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We present the effect of EGR, at a set fuel flow rate and intake temperature, on the operating parameters of timing of combustion, duration of combustion, power output, thermal efficiency, and NOx emission; which is remarkably low. We find that addition of EGR at constant inlet temperature and constant fuel flow rate has little effect on HCCI parameter of start of combustion (SOC). However, burn duration is highly dependent on the amount of EGR inducted. The experimental setup at UC Berkeley uses a 1.9-liter 4-cylinder diesel engine with a compression ratio of 18.8:1 (offered on a 1995 VW Passat TDI). The engine was converted to run in HCCI mode by addition of an 18kW air pre-heater installed in the intake system. Pressure traces were obtained using four water-cooled quartz pressure transducers, which replaced the Diesel fuel injectors. Gaseous fuel (propane or butane) flowed steadily into the intake manifold.

The use of virtual prototyping early in the design stage of a product has gained popularity due to reduced cost and time to market. The state of the art in vehicle simulation has reached a level where full vehicles are analyzed through simulation but major difficulties continue to be present in interfacing the vehicle model with accurate powertrain models and in developing adequate formulations for the contact between tire and terrain (specifically, scenarios such as tire sliding on ice and rolling on sand or other very deformable surfaces). The proposed work focuses on developing a ground vehicle simulation capability by combining several third party packages for vehicle simulation, tire simulation, and powertrain simulation. The long-term goal of this project consists in promoting the Digital Car idea through the development of a reliable and robust simulation capability that will enhance the understanding and control of off-road vehicle performance.

Modeling plume interaction and collapse for direct-injection gasoline sprays is important because of its impact on fuel-air mixing and engine performance. Nevertheless, the aerodynamic interaction between plumes and the complicated two-phase coupling of the evaporating spray has shown to be notoriously difficult to predict. With the availability of high-speed (100 kHz) Particle Image Velocimetry (PIV) experimental data, we compare velocity field predictions between plumes to observe the full temporal evolution leading up to plume merging and complete spray collapse. The target “Spray G” operating conditions of the Engine Combustion Network (ECN) is the focus of the work, including parametric variations in ambient gas temperature. We apply both LES and RANS spray models in different CFD platforms, outlining features of the spray that are most critical to model in order to predict the correct aerodynamics and fuel-air mixing.

It has previously been shown experimentally and computationally that the process of Homogeneous Charge Compression Ignition (HCCI) is very dependent on the pre-combustion gas temperature field. This study looks in detail at how temperature fields can evolve by comparing results of two combustion chamber designs, a piston with a square bowl and a disk shaped piston, and relates these temperature fields to measured HCCI combustion durations. The contributions of combustion chamber surface area and turbulence levels to the gas temperature evolution are considered over the crank angle range from intake valve closure to top-dead-center. This is a CFD study, whose results were transformed into traditional analysis methods of convective heat transfer (q=h*A*ΔT) and boundary layers.

A two-stage PPCI-diffusion combustion process recently showed good potential to enable clean and fuel-efficient gasoline compression ignition (GCI) combustion at medium-to-high loads. By conducting closed-cycle 3-D CFD combustion analysis, a further step was undertaken in this work to evaluate and optimize the PPCI-diffusion combustion strategy at a full load operating point (2000rpm-23.5 bar IMEPcc) while keeping engine-out NOx below 1 g/kWh. The light-duty GCI engine used in this investigation featured a custom-designed piston bowl geometry at a 17.0 compression ratio (CR), a high pressure diesel fuel injection system, and advanced single-stage turbocharging. A split fuel injection strategy was used to enable the two-stage PPCI-diffusion combustion process. First, the injector spray pattern and swirl ratio effects were evaluated. In-cylinder air utilization and the PPCI-diffusion combustion process were notably influenced by the closed-cycle combustion system design.

This paper shows how a computer can systematically remove non-essential chemical reactions from a large chemical kinetic mechanism. The computer removes the reactions based upon a single solution using a detailed mechanism. The resulting reduced chemical mechanism produces similar numerical predictions significantly faster than predictions that use the detailed mechanism. Specifically, a reduced chemical kinetics mechanism for iso-octane has been derived from a detailed mechanism by eliminating unimportant reaction steps and species. The reduced mechanism has been developed for the specific purpose of fast and accurate prediction of ignition timing in an HCCI engine. The reduced mechanism contains 199 species and 383 reactions, while the detailed mechanism contains 859 species and 3606 reactions. Both mechanisms have been used in numerical simulation of HCCI combustion.

