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Due to the rising costs of fuel and increasingly stringent regulations, auto makers are in need of technology to enable more fuel-efficient powertrain technologies to be introduced to the marketplace. Such powertrains must not sacrifice performance, safety or driver comfort. Today's engine and powertrain manufacturers must, therefore, do more with less by achieving acceptable vehicle performance while reducing fuel consumption. One effective method to achieve this is the extreme downsizing of current direct injection spark ignited (DISI) engines through the use of high levels of boosting and cooled exhaust gas recirculation (EGR). Key challenges to highly downsized gasoline engines are retarded combustion to prevent engine knocking and the necessity to operate at air/fuel ratios that are significantly richer than the stoichiometric ratio.

The benchmarking study described in this paper uses data from chassis dynamometer testing to determine the efficiency and operation of vehicle driveline components. A robust test procedure was created that can be followed with no a priori knowledge of component performance, nor additional instrumentation installed in the vehicle. To develop the procedure, a 2013 Chevrolet Malibu was tested on a chassis dynamometer. Dynamometer data, emissions data, and data from the vehicle controller area network (CAN) bus were used to construct efficiency maps for the engine and transmission. These maps were compared to maps of the same components produced from standalone component benchmarking, resulting in a good match between results from in-vehicle and standalone testing. The benchmarking methodology was extended to a 2013 Mercedes E350 diesel vehicle. Dynamometer, emissions, and CAN data were used to construct efficiency maps and operation strategies for the engine and transmission.

As part of the U.S. Environmental Protection Agency’s (EPA’s) continuing assessment of advanced light-duty automotive technologies in support of regulatory and compliance programs, the National Vehicle Fuels and Emissions Laboratory has benchmarked multiple transmissions to determine their efficiency during operation. The benchmarking included a modified “coastdown test,” which measures transmission output drag as a function of speed while in neutral. The transmission drag data can be represented as a second-order expression, like that used for vehicle coastdown test results, as F0 + F1V + F2V2, where V is the vehicle velocity. When represented in this fashion, the relationships among the three coefficients were found to be highly predictable. The magnitude of these coefficients can be quite large, and for some tested transmissions the deviation between the quadratic regression and the measured drag at individual velocities can be significant.

To make an HCCI engine as a useful commercial product, the engine has to be capable of performing quick transients in a large operating range, especially in vehicle applications. HCCI combustion is kinetically controlled and has to be operated properly between two limits: misfire and knock. To achieve the correct state, the right amount of fuel/air/EGR has to be inducted into the cylinder. The amounts and ratios of the three components are highly dependent on other variables as operating conditions change. It is unrealistic and unreliable to predict the right combination of these variables without principal component analysis. Thus, the optimal response control path has to be based on the quality of the previous combustion event as well as the direction and the rate of transition.

Lean operating natural gas heavy duty applications have advantages in terms of lower CO2 and PM compared to Diesel applications. This makes operating heavy duty applications on natural gas attractive and currently, they do not have to implement an exhaust particulate filter. However, the challenge is controlling methane emissions over a range of vehicle operating conditions. Methane is extremely stable and light off occurs at temperatures above 400 °C, with high efficiency occurring >500 °C and requires high precious metal loaded catalysts in the range of 150 - 200 g/ft3. Under stoichiometric conditions, 500 °C can be met in many engine operating points however, for lean operating applications, the exhaust temperature can be significantly lower than 500 °C posing a significant challenge for exhaust catalytic CH4 control. This paper will discuss synthetic gas reactor study results using ozone in the feed gas to perform low temperature methane control.

Fourier Transform Infrared Spectroscopy (FT-IR) has been used to measure the exhaust emissions from vehicles during standard driving tests. Comparisons with conventional analyzers for modal tests have been made for the regulated species such as carbon monoxide (CO), nitrogen oxides (NOx) and total hydrocarbon (THC). The concentrations of methane, methanol and formaldehyde were also measured at one second time intervals during several driving tests. The average concentration values for these species were compared to the bag samples for several tests. Modal concentration curves were also calculated for MTBE, ETBE and several other species of interest. The results indicate FT-IR can be used for making modal measurements on the regulated species and non-regulated species in vehicle exhaust emissions. Several studies were performed to evaluate the long-term stability and sensitivity of FT-IR in actual test situations.

