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We have developed a methodology for predicting combustion and emissions in a Homogeneous Charge Compression Ignition (HCCI) Engine. The methodology judiciously uses a fluid mechanics code followed by a chemical kinetics code to achieve great reduction in the computational requirements; to a level that can be handled with current computers. In previous papers, our sequential, multi-zone methodology has been applied to HCCI combustion of short-chain hydrocarbons (natural gas and propane). Applying the same procedure to long-chain hydrocarbons (iso-octane) results in unacceptably long computational time. In this paper, we show how the computational time can be made acceptable by developing a segregated solver. This reduces the run time of a ten-zone problem by an order of magnitude and thus makes it much more practical to make combustion studies of long-chain hydrocarbons.

An engine cycle simulation code with detailed chemical kinetics has been developed to study Homogeneous Charge Compression Ignition (HCCI) combustion with hydrogen as the fuel. In order to attain adequate combustion duration, resulting from the self-accelerating nature of the chemical reaction, fuel and temperature inhomogeneities have been brought to the calculation by considering the combustion chamber to have various temperature and fuel distributions. Calculations have been done under various conditions including both perfectly homogeneous and inhomogeneous cases, changing the degree of inhomogeneity. The results show that intake gas temperature is more dominant on ignition timing of HCCI than equivalence ratio and that there is a possibility to control HCCI by introducing appropriate temperature inhomogeneity to in-cylinder mixture.

We have developed a methodology for predicting combustion and emissions in a Homogeneous Charge Compression Ignition (HCCI) Engine. This methodology combines a detailed fluid mechanics code with a detailed chemical kinetics code. Instead of directly linking the two codes, which would require an extremely long computational time, the methodology consists of first running the fluid mechanics code to obtain temperature profiles as a function of time. These temperature profiles are then used as input to a multi-zone chemical kinetics code. The advantage of this procedure is that a small number of zones (10) is enough to obtain accurate results. This procedure achieves the benefits of linking the fluid mechanics and the chemical kinetics codes with a great reduction in the computational effort, to a level that can be handled with current computers.

Identifying edge cases for designed algorithms is critical for functional safety in autonomous driving deployment. In order to find the feasible boundary of designed algorithms, simulations are heavily used. However, simulations for autonomous driving validation are expensive due to the requirement of visual rendering, physical simulation, and AI agents. In this case, common sampling techniques, such as Monte Carlo Sampling, become computationally expensive due to their sample inefficiency. To improve sample efficiency and minimize the number of simulations, we propose a tailored active learning approach combining the Support Vector Machine (SVM) and the Gaussian Process Regressor (GPR). The SVM learns the feasible boundary iteratively with a new sampling point via active learning. Active Learning is achieved by using the information of the decision boundary of the current SVM and the uncertainty metric calculated by the GPR.

The simulation of combustion chemistry in internal combustion engines is challenging due to the need to include detailed reaction mechanisms to describe the engine physics. Computational times needed for coupling full chemistry to CFD simulations are still too computationally demanding, even when distributed computer systems are exploited. For these reasons the present paper proposes a time scale separation approach for the integration of the chemistry differential equations and applies it in an engine CFD code. The time scale separation is achieved through the estimation of a characteristic time for each of the species and the introduction of a sampling timestep, wherein the chemistry is subcycled during the overall integration. This allows explicit integration of the system to be carried out, and the step size is governed by tolerance requirements.

We present an approach in which an open-source software infrastructure is used for testing the behavior of autonomous vehicles through computer simulation. This software infrastructure is called CAVE, from Connected Autonomous Vehicle Emulator. As a software platform that allows rapid, low-cost and risk-free testing of novel designs, methods and software components, CAVE accelerates and democratizes research and development activities in the field of autonomous navigation.

Two distinct atomization strategies are contrasted through the measurement of time and spatially dependent mass flux. The two systems investigated include a pressure atomizer (6.9 MPa opening pressure) and an air-assist atomizer. Both systems have potential for use in direct injection spark ignition engines. The mass flux data presented were obtained using a spray patternator that was developed to allow phased sampling of the spray. The temporal mass related history of the spray was reconstructed as volume versus time plots and interpolated mass flux contour plots. Results indicate substantial differences in the distribution of both mass and mass flux in space and time for the two injection systems. For example, the pressure atomizer at high mass delivery rates produced a spray that collapsed into a dispersed cylindrical shape while at low rates, generated a hollow cone structure.