We have developed a model of the diesel fuel injection process for application to analysis of low temperature non-sooting combustion. The model uses a simplified mixing correlation and detailed chemical kinetics to analyze a parcel of fuel as it moves along the fuel jet, from injection to evaporation and ignition. The model predicts chemical composition and soot precursors, and is applied at conditions that result in low temperature non-sooting combustion. Production of soot precursors is the first step toward production of soot, and modeling precursor production is expected to give insight into the overall evolution of soot inside the engine. The results of the analysis show that the model has been successful in describing many of the observed characteristics of low temperature combustion.

In this paper, a framework for estimating experimental measurement uncertainties for a Homogenous Charge Compression Ignition (HCCI)/Low-Temperature Gasoline Combustion (LTGC) engine testing facility is presented. Detailed uncertainty quantification is first carried out for the measurement of the in-cylinder pressure, whose variations during the cycle provide most of the information for performance evaluation. Standard uncertainties of other measured quantities, such as the engine geometry and speed, the air and fuel flow rate and the intake/exhaust dry molar fractions are also estimated. Propagating those uncertainties using a Monte Carlo simulation and Bayesian inference methods then allows for estimation of uncertainties of the mass-average temperature and composition at IVC and throughout the cycle; and also of the engine performances such as gross Integrated Mean Effective Pressure, Heat Release and Ringing Intensity.

Striving for sustainable transportation solutions, hydrogen is often identified as a promising energy carrier and internal combustion engines are seen as a cost effective consumer of hydrogen to facilitate the development of a large-scale hydrogen infrastructure. Driven by efficiency and emissions targets defined by the U.S. Department of Energy, a research team at Argonne National Laboratory has worked on optimizing a spark-ignited direct injection engine for hydrogen. Using direct injection improves volumetric efficiency and provides the opportunity to properly stratify the fuel-air mixture in-cylinder. Collaborative 3D-CFD and experimental efforts have focused on optimizing the mixture stratification and have demonstrated the potential for high engine efficiency with low NOx emissions. Performance of the hydrogen engine is evaluated in this paper over a speed range from 1000 to 3000 RPM and a load range from 1.7 to 14.3 bar BMEP.

A methodology has been developed for identifying the combination of battery characteristics which lead to least-cost electric vehicles. Battery interrelationships include specific power vs, specific energy, peak power vs. specific energy and DOD, cycle life vs. DOD, cost vs. specific energy and peak power, and volumetric and battery size effects. The method is illustrated for the “second car” mission assuming lead/acid batteries. Reductions in life-cycle costs associated with future battery research breakthroughs are estimated using a sensitivity technique. A research prioritization system is described.

Traditional Lagrangian spray modeling approaches for internal combustion engines are highly grid-dependent due to insufficient resolution in the near nozzle region. This is primarily because of inherent restrictions of volume fraction with the Lagrangian assumption together with high computational costs associated with small grid sizes. A state-of-the-art grid-convergent spray modeling approach was recently developed and implemented by Senecal et al., (ASME-ICEF2012-92043) in the CONVERGE software. The key features of the methodology include Adaptive Mesh Refinement (AMR), advanced liquid-gas momentum coupling, and improved distribution of the liquid phase, which enables use of cell sizes smaller than the nozzle diameter. This modeling approach was rigorously validated against non-evaporating, evaporating, and reacting data from the literature.

There are many challenges in implementing grid aware plug-in electric vehicle (PEV) charging systems with local load control. New opportunities for innovative load control were created as a result of changes to the 2014 National Electric Code (NEC) about automatic load control definitions for EV charging infrastructure. Stakeholders in optimized dispatch of EV charging assets include the end users (EV drivers), site owner/operators, facility managers and utilities. NEC definition changes allow for ‘over subscription’ of more potential EV charging station load than can be continuously supported if the total load at any time is within the supply system safety limit. Local load control can be implemented via compact submeter(s) with locally hosted control algorithms using direct communication to the managed electric vehicle supply equipment (EVSE).

Road vehicles can expend a significant amount of energy in undesirable vertical motions that are induced by road bumps, and much of that is dissipated in conventional shock absorbers as they dampen the vertical motions. Presented in this paper are some of the results of a study aimed at determining the effectiveness of efficiently transforming that energy into electrical power by using optimally designed regenerative electromagnetic shock absorbers. In turn, the electrical power can be used to recharge batteries or other efficient energy storage devices (e.g., flywheels) rather than be dissipated. The results of the study are encouraging - they suggest that a significant amount of the vertical motion energy can be recovered and stored.

