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This investigation was aimed at measuring the relative performance of two spray-guided, single-cylinder, spark-ignited direct-injected (SIDI) engine combustion system designs. The first utilizes an outwardly-opening poppet, piezo-actuated injector, and the second a conventional, solenoid operated, inwardly-opening multi-hole injector. The single-cylinder engine tests were limited to steady state, warmed-up conditions. The comparison showed that these two spray-guided combustion systems with two very different sprays had surprisingly close results and only differed in some details. Combustion stability and smoke emissions of the systems are comparable to each other over most of the load range. Over a simulated Federal Test Procedure (FTP) cycle, the multi-hole system had 15% lower hydrocarbon and 18% lower carbon monoxide emissions.

Fuel chemistry plays a crucial role in the continued reduction of particulate emissions (PE) and cleaner air quality from vehicles and equipment powered by internal combustion engines (ICE). Over the past ten years, there have been great improvements in predictive particulate emissions indices (correlative mathematical models) based on the fuel’s composition. Examples of these particulate indices (PI) are the Honda Particulate Matter Index (PMI) and the General Motors Particulate Evaluation Index (PEI). However, the analytical chemistry lab methods used to generate data for these two PI indices are very time-consuming. Because gasoline can be mixtures of hundreds of hydrocarbon compounds, these lab methods typically include the use of the high resolution chromatographic separation techniques such as detailed hydrocarbon analysis (DHA), with 100m chromatography columns and long (3 - 4 hours) analysis times per sample.

A pilot study was performed to explore the effects of PM Index, low and high molecular weight aromatics, and ethanol content on particulate matter (PM) emissions from light-duty Tier 2 gasoline vehicles. Four test vehicles from model years 2007-2009 were tested on seven fuels spanning PM Index values from 0.9 to 2.7, aromatic content from 14 to 38%, and ethanol content from 0 to 15%. Three of the test vehicles were port fuel injected (PFI) while the fourth featured gasoline direct injection (GDI). In an earlier program, two of the PFI vehicles demonstrated high sensitivity of PM emissions to fuel property changes while the third showed low sensitivity. The sensitivity of the GDI vehicle to fuel property changes was not known prior to this study. The vehicles were tested over the LA92 and US06 test cycles at 24°C (75°F). PM and regulated gaseous emissions were measured by test phase. Second-by-second tailpipe soot emissions were measured using the AVL Micro Soot Sensor.

As part of the U.S. Environmental Protection Agency (U.S. EPA) “Midterm Evaluation of Light-duty Vehicle Standards for Model Years 2022-2025 [1]”, the U.S. EPA is evaluating engines and assessing the effectiveness of future engine technologies for reducing CO2 emissions. Such assessments often require significant development time and resources in order to optimize intake and exhaust cam variable valve timing (VVT), exhaust gas recirculation (EGR) flow rates, and compression ratio (CR) changes. Mazda SkyActiv-G spark-ignition (SI) engines were selected by EPA for an internal engine development program based upon their high geometric compression ratio (14:1 in Europe and Japan, 13:1 in North America) and their use of a flexible valve train configuration with electro-mechanical phasing control on the intake camshaft. A one-dimensional GT-Power engine model was calibrated and validated using detailed engine dynamometer test data [2] from 2.0L and 2.5L versions of the SkyActiv-G engine.

Homogenous charge compression ignition (HCCI) engines offer a great potential in achieving high thermal efficiency and extremely low NOx at the same time. However, control of combustion phasing over a wide speed and load range has been a challenge, especially during transient operations. This paper describes work conducted at the National Vehicle and Fuel Emissions Laboratory, which explores the potential use of an HCCI engine as a power plant for a hybrid vehicle. A four-cylinder, 1.9 L commercial diesel engine was modified to operate with port-injected regular grade gasoline in HCCI mode. The combustion phasing is controlled by a combination of boost, EGR and thermal management as a function of engine speed and load. As a stand-alone unit, the engine has demonstrated a wide operation range with efficiency like that of a diesel engine and NOx below 0.2 g/kWh. At room temperature, the engine starts in SI mode and then transitions to HCCI in about 25 seconds.

In the previous research1), the authors discovered that the sudden pressure increase phenomenon in diesel particulate filter (DPF) was a result of soot collapse inside DPF channels. The proposed hypothesis for soot collapse was a combination of factors such as passive regeneration, high humidity, extended soak period, high soot loading and high exhaust flow rate. The passive regeneration due to in-situ NO2 and high humidity caused the straw like soot deposited inside DPF channels to take a concave shape making the collapse easier during high vehicle acceleration. It was shown that even if one of these factor was missing, the undesirable soot collapse and subsequent back pressure increase did not occur. Currently, one of the very popular NOx reduction technologies is the Selective Catalytic Reduction (SCR) on Filter which does not have any platinum group metal (PGM) in the washcoat.