This paper presents the results of an experimental program in which a Texaco L-163S engine was fueled with methanol and operated in its traditional stratified charge mode and then modified to run as a homogeneous charge spark ignited engine. The primary data taken were the aldehyde and unburned fuel emissions (UBF). These data were taken using a continuous time-averaging sampling probe at the exhaust tank and at the exhaust port and with a rotary time-resolving sampling valve located at the exhaust port. The data are for two loads, 138.1 kPa (20 psi) and 207.1 kPa (30 psi) BMEP and three speeds, 1000, 1400 and 1800 rpm. The data indicate that for both the stratified charge and the homogeneous charge modes of operation formaldehyde was the only aldehyde detected in the exhaust and it primarily originated in the cylinder.

Combustion under stratified operating conditions in a direct-injection spark-ignition engine was investigated using simultaneous planar laser-induced fluorescence imaging of the fuel distribution (via 3-pentanone doped into the fuel) and the combustion products (via OH, which occurs naturally). The simultaneous images allow direct determination of the flame front location under highly stratified conditions where the flame, or product, location is not uniquely identified by the absence of fuel. The 3-pentanone images were quantified, and an edge detection algorithm was developed and applied to the OH data to identify the flame front position. The result was the compilation of local flame-front equivalence ratio probability density functions (PDFs) for engine operating conditions at 600 and 1200 rpm and engine loads varying from equivalence ratios of 0.89 to 0.32 with an unthrottled intake. Homogeneous conditions were used to verify the integrity of the method.

The present work is aimed at developing a computational model of the interelectrode phenomena in thermionic energy converters which will be accurate over a very wide range of plasma conditions and operating modes. Previous models have achieved only moderate degrees of accuracy and, in a limited range, of validity. This limited range excludes a number of advanced thermionic devices, such as barium-cesium converters. The model under development promises improved accuracy in prediction of conventional devices and extension of predictive capability to advanced devices. The approach is to adapt the “Converted Scheme”, or CS method, to the cesium vapor plasma diode. This method, developed at the University of Wisconsin- Madison, is an extremely efficient algorithm for the solution of charged-particle kinetic equations and has been successfully used to simulate helium RF glow discharges.

The effect of equivalence ratio on the particulate size distribution (PSD) in a spark-ignited, direct-injected (SIDI) engine was investigated. A single-cylinder, four-stroke, spark-ignited direct-injection engine fueled with certification gasoline was used for the measurements. The engine was operated with early injection during the intake stroke. Equivalence ratio was swept over the range where stable combustion was achieved. Throughout this range combustion phasing was held constant. Particle size distributions were measured as a function of equivalence ratio. The data show the sensitivity of both engine-out particle number and particle size to global equivalence ratio. As equivalence ratio was increased a larger fraction of particles were due to agglomerates with diameters ≻ 100 nm. For decreasing equivalence ratio smaller particles dominate the distribution. The total particle number and mass increased non-linearly with increasing equivalence ratio.

Multidimensional modeling is used to study air-fuel mixing in a direct-injection spark-ignition engine. Emphasis is placed on the effects of the start of fuel injection on gas/spray interactions, wall wetting, fuel vaporization rate and air-fuel ratio distributions in this paper. It was found that the in-cylinder gas/spray interactions vary with fuel injection timing which directly impacts spray characteristics such as tip penetration and spray/wall impingement and air-fuel mixing. It was also found that, compared with a non-spray case, the mixture temperature at the end of the compression stroke decreases substantially in spray cases due to in-cylinder fuel vaporization. The computed trapped-mass and total heat-gain from the cylinder walls during the induction and compression processes were also shown to be increased in spray cases.

A laboratory-based fuel mixture system capable of delivering a range of fuel/air mixtures has been used to observe the effects of differing mixture characteristics on engine combustion through measurement and analysis of incylinder pressure and exhaust emissions. Fuel air mixtures studied can be classified into four different types: 1) Completely homogeneous fuel/air mixtures, where the fuel has been vaporized and mixed with the air prior to entrance into the normal engine induction system, 2) liquid fuel that is atomized and introduced with the air to the normal engine induction system, 3) liquid fuel that is atomized, and partially prevaporized but the air/fuel charge remains stratified up to introduction to the induction system, and 4) the standard fuel metering system. All tests reported here were conducted under wide open throttle conditions. A four-stroke, spark-ignited, single-cylinder, overhead valve-type engine was used for all tests.

