Search Results

A generalized re-normalization group (RNG) turbulence model based on the local "dimensionality" of the flow field is proposed. In this modeling approach the model coefficients C₁, C₂, and C₃ are all constructed as functions of flow strain rate. In order to further validate the proposed turbulence model, the generalized RNG closure model was applied to model the backward facing step flow (a classic test case for turbulence models). The results indicated that the modeling of C₂ in the generalized RNG closure model is reasonable, and furthermore, the predictions of the generalized RNG model were in better agreement with experimental data than the standard RNG turbulence model. As a second step, the performance of the generalized RNG closure was investigated for a complex engine flow.

The paper presents the development of a novel approach to the solution of detailed chemistry in internal combustion engine simulations, which relies on the analytical computation of the ordinary differential equations (ODE) system Jacobian matrix in sparse form. Arbitrary reaction behaviors in either Arrhenius, third-body or fall-off formulations can be considered, and thermodynamic gas-phase mixture properties are evaluated according to the well-established 7-coefficient JANAF polynomial form. The current work presents a full validation of the new chemistry solver when coupled to the KIVA-4 code, through modeling of a single cylinder Caterpillar 3401 heavy-duty engine, running in two-stage combustion mode.

This paper reviews the engine modeling program in the Powertrain Control Research Laboratory at the University of Wisconsin-Madison, focuses on simulation results obtained from a complete modular turbocharged diesel engine dynamic model developed in this lab, and suggests ways that dynamic engine system models can be used in the design process. It examines the dynamic responses and interactions between various components in the engine system, looks at how these components affect the overall performance of the system in transient and steady state operation.

This paper describes the transient spray characteristics of a high pressure, single fluid injector, intended for use in a direct-injection spark-ignited (DISI) engine. The injector was a single hole, pintle type injector and was electronically controlled. A variety of measurement diagnostics, including full-field imaging and line-of-sight diffraction based particle sizing were employed for spray characterization. Transient patternator measurements were also performed to obtain temporally resolved average mass flux distributions. Particle size and obscuration measurements were performed at three locations in the spray and at three injection pressures: 3.45 MPa (500 psi), 4.83 Mpa (700 psi), and 6.21 MPa (900 psi). Results of the spray imaging experiments indicated that the spray shapes varied with time after the start of injection and contained a leading mass, or slug along the center line of the spray.

Traffic state identification is a key problem in intelligent transportation system. As a new technology, connected and automated vehicle can play a role of identifying traffic state with the installation of onboard sensors. However, research of lane level traffic state identification is relatively lacked. Identifying lane level traffic state is helpful to lane selection in the process of driving and trajectory planning. In addition, traffic state identification precision with low penetration of connected and automated vehicles is relatively low. To fill this gap, this paper proposes a novel method of identifying traffic state in the presence of connected and automated vehicles with low penetration rate. Assuming connected and automated vehicles can obtain information of surrounding vehicles’, we use the perceptible information to estimate imperceptible information, then traffic state of road section can be inferred.

The development of analytic models of diesel engine flow, combustion and subprocesses is described. The models are intended for use as design tools by industry for the prediction of engine performance and emissions to help reduce engine development time and costs. Part of the research program includes performing engine experiments to provide validation data for the models. The experiments are performed on a single-cylinder version of the Caterpillar 3406 engine that is equipped with state-of-the-art high pressure electronic fuel injection and emissions instrumentation. In-cylinder gas velocity and gas temperature measurements have also been made to characterize the flows in the engine.

An electronically controlled Caterpillar single-cylinder oil test engine (SCOTE) was used to study diesel combustion. The SCOTE retains the port, combustion chamber, and injection geometry of the production six cylinder, 373 kW (500 hp) 3406E heavy-duty truck engine. The engine was equipped with an electronic unit injector and an electronically controlled common rail injector that is capable of multiple injections. An emissions investigation was carried out using a six-mode cycle simulation of the EPA Federal Transient Test Procedure. The results show that the SCOTE meets current EPA mandated emissions levels, despite the higher internal friction imposed by the single-cylinder configuration. NOx versus particulate trade-off curves were generated over a range of injection timings for each mode and results of heat release calculations were examined, giving insight into combustion phenomena in current “state of the art” heavy-duty diesel engines.

