Search Results

Obtaining and maintaining a stratified charge in a practical engine is a difficult problem. Consequently, many approaches have been proposed and reported in the scientific and patent literature. In attempting to assess the most profitable approach for future development work, it is important to group together similar approaches so that one can study their performance as a group. Making such a classification has the additional advantage of helping to standardize terminology used by different investigators. With this thought in mind, a literature study was made and a proposed classification chart prepared for the different engine combustion systems reported in the literature. For the sake of completeness, the finally proposed classification chart includes homogeneous combustion engines as well as heterogeneous combustion engines. Because of their similarity of combustion, rotary engines such as the Wankel engine are considered as “reciprocating” although gas turbines are not included.

Electrification is the well-accepted solution to address carbon emissions and modernize vehicle controls. Batteries play a critical in the journey of electrification and modernization with battery voltage prediction as the foundation for safe and efficient operation. Due to its strong dependency on prior information, battery voltage was estimated with recurrent neural network methods in the recent literatures exploring a variety of deep learning techniques to estimate battery behaviors. In these studies, standard recurrent neural networks, gated recurrent units, and long-short term memory are popular neural network architectures under review. However, in most cases, each neural network architecture is individually assessed and therefore the knowledge about comparative study among three neural network architecture is limited. In addition, many literatures only studied either the dynamic voltage response or the voltage relaxation.

A computer program which rapidly calculates the equilibrium mole fractions and the partial derivatives of the mole fractions with respect to temperature, pressure and equivalence ratio for the products of combustion of any hydrocarbon fuel and air is described. A subroutine is also given which calculates the gas constant, enthalpy, internal energy and the partial derivatives of these with respect to temperature, pressure and equivalence ratio. Some examples of the uses of the programs are also given.

One of the major challenges in multiobjective, multidisciplinary design optimization (MDO) is the long computational time required in evaluating the new designs' performances. To shorten the cycle time of product design, a data mining-based strategy is developed to improve the efficiency of heuristic optimization algorithms. Based on the historical information of the optimization process, clustering and classification techniques are employed to identify and eliminate the low quality and repetitive designs before operating the time-consuming design evaluations. The proposed method improves design performances within the same computation budget. Two case studies, one mathematical benchmark problem and one vehicle side impact design problem, are conducted as demonstration.

The results of two derivations relating to the fuel economy of hybrid-electric vehicles (vehicles which employ both a heat engine and electric drive system) are presented and their use is illustrated through the examples of the University of Wisconsin and TRW Systems Group hybrid-electric vehicles. The method of mileage estimation employs a specific fuel-consumption versus torque-speed map for the heat engine under study and knowledge of the hybrid-vehicle dynamics and road-load power. The method is easily extended to estimation of emission reductions through use of specific-emission-production versus torque-speed maps and is applicable to hybrid vehicles with other than electrical energy-storage systems.

Analytical models (math or computer simulation models) are typically built on the basis of many assumptions and simplifications and hence model prediction could be inaccurate in intended applications. Model validation is thus critical to quantify and improve the degree of accuracy of these models. So far, little work considers model validation for various design configurations so that model prediction is accurate in the intended design space. Furthermore, there is a lack of effective approaches that can be used to quantify model accuracy considering different number of experimental data. To overcome these limitations, objective of this paper is to develop a model validation approach for various design configurations with a reference metric for model accuracy check considering different number of experimental data.

Particle swarm optimization (PSO) is a relatively new stochastic optimization algorithm and has gained much attention in recent years because of its fast convergence speed and strong optimization ability. However, PSO suffers from premature convergence problem for quick losing of diversity. That is to say, if no particle discovers a new superiority position than its previous best location, PSO algorithm will fall into stagnation and output local optimum result. In order to improve the diversity of basic PSO, design of experiment technique is used to initialize the particle swarm in consideration of its space-filling property which guarantees covering the design space comprehensively. And the optimization procedure of PSO is divided into two stages, optimization stage and improving stage. In the optimization stage, the basic PSO initialized by Optimal Latin hypercube technique is conducted.