The 4th Workshop of the Engine Combustion Network (ECN) was held September 5-6, 2015 in Kyoto, Japan. This manuscript presents a summary of the progress in experiments and modeling among ECN contributors leading to a better understanding of soot formation under the ECN “Spray A” configuration and some parametric variants. Relevant published and unpublished work from prior ECN workshops is reviewed. Experiments measuring soot particle size and morphology, soot volume fraction (fv), and transient soot mass have been conducted at various international institutions providing target data for improvements to computational models. Multiple modeling contributions using both the Reynolds Averaged Navier-Stokes (RANS) Equations approach and the Large-Eddy Simulation (LES) approach have been submitted. Among these, various chemical mechanisms, soot models, and turbulence-chemistry interaction (TCI) methodologies have been considered.

As connectivity and sensing technologies become more mature, automated vehicles can predict future driving situations and utilize this information to drive more energy-efficiently than human-driven vehicles. However, future information beyond the limited connectivity and sensing range is difficult to predict and utilize, limiting the energy-saving potential of energy-efficient driving. Thus, we combine a conventional speed optimization planner, developed in our previous work, and reinforcement learning to propose a real-time intelligent speed optimization planner for connected and automated vehicles. We briefly summarize the conventional speed optimization planner with limited information, based on closed-form energy-optimal solutions, and present its multiple parameters that determine reference speed trajectories.

In this work, an experimental and analysis methodology was developed to evaluate the preignition propensity of fuels and engine operating conditions in an SI engine. A heated glow plug was introduced into the combustion chamber to induce early propagating flames. As the temperature of the glowplug varied, both the fraction of cycles experiencing these early flames and the phasing of this combustion in the engine cycle varied. A statistical methodology for assigning a single-value to this complex behavior was developed and found to have very good repeatability. The effects of engine operating conditions and fuels were evaluated using this methodology. While this study is not directly studying the so-called stochastic preignition or low-speed preignition problem, it studies one aspect of that problem in a very controlled manner.

This work presents a simple fan model that is based on the actuator disk approximation, and the blade element and vortex theory of a propeller. A set of equations are derived that require as input the rotational speed of the fan, geometric fan data, and the lift and drag coefficients of the blades. These equations are solved iteratively to obtain the body forces generated by the fan in the axial and circumferential directions. These forces are used as momentum sources in a CFD code to simulate the effect of the fan in an underhood thermal management simulation. To validate this fan model, a fan experiment was simulated. The model was incorporated into the CFD code STAR-CD and predictions were generated for axial and circumferential air velocities at different radial positions and at different planes downstream of the fan. The agreement between experimental measurements and predictions is good.

Detailed chemical kinetics, although preferred due to increased accuracy, can significantly slow down CFD combustion simulations. Chemistry solutions are typically the most computationally costly step in engine simulations. The calculation time can be significantly accelerated using a multi-zone combustion model. The multi-zone model is integrated into the CONVERGE CFD code. At each time-step, the CFD cells are grouped into zones based on the cell temperature and equivalence ratio. The chemistry solver is invoked only on each zone. The zonal temperature and mass fractions are remapped onto the CFD cells, such that the temperature and composition non-uniformities are preserved. Two remapping techniques published in the literature are compared for their relative performance. The accuracy and speed-up of the multi-zone model is improved by using variable bin sizes at different temperature and equivalence ratios.

In an effort of providing better understanding of regeneration mechanisms of diesel particulate matter (PM), this experimental investigation focused on evaluating the amount of heat release generated during the thermal reaction of diesel PM and the concentrations of soluble organic compounds (SOCs) dissolved in PM emissions. Differences in oxidation behaviors were observed for two different diesel PM samples: a SOC-containing PM sample and a dry soot sample with no SOCs. Both samples were collected from a cordierite particulate filter membrane in a thermal reactor connected to the exhaust pipe of a light-duty diesel engine. A differential scanning calorimeter (DSC) and a thermogravimetric analyzer (TGA) were used to measure the amount of heat release during oxidation, along with subsequent oxidation rates and the concentrations of SOCs dissolved in particulate samples, respectively.

For several years there has been a great deal of effort made in researching ways to run a compression ignition engine with simultaneously high efficiency and low emissions. Recently much of this focus has been dedicated to using gasoline-like fuels that are more volatile and less reactive than conventional diesel fuel to allow the combustion to be more premixed. One of the key challenges to using fuels with such properties in a compression ignition engine is stable engine operation at low loads. This paper provides an analysis of how stable gasoline compression ignition (GCI) engine operation was achieved down to idle speed and load on a multi-cylinder compression ignition engine using only 87 anti-knock index (AKI) gasoline. The variables explored to extend stable engine operation to idle included: uncooled exhaust gas recirculation (EGR), injection timing, injection pressure, and injector nozzle geometry.