The paper presents the main results of a study on the simulation of energy efficient management of on-board electric and thermal systems for a medium-size passenger vehicle featuring a parallel-hybrid diesel powertrain with a high-voltage belt alternator starter. A set of advanced technologies has been considered on the basis of very aggressive fuel economy targets: base-engine downsizing and friction reduction, combustion optimization, active thermal management, enhanced aftertreatment and downspeeding. Mild-hybridization has also been added with the goal of supporting the downsized/downspeeded engine performance, performing energy recuperation during coasting phases and enabling smooth stop/start and acceleration. The simulation has implemented a dynamic response to the required velocity and manual gear shift profiles in order to reproduce real-driver behavior and has actuated an automatic power split between the Internal Combustion Engine (ICE) and the Electric Machine (EM).

The diesel particulate filters (DPF) are considered the most robust technologies for particle emission reduction both in terms of mass and number. On the other hand, the increase of the backpressure in the exhaust system due to the accumulation of the particles in the filter walls leads to an increase of the engine fuel consumption and engine power reduction. To limit the filter loading, and the backpressure, a periodical regeneration is needed. Because of the growing interest about particle emission both in terms of mass, number and size, it appears important to monitor the evolution of the particle mass and number concentrations and size distribution during the regeneration of the DPFs. For this matter, in the presented work the regeneration of a catalyzed filter was fully analyzed. Particular attention was dedicated to the dynamic evolution both of the thermodynamic parameters and particle emissions.

This paper examines the pace at which manufacturers have added certain powertrain technology into new vehicles from model year 1975 to the present. Based on data from the EPA's Light-Duty Automotive Technology, Carbon Dioxide Emissions, and Fuel Economy Trends database [1], the analysis will focus on several key technologies that have either reached a high level of penetration in light duty vehicles, or whose use in the new vehicle fleet has been growing in recent years. The findings indicate that individual manufacturers have, at times, implemented new technology across major portions of their new vehicle offerings in only a few model years. This is an important clarification to prior EPA analysis that indicated much longer adoption times for the industry as a whole. This new analysis suggests a technology penetration paradigm where individual manufacturers have a much shorter technology penetration cycle than the overall industry, due to “sequencing” by individual manufacturers.

As the proliferation of downsized boosted engines continues, it becomes increasingly important to understand how engine and vehicle hardware impact vehicle transient response. Several different methodologies can be used to understand hardware impacts, such as vehicle testing, 0-D vehicle models, and constant engine speed load steps. The next evolution of predicting vehicle transient response is to transition to a system level vehicle analysis by coupling a detailed engine model, utilizing crank angle resolved calculations, with a simple vehicle model. This allows for the evaluation of engine and vehicle hardware effects on vehicle acceleration and the rate of change of vehicle acceleration, or jerk, and the tradeoffs that can be made between the hardware in early program development. By comparing this system level vehicle model to the different methodologies, it can be shown that a system level vehicle analysis allows for higher fidelity evaluations of vehicle transient response.

Battery Electric Vehicles (BEVs) are becoming more competitive day by day to achieve maximum peak power and energy requirement. This poses challenges to the design of Thermal Interface Material (TIM) which maintains the cell temperature and ensure retention of cell and prevent electrolyte leak under different crash loads. TIM can be in the form of adhesives, gels, gap fillers. In this paper, TIM is considered as structural, and requires design balance with respect to thermal and mechanical requirements. Improving structural strength of TIM will have negative impact on its thermal conductivity; hence due care needs to be taken to determine optimal strength that meets both structural and thermal performance. During various crash conditions, due to large inertial force of cell and module assembly, TIM is undertaking significant loads on tensile and shear directions. LS-DYNA® is used as simulation solver for performing crash loading conditions and evaluate structural integrity of TIM.

In-use, light-duty vehicles were recruited in Cary, North Carolina for emissions testing on a transportable dynamometer in 1999. Two hundred forty-eight vehicles were tested in as received condition using the IM240 driving cycle. The study was conducted in two phases, a summer and winter phase, with half of the vehicles recruited during each phase. Regulated emissions, PM10, carbonaceous PM, aldehydes and ketones were measured for every test. PM2.5, individual volatile hydrocarbons, polycyclic aromatic hydrocarbons, sterane and hopane emissions were measured from a subset of the vehicles. Average light-duty gasoline PM10 emission rates increased from 6.5 mg/mi for 1993-97 vehicles to 53.8 mg/mi for the pre-1985 vehicles. The recruited fleet average, hot-stabilized IM240 PM10 emission rate for gasoline vehicles was 19.0 mg/mi.

The impact of gasoline composition on vehicle particulate emissions response has been widely investigated and documented. Correlation equations between fuel composition and particulate emissions have also been documented, e.g. Particulate Matter Index (PMI) and Particulate Evaluation Index (PEI). Vehicle PM/PN emissions correlate very well with these indices. In a previous paper, global assessment with PEI on fuel sooting tendency was presented [1]. This paper will continue the previous theme by the authors, and cover China gasoline in more detail. With air pollution an increasing concern, along with more stringent emission requirements in China, both OEMs and oil industries are facing new challenges. Emissions controls require a systematic approach on both fuels and vehicles. Chinese production vehicle particulate emissions for a range of PEI fuels are also presented.