Simulation is a useful tool which can significantly reduce resources invested during product development. Vehicle manufacturers are using simulations to aid in the evaluation of designs and components, including powertrain systems and controllers. These simulations can be made more useful by addressing issues such as flexibility, modularity, and causality. These issues and other aspects involved in the development and use of powertrain system simulations are discussed in this paper, and a case study of a powertrain system model developed in the PCRL using methodologies based on considerations of such issues is presented.

An integrated numerical model has been developed for diesel engine computations based on the KIVA-II code. The model incorporates a modified RNG k-ε, turbulence model, a ‘wave’ breakup spray model, the Shell ignition model, the laminar-and-turbulent characteristic-time combustion model, a crevice flow model, a spray/wall impingement model that includes rebounding and breaking-up drops, and other improved submodels in the KIVA code. The model was validated and applied to model successfully different types of diesel engines under various operating conditions. These engines include a Caterpillar engine with different injection pressures at different injection timings, a small Tacom engine at different loads, and a Cummins engine modified by Sandia for optical experiments. Good levels of agreement in cylinder pressures and heat release rate data were obtained using the same computer model for all engine cases.

A study was performed that takes into account both turbulence and chemical kinetic effects in the numerical simulation of diesel engine combustion in order to better understand the importance of their respective roles at changing operating conditions. An approach was developed which combines the simplicity and low computational and storage requests of the laminar-and-turbulent characteristic-time model with a detailed combustion chemistry model based on well-known simplified mechanisms. Assuming appropriate simplifications such as steady state or equilibrium for most of the radicals and intermediate species, the kinetics of hydrocarbons can be described by means of three overall steps. This approach was integrated in the KIVA-II code. The concept was validated and applied to a single-cylinder, heavy-duty engine. The simulation covers a wide range of operating conditions.

An experimental investigation of the spectral characteristics of turbulent flow in a scale model of a high pressure diesel fuel injector nozzle hole has been conducted. Instantaneous velocity measurements were made in a 50X transparent model of one hole of an injector nozzle using an Aerometrics Phase/Doppler Particle Analyzer (PDPA) in the velocity mode. Turbulence spectra were calculated from the velocity data using the Lomb-Scargle method. Injector hole length to diameter ratio (L/D) values of 1.3, 2.4, 4.9, and 7.7 and inlet radius to diameter ratio (R/D) values of approximately 0 and 0.3 were investigated. Results were obtained for a steady flow average Reynolds number of 10,500, which is analogous to a fuel injection velocity of 320 m/s and a sac pressure of approximately 67 MPa (10,000 psi). Turbulence time frequency spectra were obtained for significant locations in each geometry, in order to determine how geometry affects the development of the turbulent spectra.

This paper presents a diagnostics methodology that has applications to internal combustion engines as well as other dynamic devices. Included is an overview of the theoretical foundation of the approach, discussions on its application to internal combustion engine diagnostics, and experimental engine data showing the application of this methodology. Also included are the recent developments addressing issues of the effect of motoring compression and expansion work on crankshaft speed fluctuations and the resulting torque estimation. The methodology consists of a hard-wired nonlinear to linear transformation of engine variables that allow all subsequent diagnostics and control calculations to use linear mathematics, which significantly simplifies the size and complexity of the engine control and diagnostics strategy and code.

The focus of this paper is to discuss the modeling and control of intake plenum pressure on the Powertrain Control Research Laboratory's (PCRL) Single-Cylinder Engine (SCE) transient test system using a patented device known as the Intake Air Simulator (IAS), which dynamically controls the intake plenum pressure, and, subsequently, the instantaneous airflow into the cylinder. The IAS exists as just one of many devices that the PCRL uses to control the dynamic boundary conditions of its SCE transient test system to make it “think” and operate as though it were part of a Multi-Cylinder Engine (MCE) test system. The model described in this paper will be used to design a second generation of this device that utilizes both continuously and discretely actuating valves working in parallel.

The SAE AutoDrive Challenge II is a four-year collegiate competition dedicated to developing a Level 4 autonomous vehicle by 2025. In January 2023, the participating teams each received a Chevy Bolt EUV. Within a span of five months, the second phase of the competition took place in Ann Arbor, MI. The authors of this contribution, who participated in this event as team Wisconsin Autonomous representing the University of Wisconsin–Madison, secured second place in static events and third place in dynamic events. This has been accomplished by reducing reliance on the actual vehicle platform and instead leveraging physical analogs and simulation. This paper outlines the software and hardware infrastructure of the competing vehicle, touching on issues pertaining sensors, hardware, and the software architecture employed on the autonomous vehicle. We discuss the LiDAR-camera fusion approach for object detection and the three-tier route planning and following systems.

