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A fast time-scale 1-D dynamic diesel particulate filter model capable of resolving the pressure pulsations due to individual cylinder firing events is presented. The purpose of this model is to investigate changes in the firing frequency component of the pulsating exhaust flow at different particulate loadings. Experimental validation data and simulation results clearly show that the magnitude and phase of the firing frequency components are directly correlated to the mass of particulate stored in a diesel particulate filter. This dynamic pressure signal information may prove particularly useful for monitoring particulate load during vehicle operation.

A prototype 2007 ISL Cummins diesel engine equipped with a diesel oxidation catalyst (DOC), diesel particle filter (DPF), variable geometry turbocharger (VGT), and cooled exhaust gas recirculation (EGR) was tested at Southwest Research Institute (SwRI) under a high-load accelerated durability cycle for 1000 hours with B20 soy-based biodiesel blends and ultra-low sulfur diesel (ULSD) fuel to determine the impact of B20 on engine durability, performance, emissions, and fuel consumption. At the completion of the 1000-hour test, a thorough engine teardown evaluation of the overhead, power transfer, cylinder, cooling, lube, air handling, gaskets, aftertreatment, and fuel system parts was performed. The engine operated successfully with no biodiesel-related failures. Results indicate that engine performance was essentially the same when tested at 125 and 1000 hours of accumulated durability operation.

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.

Near-Field Acoustical Holography (NAH) is an inverse process in which sound pressure measurements made in the near-field of an unknown sound source are used to reconstruct the sound field so that source distributions can be clearly identified. NAH was originally based on performing spatial transforms of arrays of measured pressures and then processing the data in the wavenumber domain, a procedure that entailed the use of very large microphone arrays to avoid spatial truncation effects. Over the last twenty years, a number of different NAH methods have been proposed that can reduce or avoid spatial truncation issues: for example, Statistically Optimized Near-Field Acoustical Holography (SONAH), various Equivalent Source Methods (ESM), etc.

Accurately characterizing vehicle drive cycles plays a fundamental role in assessing the performance of new vehicle technologies. Repeatable, short duration representative drive cycles facilitate more informed decision making, resulting in improved test procedures and more successful vehicle designs. With continued growth in the deployment of onboard telematics systems employing global positioning systems (GPS), large scale, low cost collection of real-world vehicle drive cycle data has become a reality. As a result of these technological advances, researchers, designers, and engineers are no longer constrained by lack of operating data when developing and optimizing technology, but rather by resources available for testing and simulation. Experimental testing is expensive and time consuming, therefore the need exists for a fast and accurate means of generating representative cycles from large volumes of real-world driving data.

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.

Multidimensional models are increasingly employed to predict NO and soot emissions from Diesel engines. In the traditional approach, the ensemble-averaged values of variables are employed in the expressions for NO and soot formation and oxidation. In the mixture fraction averaged approach, the values of state variables and species concentrations are obtained from the structure of laminar diffusion flames. The source terms for NO and soot are then obtained by averaging across the mixture fraction coordinate with a probability density function. The clipped-Gaussian probability density function and profiles obtained by employing the OPPDIF code (part of the CHEMKIN package) for the laminar flame structure are employed in this work. The Zeldovich mechanism for NO formation and the Moss et al. formation and Nagle-Strickland-Constable oxidation model for soot have been employed to study the qualitative trends of pollutants in transient combusting Diesel jets.

In a gasoline engine, the unswept in-cylinder residual gas and introduction of external EGR is one of the important means of controlling engine raw NOx emissions and improving part load fuel economy via reduction of pumping losses. Since the trapped in-cylinder Residual Gas Fraction (RGF, comprised of both internal, and external) significantly affects the combustion process, on-line diagnosis and monitoring of in-cylinder RGF is very important to the understanding of the in-cylinder dilution condition. This is critical during the combustion system development testing and calibration processes. However, on-line measurement of in-cylinder RGF is difficult and requires an expensive exhaust gas analyzer, making it impractical for every application. Other existing methods, based on measured intake and exhaust pressures (steady state or dynamic traces) to calculate gas mass flowrate across the cylinder ports, provide a fast and economical solution to this problem.

The goal of the automated mobility platforms (AMPs) initiative is to raise the bar of service regarding equity and sustainability for public mobility systems that are crucial to large facilities, and doing so using electrified, energy efficient technology. Using airports as an example, the rapid growth in air travel demand has led to facility expansions and congested terminals, which directly impacts equity (e.g., increased challenges for Passengers with Reduced Mobility [PRMs]) and sustainability—both of which are important metrics often overlooked during the engineering design process.

Accurate evaluation of vehicles' transient total power requirement helps achieving further improvements in vehicle fuel efficiency. When operated, the air-conditioning (A/C) system is the largest auxiliary load on a vehicle, therefore accurate evaluation of the load it places on the vehicle's engine and/or energy storage system is especially important. Vehicle simulation models, such as "Autonomie," have been used by OEMs to evaluate vehicles' energy performance. However, the load from the A/C system on the engine or on the energy storage system has not always been modeled in sufficient detail. A transient A/C simulation tool incorporated into vehicle simulation models would also provide a tool for developing more efficient A/C systems through a thorough consideration of the transient A/C system performance. The dynamic system simulation software MATLAB/Simulink® is frequently used by vehicle controls engineers to develop new and more efficient vehicle energy system controls.