Lithium-ion and Lithium polymer batteries are fast becoming ubiquitous in high-discharge rate applications for military and non-military systems. Applications such as small aerial vehicles and energy transfer systems can often function at C-rates greater than 1. To maximize system endurance and battery health, there is a need for models capable of precisely estimating the battery state-of-charge (SoC) under all temperature and loading conditions. However, the ability to perform state estimation consistently and accurately to within 1% error has remained unsolved. Doing so can offer enhanced endurance, safety, reliability, and planning, and additionally, simplify energy management. Therefore, the work presented in this paper aims to study and develop experimentally validated mathematical models capable of high-accuracy battery SoC estimation.

A direct injection-gasoline (DI-G) system was applied to a heavy-duty diesel-type engine to study the effects of charge stratification on the performance of premixed compression ignited combustion. The effects of the fuel injection parameters on combustion phasing were of primary interest. The simultaneous effects of the fuel stratification on Unburned Hydrocarbon (UHC), Oxides of Nitrogen (NOx), Carbon Monoxide (CO), and smoke emissions were also measured. Engine tests were conducted with altered injection parameters covering the entire load range of normally aspirated Homogeneous Charge Compression Ignited (HCCI) combustion. Combustion phasing tests were also conducted at several engine speeds to evaluate its effects on a fuel stratification strategy.

The present study investigated HCCI combustion in a heavy-duty diesel engine both experimentally and numerically. The engine was equipped with a hollow-cone pressure-swirl injector using gasoline direct injection. Characteristics of HCCI combustion were obtained by very early injection with a heated intake charge. Experimental results showed an increase in NOx emission and a decrease in UHC as the injection timing was retarded. It was also found that optimization can be achieved by controlling the intake temperature together with the start-of-injection timing. The experiments were modeled by using an engine CFD code with detailed chemistry. The CHEMKIN code was implemented into KIVA-3V such that the chemistry and flow solutions were coupled. The model predicted ignition timing, cylinder pressure, and heat release rates reasonably well. The NOx emissions were found to increase as the injection timing was retarded, in agreement with experimental results.

Automatic manufacturability analysis of injection moldings, sheet metal castings, stampings, forgings, etc., using knowledge-based heuristics depends on shape features, which are abstractions of the three dimensional (3D) geometric model of the parts. Conventional CAD systems do not explicitly contain shape feature information, therefore such information needs to be extracted from them. So far, extraction of shape features has been restricted to models with simple geometric shapes such as planar, cylindrical or conical shapes. Extending shape feature extraction to non-linear geometric models will allow Design For Manufacturability (DFM) analysis of non-linear models. This paper presents an approach to extract features from non-linear geometric models. The approach is based on abstract geometric entities called C-loops. The formation of a C-loop depends on a geometric entity called a silhouette. The C-loops are derived from the silhouette boundaries of an object.

Fuel film temperature and thickness were measured on the piston crown of a DISI engine under both motored and fired conditions using the fiber-based laser-induced fluorescence method wherein a single fiber delivers the excitation light and collects the fluorescence. The fibers were installed in the piston crown of a Bowditch-type optical engine and exited via the mirror passage. The fuel used for the fuel film temperature measurement was a 2×10-6 M solution of BTBP in isooctane. The ratio of the fluorescence intensity at 515 to that at 532 nm was found to be directly, but not linearly, related to temperature when excited at 488 nm. Effects related to the solvent, solution aging and bleaching were investigated. The measured fuel film temperature was found to closely follow the piston crown metal temperature, which was measured with a thermocouple.

A global optimization method has been developed for an engine simulation code and utilized in the search of optimal fuel injection strategies. This method uses a Lagrange interpolation function which interpolates engine output data generated at the vertices and the intermediate points of the input parameters. This interpolation function is then used to find a global minimum over the entire parameter set, which in turn becomes the starting point of a CFD-based optimization. The CFD optimization is based on a steepest descent method with an adaptive cost function, where the line searches are performed with a fast-converging backtracking algorithm. The adaptive cost function is based on the penalty method, where the penalty coefficient is increased after every line search. The parameter space is normalized and, thus, the optimization occurs over the unit cube in higher-dimensional space.

Transient operation of automobile engines is known to contribute significantly to regulated exhaust emissions, and is also an area of drivability concerns. Furthermore, many on-board diagnostic algorithms do not perform well during transient operation and are often temporarily disabled to avoid problems. The inability to quickly and repeatedly test engines during transient conditions in a laboratory setting limits researchers and development engineers ability to produce more effective and robust algorithms to lower vehicle emissions. To meet this need, members of the Powertrain Control Research Laboratory (PCRL) at the University of Wisconsin-Madison have developed a high-bandwidth, hydrostatic dynamometer system that will enable researchers to explore transient characteristics of engines and powertrains in the laboratory.