Pending reductions in light duty vehicle PM emissions standards from 10 to 3 mg/mi and below will push the limits of the gravimetric measurement method. At these levels the PM mass collected approaches the mass of non-particle gaseous species that adsorb onto the filter from exhaust and ambient air. This introduces an intrinsic lower limit to filter based measurement that is independent of improvements achieved in weighing metrology. The statistical variability of back-up filter measurements at these levels makes them an ineffective means for correcting the adsorption artifact. The proposed subtraction of a facility based estimate of the artifact will partially alleviate the mass bias from adsorption, but its impact on weighing variability remains a problem that can reach a significant fraction of the upcoming 3 and future 1 mg/mi standards. This paper proposes an improved PM mass method that combines the gravimetric filter approach with real time aerosol measurement.

The largest contribution to engine rubbing friction is made by the piston and piston rings running in the cylinder liner. The magnitude and characteristics of the friction behaviour and the influence on these of factors such as surface roughness, piston design and lubricant properties are of keen interest. Investigating presents experimental challenges, including potential problems of uncontrolled build-to-build variability when component changes are made. These are addressed in the design of a new motored piston and floating liner rig. The design constrains transverse movement of a single liner using cantilevered mounts at the top and bottom. The mounts and two high stiffness strain gauged load cells constrain vertical movement. The outputs of the load cells are processed to extract the force contribution associated with friction. The liner, piston and crankshaft parts were taken from a EuroV-compliant, HPCR diesel engine with a swept capacity of 550cc per cylinder.

Design optimization methods are commonly used for weight reduction subjecting to multiple constraints in automotive industry. One of the major challenges remained is to deal with a large number of design variables for large-scale design optimization problems effectively. In this paper, a new approach based on fuzzy rough set is proposed to address this issue. The concept of rough set theory is to deal with redundant information and seek for a reduced design variable set. The proposed method first exploits fuzzy rough set to screen out the insignificant or redundant design variables with regard to the output functions, then uses the reduced design variable set for design optimization. A vehicle body structure is used to demonstrate the effectiveness of the proposed method and compare with a traditional weighted sensitivity based main effect approach.

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.

Fine-wire resistance thermometers were used to measure compression gas temperatures in a motoring (nonfiring) cycle CFR engine. Temperature versus crankangle curves were obtained for the compression and expansion strokes by means of tungsten wires ranging in diameter from 0.15–1.00 mils and at speeds from 600–1800 rpm. The results were compared with the infrared pyrometer; the peak temperature and peak crankangle lags were determined as a function of the wire diameter and engine speed. Attempts to evaluate the instantaneous energy balance around the wire resulted in a negative heat transfer coefficient, for which no current satisfactory explanation is available, although other observers have reported similar phenomena. The tungsten resistance thermometer is simple to build, easy to install, and requires no modification of the engine block for use during motoring. Thus, it is suitable for comparing the compression temperatures of different design engines.

Cycle-to-cycle variation in combustion phasing and combustion rate cause knock to occur differently in every cycle. This is found to be true even if the end gas thermo-chemical time history is the same. Three cycles are shown that have matched combustion phasing, combustion rate, and time of knock onset, but have knock intensity that differs by a factor of six. Thus, the prediction of knock intensity must include a stochastic component. It is shown that there is a relationship between the maximum possible knock intensity and the unburned fuel energy at the time of knock onset. Further, for a small window of unburned energy at knock onset, the probability density function of knock intensity is self similar when scaled by the 95th percentile of the cumulative distribution, and log-normal in shape.

The development of a high speed, multichannel data acquisition system is described. A precision magnetic tape recorder is used to record analog data from highly transient phenomena. Analog-to-digital data conversion is performed on a hybrid computer and the digitized data is processed using large, high speed digital computers. A detailed example of the application of the system to the measurement of rates-of-injection, rates-of-heat release, and instantaneous rates-of-heat transfer from the cylinder gases to the cylinder walls in a high speed open-chamber diesel engine is presented.

