocharged engine. Studies of the effect of payload, tire efficiency, and drag coefficient on vehicle performance are also conducted, as well as a performance comparison between manual and automatic transmissions. It is concluded that the VPS code can provide good predictions of vehicle fuel economy, and thus is a useful tool in designing and evaluating vehicle powertrains.

Modern diesel engines manufactured for commercial vehicles are calibrated to meet EPA emissions regulations. Many of the technologies and strategies typically incorporated to meet emissions targets compromise engine performance and efficiency. When used in military applications, however, engine performance and efficiency are of utmost importance in combat conditions or in remote locations where fuel supplies are scarce. This motivates the study of the potential to utilize the flexibility of emissions-reduction technologies toward optimizing engine performance while still keeping the emissions within tolerable limits. The study was conducted on a modern medium-duty International V-8 diesel engine with variable geometry turbocharger (VGT) and exhaust gas recirculation (EGR). The performance-emissions tradeoffs were explored using design of experiments and response surface methodology.

Variable geometry turbines (VGT) are of particular interest to advanced diesel powertrains for future conventional trucks, since they can dramatically improve system transient response to sudden changes in speed and load, characteristic of automotive applications. VGT systems are also viewed as the key enabler for the application of the EGR system for reduction of heavy-duty diesel emissions. This paper applies an artificial neural network methodology to VGT modeling in order to enable representation of the VGT characteristics for any blade (nozzle) position. Following validation of the ANN model of the baseline, fixed geometry turbine, the VGT model is integrated with the diesel engine system. The latter is linked to the driveline and the vehicle dynamics module to form a complete, high-fidelity vehicle simulation.

The effects of lubricating oil on friction and engine-out emissions in a light-duty 2.2L compression ignition direct injection (CIDI) engine were investigated. A matrix of test oils varying in viscosity (SAE 5W-20 to 10W-40), friction modifier (FM) level and chemistry (MoDTC and organic FM), and basestock chemistry (mineral and synthetic) was investigated. Tests were run in an engine dynamometer according to a simulated, steady state FTP-75 procedure. Low viscosity oils and high levels of organic FM showed benefits in terms of fuel economy, but there were no significant effects observed with the oils with low MoDTC concentration on engine friction run in this program. No significant oil effects were observed on the gaseous emissions of the engine. PM emissions were analyzed for organic solubles and insolubles. The organic soluble fraction was further analyzed for the oil and fuel soluble portions.

This paper describes a test cell setup for concurrent running of a real engine and a vehicle system simulation, and its use for evaluating engine performance when integrated with a conventional and a hybrid electric driveline/vehicle. This engine-in-the-loop (EIL) system uses fast instruments and emission analyzers to investigate how critical in-vehicle transients affect engine system response and transient emissions. Main enablers of the work include the highly dynamic AC electric dynamometer with the accompanying computerized control system and the computationally efficient simulation of the driveline/vehicle system. The latter is developed through systematic energy-based proper modeling that tailors the virtual model to capture critical powertrain transients while running in real time. Coupling the real engine with the virtual driveline/vehicle offers a chance to easily modify vehicle parameters, and even study two different powertrain configurations.

Natural gas quality, in terms of the volume fraction of higher hydrocarbons, strongly affects the auto-ignition characteristics of the air-fuel mixture, the engine performance and its controllability. The influence of natural gas composition on engine operation has been investigated both experimentally and through chemical kinetic based cycle simulation. A range of two component gas mixtures has been tested with methane as the base fuel. The equivalence ratio (0.3), the compression ratio (19.8), and the engine speed (1000 rpm) were held constant in order to isolate the impact of fuel autoignition chemistry. For each fuel mixture, the start of combustion was phased near top dead center (TDC) and then the inlet mixture temperature was reduced. These experimental results have been utilized as a source of data for the validation of a chemical kinetic based full-cycle simulation.

A novel framework for intelligent design of engine systems is introduced. Existing models of engine components and processes are integrated into a multi-purpose, flexible configuration framework. Fundamental thermodynamic elements, including zero-dimensional control volumes, one-dimensional pulsating fluid lines, and continuous flow machines are identified as the constituting components of engine systems. Models of the behavior of these elements, with various degrees of thermodynamic resolution, have been implemented into the framework. The task of the engine designer is, thus, reduced into selecting appropriate thermodynamic elements to model his engine system based on his design objectives. The applicability of the present framework to a wide range of simulation problems is demonstrated.

A program to explore the effects of natural and additive-derived cetane on various aspects of diesel performance and combustion has been carried out. Procedures have been developed to measure diesel engine fuel consumption and power to a high degree of precision. These methods have been used to measure fuel consumption and power in three heavy-duty direct-injection diesel engines. The fuel matrix consisted of three commercial fuels of cetane number (CN) of 40-42, the same fuels raised to CN 48-50 with a cetane improver additive, and three commercial fuels of base CN 47-50. The engines came from three different U.S. manufacturers and were of three different model years and emissions configurations. Both fuel economy and power were found to be significantly higher for the cetane-improved fuels than for the naturally high cetane fuels. These performance advantages derive mainly from the higher volumetric heat content inherent to the cetane-improved fuels.

A hybrid electric vehicle simulation tool (HE-VESIM) has been developed at the Automotive Research Center of the University of Michigan to study the fuel economy potential of hybrid military/civilian trucks. In this paper, the fundamental architecture of the feed-forward parallel hybrid-electric vehicle system is described, together with dynamic equations and basic features of sub-system modules. Two vehicle-level power management control algorithms are assessed, a rule-based algorithm, which mainly explores engine efficiency in an intuitive manner, and a dynamic-programming optimization algorithm. Simulation results over the urban driving cycle demonstrate the potential of the selected hybrid system to significantly improve vehicle fuel economy, the improvement being greater when the dynamic-programming power management algorithm is applied.

The effect of natural gas composition on ignition delay has been investigated numerically by using detailed and reduced chemical kinetic mechanisms. Three different blends of natural gas have been analyzed at pressures and temperatures that are typical of top dead center conditions in compression ignition engines. The predicted ignition delay shows a decrease with temperature in an Arrhenius manner and has a first order dependence on pressure. Similar trends have been observed by Naber et al. [1] in their experimental study of natural gas autoignition in a bomb. It is shown that two kinetic mechanisms (GRI-Mech 1.2 and reduced set DRM22) are best capable of predicting the ignition delay of natural gas under compression ignition conditions. The DRM22 mechanism has been chosen for further studies as t involves lower computational costs compared to the full GRI-Mech 1.2 mechanism.

The heat release and pollutant formation processes in a direct injection natural gas engine are studied by coupling detailed chemistry with a multi-dimensional reactive flow code. A detailed kinetic mechanism consisting of 22 species and 104 elementary reactions is chosen by comparing ignition delay predictions with measurements in a combustion bomb. The ignition model is then coupled with a turbulent combustion model and extended Zeldovich kinetics to simulate heat release and nitric oxide production in a direct injection engine. Parametric studies are conducted to investigate the effect of engine operating conditions which include speed, load, injection timing and level of boost. It is shown that use of detailed chemistry is extremely important to predict the correct ignition delay period as engine operating conditions change. Use of both time and crank angle as the independent variable reveals interesting details of the heat release process as a function of engine speed.