Low-temperature gasoline combustion (LTGC) engines can provide high efficiencies and extremely low NOx and particulate emissions, but controlling the combustion timing remains a challenge. This paper explores the potential of Partial Fuel Stratification (PFS) to provide fast control of CA50 in an LTGC engine. Two different compression ratios are used (CR=16:1 and 14:1) that provide high efficiencies and are compatible with mixed-mode SI-LTGC engines. The fuel used is a research grade E10 gasoline (RON 92, MON 85) representative of a regular-grade market gasoline found in the United States. The fuel was supplied with a gasoline-type direct injector (GDI) mounted centrally in the cylinder. To create the PFS, the GDI injector was pulsed twice each engine cycle. First, an injection early in the intake stroke delivered the majority of the fuel (70 - 80%), establishing the minimum equivalence ratio in the charge.

The Particulate Matter Index (PMI) is a tool that provides an indication of a fuel’s tendency to produce Particulate Matter (PM) emissions. Currently, the index is being used by various fuel laboratories and the Automotive OEMs as a tool to understand the gasoline fuel’s impact on both PM from engine hardware and vehicle-out emissions. In addition, a newer index that could be used to give an indication of the PM tendency of the gasoline range fuels, called the Particulate Evaluation Index (PEI), is shown to have a good correlation to PMI. The data used in those indices are collected from chemical analytical methods. This paper will compare gas chromatography (GC) methods used by three laboratories and discuss how the different techniques may affect the PMI and PEI calculation.

The U.S. Environmental Protection Agency, U.S. Department of Transportation's National Highway and Traffic Safety Administration, and the California Air Resources Board have recently released proposed new regulations for greenhouse gas emissions and fuel economy for light-duty vehicles and trucks in model years 2017-2025. These proposed regulations intend to significantly reduce greenhouse gas emissions and increase fleet fuel economy from current levels. At the fleet level, these rules the proposed regulations represent a 50% reduction in greenhouse gas emissions by new vehicles in 2025 compared to current fleet levels. At the same time, global growth, especially in developing economies, should continue to drive demand for crude oil and may lead to further fuel price increases. Both of these trends will therefore require light duty vehicles (LDV) to significantly improve their greenhouse gas emissions over the next 5-15 years to meet regulatory requirements and customer demand.

Internal combustion engine (IC engine) vehicles are commonly used for transportation due to their versatility. Due to this, efficiency in design process of IC engines is critical for the industry. To assess performance capabilities of an IC engine, thermal predictions are of utmost consequence. This study describes a computational method based on unsteady Reynolds-averaged Navier–Stokes equations that resolves the gas–liquid interface to examine the unsteady single phase/multiphase flow and heat transfer in a 4-cylinder Inline (i-4) engine. The study considers all important parts of the engine i.e., pistons, cylinder liners, head, block etc. The study highlights the ease of capturing complex and intricate flow paths with a robust mesh generation tool in combination with a robust high-fidelity interface capturing VOF (Volume-of-Fluid) scheme to resolve the gas-liquid interfaces.

This study brings to forefront the analysis capability of CFD for the oil-cooling of an Electric-Motor (E-Motor) powering an automobile. With the rapid increase in electrically powered vehicle, there is an increasing need in the CFD modeling community to perform virtual simulations of the E-Motors to determine the viability of the designs and their performance capabilities. The thermal predictions are extremely vital as they have tremendous impact on the design, spacing and sizes of these motors. In this paper, with the Simerics, Inc. software, Simerics-MP+®, a complete three dimensional CFD with conjugate heat transfer CHT model of an Electric Motor, including all the important parts like the windings, rotor and stator laminate, endrings etc. is created. The multiphase Volume of Fluid (VOF) approach is used to model the oil flow inside this motor.

Several predictive equations based on the chemical composition of gasoline have been shown to estimate the particulate emissions of light-duty, internal combustion engine (ICE) powered vehicles and are reviewed in this paper. Improvements to one of them, the PEISimDis equation are detailed herein. The PEISimDis predictive equation was developed by General Motor’s researchers in 2022 based on two laboratory gas chromatography (GC) analyses; Simulated Distillation (SimDis), ASTM D7096 and Detailed Hydrocarbon Analysis (DHA), ASTM D6730. The DHA method is a gas chromatography mass spectroscopy (GC/MS) methodology and provides the detailed speciation of the hundreds of hydrocarbon species within gasoline. A DHA’s aromatic species from carbon group seven through ten plus (C7 – C10+) can be used to calculate a Particulate Evaluation Index (PEI) of a gasoline, however this technique takes many hours to derive because of its long chromatography analysis time.

There has been an increasing interest in exploring the potential to reduce energy consumption of future connected and automated vehicles. People have extensively studied various eco-driving implementations that leverage preview information provided by on-board sensors and connectivity, as well as the control authority enabled by automation. Quantitative real-world evaluation of eco-driving benefits is a challenging task. The standard regulatory driving cycles used for measuring exhaust emissions and fuel economy are not truly representative of real-world driving, nor for capturing how connectivity and automation might influence driving trajectories. To adequately consider real-world driving behavior and potential “off-cycle” impacts, this paper presents four collaborative evaluation methods: large-scale simulation, in-depth simulation, vehicle-in-the-loop testing, and vehicle road testing.