Bioregenerative systems for removal of gaseous contaminants are desired for long-term space missions to reduce the equivalent system mass of the air cleaning system. This paper describes an innovative design of a new biofiltration test lab for investigating the capability of biofiltration process for removal of ersatz multi-component gaseous streams representative of spacecraft contaminants released during long-term space travel. The lab setup allows a total of 24 bioreactors to receive identical inlet waste streams at stable contaminant concentrations via use of permeations ovens, needle valves, precision orifices, etc. A unique set of hardware including a Fourier Transform Infrared (FTIR) spectrometer, and a data acquisition and control system using LabVIEW™ software allows automatic, continuous, and real-time gas monitoring and data collection for the 24 bioreactors. This lab setup allows powerful factorial experimental design.

Excessive vibration and poor controllability occur in many mobile fluid power applications, with negative consequences as concerns operators' health and comfort as well as machine safety and productivity. This paper addresses the problem of reducing oscillations in fluid power machines presenting a novel control technique of general applicability. Strong nonlinearities of hydraulic systems and the unpredictable operating conditions of the specific application (e.g. uneven ground, varying loads, etc.) are the main challenges to the development of satisfactory general vibration damping methods. The state of the art methods are typically designed as a function of the specific application, and in many cases they introduce energy dissipation and/or system slowdown. This paper contributes to this research by introducing an energy efficient active damping method based on feedback signals from pressure sensors mounted on the flow control valve block.

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.

This paper reviews some applications of lattice Boltzmann methods (LBM) to compute multiphase flows. The method is based on the solution of a kinetic equation which describes the evolution of the distribution of the population of particles whose collective behavior reproduces fluid behavior. The distribution is modified by particle streaming and collisions on a lattice. Modeling of physics at a mesoscopic level enables LBM to naturally incorporate physical properties needed to compute complex flows. In multiphase flows, the surface tension and phase segregation are incorporated by considering intermolecular attraction forces. Furthermore, the solution of the kinetic equations representing linear advection and collision, in which non-linearity is lumped locally, makes it parallelizable with relative ease. In this paper, a brief review of the lattice Boltzmann method relevant to engine sprays will be presented.

This paper describes a simulation approach for the modeling of tandem external gear pumps. A tandem gear pump is the combination of two pumps with a common drive shaft. Such design architecture finds application in certain automotive transmission systems. The model presented in this work is applicable for pumps with both helical and spur gears. The simulation model is built on the HYGESim (HYdraulic GEars machines Simulator) previously developed by the authors for external spur gear units. In this work, the model formulation is properly extended to the capabilities of simulating helical gears. Starting directly from the CAD drawings of the unit, the fluid-dynamic model solves the internal instantaneous tooth space volume pressures and the internal flows following a lumped parameter approach. The simulation tool considers also the radial micro-motion of the gears, which influences the internal leakages and the features of the meshing process.

The small-displacement direct-injection (DI) diesel engine is a prime candidate for future transportation needs because of its high thermal efficiency combined with near term production feasibility. Ford Motor Company and FEV Engine Technology, Inc. are working together with the US Department of Energy to develop a small displacement DI diesel engine that meets the key challenges of emissions, NVH, and power density. The targets for the engine are to meet ULEV emission standards while maintaining a best fuel consumption of 200g/kW-hr. The NVH performance goal is transparency with state-of-the-art, four-cylinder gasoline vehicles. Advanced features are required to meet the ambitious targets for this engine. Small-bore combustion systems enable the downsizing of the engine required for high fuel economy with the NVH advantages a four- cylinder has over a three-cylinder engine.

Battery electric vehicles (BEVs) offer the potential to reduce both oil imports and greenhouse gas emissions, but high upfront costs, battery-limited vehicle range, and concern over high battery replacement costs may discourage potential buyers. A subscription model in which a service provider owns the battery and supplies access to battery swapping infrastructure could reduce upfront and battery replacement costs with a predictable monthly fee, while expanding BEV range. Assessing the costs and benefits of such a proposal are complicated by many factors, including customer drive patterns, the amount of required infrastructure, battery life, etc. The National Renewable Energy Laboratory has applied its Battery Ownership Model to compare the economics and utility of BEV battery swapping service plan options to more traditional direct ownership options.

In this paper, a wall-modified interactive flamelet model is developed for improving the modeling of Diesel combustion. The objective is to include the effects of wall heat loss on the transient flame structure. The essential idea is to compute several flamelets with several representative enthalpy defects which account for wall heat loss. Then, the averaged flamelet profile can be obtained through a linear fit between the flamelets according to the enthalpy defect of the local gas which results from the wall heat loss. The enthalpy defect is estimated as the difference between the enthalpy in a flamelet without wall heat loss, which would correspond to the enthalpy in the gas without wall heat loss, and the gas with wall heat loss. The improved model is applied to model combustion in a Diesel engine. In the application, two flamelets, one without wall heat loss and one with wall heat loss, are considered.