Progress on the development and validation of a CFD model for diesel engine combustion and flow is described. A modified version of the KIVA code is used for the computations, with improved submodels for liquid breakup, drop distortion and drag, spray/wall impingement with rebounding, sliding and breaking-up drops, wall heat transfer with unsteadiness and compressibility, multistep kinetics ignition and laminar-turbulent characteristic time combustion models, Zeldovich NOx formation, and soot formation with Nagle Strickland-Constable oxidation. The code also considers piston-cylinder-liner crevice flows and allows computations of the intake flow process in the realistic engine geometry with two moving intake valves. Significant progress has been made using a modified RNG k-ε turbulence model, and a multicomponent fuel vaporization model and a flamelet combustion model have been implemented.

In this work we studied the effects of piston bowl design on combustion in a small-bore direct-injection diesel engine. Two bowl designs were compared: a conventional, omega-shaped bowl and a stepped-lip piston bowl. Experiments were carried out in the Sandia single-cylinder optical engine facility, with a medium-load, mild-boosted operating condition featuring a pilot+main injection strategy. CFD simulations were carried out with the FRESCO platform featuring full-geometric body-fitted mesh modeling of the engine and were validated against measured in-cylinder performance as well as soot natural luminosity images. Differences in combustion development were studied using the simulation results, and sensitivities to in-cylinder flow field (swirl ratio) and injection rate parameters were also analyzed.

This paper investigates flow and combustion in a full-cycle simulation of a four-stroke, three-valve HCCI engine by visualizing the flow with pathlines. Pathlines trace massless particles in a transient flow field. In addition to visualization, pathlines are used here to trace the history, or evolution, of flow fields and species. In this study evolution is followed from the intake port through combustion. Pathline analysis follows packets of intake charge in time and space from induction through combustion. The local scalar fields traversed by the individual packets in terms of velocity magnitude, turbulence, species concentration and temperatures are extracted from the simulation results. The results show how the intake event establishes local chemical and thermal environments in-cylinder and how the species respond (chemically react) to the local field.

Appropriate spray modeling in multidimensional simulations of diesel engines is well known to affect the overall accuracy of the results. More and more accurate models are being developed to deal with drop dynamics, breakup, collisions, and vaporization/multiphase processes; the latter ones being the most computationally demanding. In fact, in parallel calculations, the droplets occupy a physical region of the in-cylinder domain, which is generally very different than the topology-driven finite-volume mesh decomposition. This makes the CPU decomposition of the spray cloud severely uneven when many CPUs are employed, yielding poor parallel performance of the spray computation. Furthermore, mesh-independent models such as collision calculations require checking of each possible droplet pair, which leads to a practically intractable O(np2/2) computational cost, np being the total number of droplets in the spray cloud, and additional overhead for parallel communications.

Optimal fuel injection strategies are obtained with a micro-genetic algorithm and an adaptive gradient method for a nonroad, medium-speed DI diesel engine equipped with a multi-orifice, asynchronous fuel injection system. The gradient optimization utilizes a fast-converging backtracking algorithm and an adaptive cost function which is based on the penalty method, where the penalty coefficient is increased after every line search. The micro-genetic algorithm uses parameter combinations of the best two individuals in each generation until a local convergence is achieved, and then generates a random population to continue the global search. The optimizations have been performed for a two pulse fuel injection strategy where the optimization parameters are the injection timings and the nozzle orifice diameters.

A numerical simulation and optimization study was conducted for a medium speed direct injection diesel engine. The engine's operating characteristics were first matched to available experimental data to test the validity of the numerical model. The KIVA-3V ERC CFD code was then modified to allow independent spray events from two rows of nozzle holes. The angular alignment, nozzle hole size, and injection pressure of each set of nozzle holes were optimized using a micro-genetic algorithm. The design fitness criteria were based on a multi-variable merit function with inputs of emissions of soot, NOx, unburned hydrocarbons, and fuel consumption targets. Penalties to the merit function value were used to limit the maximum in-cylinder pressure and the burned gas temperature at exhaust valve opening. The optimization produced a 28.4% decrease in NOx and a 40% decrease in soot from the baseline case, while giving a 3.1% improvement in fuel economy.