We present research in progress to develop and implement a transportable instrumentation package (TIP) to collect driver data in a vehicle. The overall objective of the project is to investigate the symbiotic relationship between humans and their vehicles. We first describe the state-of-art technologies to build the components of TIP that meet the criteria of ease of installation, minimal interference with driving, and sufficient signals to monitor driver state and condition. This method is a viable alternative to current practice which is to first develop a fully instrumented test vehicle, often at great expense, and use it to collect data from each participant as he/she drives a prescribed route. Another practice, as for example currently being used in the SHRP-2 naturalistic driving study, is to install the appropriate instrumentation for data collection in each individual's vehicle, often requiring several hours.

Modeling ignition kernel development in spark ignition engines is crucial to capturing the sources of cyclic variability, both with RANS and LES simulations. Appropriate kernel modeling must ensure that energy transfer from the electrodes to the gas phase has the correct timing, rate and locations, until the flame surface is large enough to be represented on the mesh by the G-Equation level-set method. However, in most kernel models, geometric details driving kernel growth are missing: either because it is described as Lagrangian particles, or because its development is simplified, i.e., down to multiple spherical flames. This paper covers the geometric aspects of kernel development, which makes up the core of a Triangulated Lagrangian Ignition Kernel model. One (or multiple, if it restrikes) spark channel is initialized as a one-dimensional Lagrangian particle thread.

The long-term goal of this work is to develop a conceptual model for multiple injections of diesel jets. The current work contributes to that effort by performing a detailed modeling investigation into mechanisms that are predicted to control 1st and 2nd stage ignition in single-pulse diesel (n-dodecane) jets under different conditions. One condition produces a jet with negative ignition dwell that is dominated by mixing-controlled heat release, and the other, a jet with positive ignition dwell and dominated by premixed heat release. During 1st stage ignition, fuel is predicted to burn similarly under both conditions; far upstream, gases at the radial-edge of the jet, where gas temperatures are hotter, partially react and reactions continue as gases flow downstream. Once beyond the point of complete fuel evaporation, near-axis gases are no longer cooled by the evaporation process and 1st stage ignition transitions to 2nd stage ignition.

Exhaust gas recirculation (EGR) coolers are commonly used in diesel engines to reduce the temperature of recirculated exhaust gases in order to reduce NOx emissions. The presence of a cool surface in the hot exhaust causes particulate soot deposition as well as hydrocarbon and water condensation. Fouling experienced through deposition of particulate matter and hydrocarbons results in degraded cooler effectiveness and increased pressure drop. In this study, a visualization test setup is designed and constructed so that the effect of water condensation on the deposit formation and growth at various coolant temperatures can be studied. A water-cooled surrogate rectangular channel is employed to represent the EGR cooler. One side of the channel is made of glass for visualization purposes. A medium duty diesel engine is used to generate the exhaust stream.

Homogeneous low temperature combustion is believed to be a promising approach to resolve the conflict of goals between high efficiency and low exhaust emissions. Disadvantageously for this kind of combustion, the whole process depends on chemical kinetics and thus is hard to control. Reactivity controlled combustion can help to overcome this difficulty. In the so-called RCCI (reactivity controlled compression ignition) combustion concept a small amount of pilot diesel that is injected directly into the combustion chamber ignites a highly diluted gasoline-air mixture. As the gasoline does not ignite without the diesel, the pilot injection timing and the ratio between diesel and gasoline can be used to control the combustion process. A phenomenological multi-zone model to predict RCCI combustion has been developed and validated against experimental and 3D-CFD data. The model captures the main physics governing ignition and combustion.

ACOUSTOMIZE™ is a new method of acoustic evaluation used for the purpose of understanding and optimizing NVH performance of vehicles. The following paper documents a case study of the ACOUSTOMIZE™ test methodology on a passenger car BIW. This study includes an analysis of noise flow through BIW locations, a comparison of noise sound levels through BIW cavities with and without a sound treatment package and a comparison of the original cavity sealing design package consisting of baffles, tapes and baggies to low density polyurethane NVH Foam. The results of the study show detection of complex BIW pass throughs that the body leakage test (BLT) was not able to find. In addition, the data shows improved noise reduction with the low density polyurethane foam versus the original cavity sealing design package.