As part of its midterm evaluation of the 2022-2025 light-duty greenhouse gas (GHG) standards, the Environmental Protection Agency (EPA) has been acquiring fuel efficiency data from testing of recent engines and vehicles. The benchmarking data are used as inputs to EPA’s Advanced Light Duty Powertrain and Hybrid Analysis (ALPHA) vehicle simulation model created to estimate GHG emissions from light-duty vehicles. For complete powertrain modeling, ALPHA needs both detailed engine fuel consumption maps and transmission efficiency maps. EPA’s National Vehicle and Fuels Emissions Laboratory has previously relied on contractors to provide full characterization of transmission efficiency maps. To add to its benchmarking resources, EPA developed a streamlined more cost-effective in-house method of transmission testing, capable of gathering a dataset sufficient to broadly characterize transmissions within ALPHA.

An investigation has been carried out to examine the influence of up to 300 MPa injection pressure on engine performance and emissions. Experiments were performed on a 4 cylinder, 4 valve / cylinder, 4.5 liter John Deere diesel engine using the Ricardo Twin Vortex Combustion System (TVCS). The study was conducted by varying the injection pressure, Start of Injection (SOI), Variable Geometry Turbine (VGT) vane position and a wide range of EGR rates covering engine out NOx levels between 0.3 g/kWh to 2.5 g/kWh. A structured Design of Experiment approach was used to set up the experiments, develop empirical models and predict the optimum results for a range of different scenarios. Substantial fuel consumption benefits were found at the lowest NOx levels using 300 MPa injection pressure. At higher NOx levels the impact was nonexistent. In a separate investigation a Cambustion DMS-500 fast particle spectrometer, was used to sample and analyze the exhaust gas.

Internal combustion engines continue to grow more complex every day out of necessity. Legislation and increasing customer demand means that advanced technologies like variable valve actuation (VVA), multi-path exhaust gas recirculation (EGR), advanced boosting, and aftertreatment systems continue to drive ever-expanding requirements for engine control to improve performance, fuel economy, and reduce emissions. Therefore, controller development and implementation are becoming more costly, both in terms of time and the monetary investment in engine hardware. To help reduce these costs, a sophisticated tool chain has been created which allows a real-time, physical, crank-angle resolved one-dimensional (1D) engine model to be implemented on a rapid prototyping engine control unit (ECU) which is then used in the control strategy of a running engine. Model-based controllers have been developed and validated to perform as well as or better than controllers using traditional sensors.

This study is the second in a series of three EPA studies to investigate the effect of fuel reformulations and modifications on exhaust emissions. Both the first and second study in this series of studies were used to support the development of EPA's complex model for the certification of reformulated gasolines. Phase I of the study tested eight fuels on forty vehicles. This study, termed Phase II, tested twelve fuels on a separate fleet of 39 light-duty vehicles. The Phase II fuel parameters studied included Reid Vapor Pressure (RVP), the 50% and 90% evaporated distillation temperatures (T50 and T90), sulfur content, aromatics content, olefin content, oxygenate type and oxygen content. Measured exhaust emissions included total hydrocarbons (THC), oxides of nitrogen (NOx), carbon monoxide (CO), carbon dioxide (CO2), benzene, 1,3-butadiene, acetaldehyde and formaldehyde.

This study was the first of three EPA studies to investigate the effect of gasoline fuel parameters on hydrocarbon, nonmethane hydrocarbon, nitrogen oxides, benzene, formaldehyde, and acetaldehyde exhaust emissions of 1990 model year or equivalent vehicles. The fuel parameters tested in this program were oxygen concentration, Reid Vapor Pressure (RVP), ninety percent evaporative distillation temperature (T90), and sulfur concentration. Sulfur concentration was found to have the greatest effect on hydrocarbon and nitrogen oxide emissions. Increasing oxygen concentration and RVP reduction was found to reduce hydrocarbon emission more for high-emitting than normal-emitting vehicles. Oxygenate concentration was found to have a significant effect on aldehyde emissions.

Portable Emission Measurement Systems (PEMS) are used by the U.S. Environmental Protection Agency (EPA) to measure gaseous and particulate mass emissions from vehicles in normal, in-use, on-the-road operation to support many of its programs, including assessing mobile source emissions compliance, emissions factor assessment for in-use fleet modeling, and collection of in-use vehicle operational data to support vehicle simulation modeling programs. This paper discusses EPA’s use of Global Positioning System (GPS) measured altitude data and electronically logged vehicle speed data to provide real-world road grade data for use as an input into the Gamma Technologies GT-DRIVE+ vehicle model. The GPS measured altitudes and the CAN vehicle speed data were filtered and smoothed to calculate the road grades by using open-source Python code and associated packages.

EPA has been benchmarking engines and transmissions to generate inputs for use in its technology assessments supporting the Midterm Evaluation of EPA’s 2017-2025 Light-Duty Vehicle greenhouse gas emissions assessments. As part of an Atkinson cycle engine technology assessment of applications in light-duty vehicles, cooled external exhaust gas recirculation (cEGR) and cylinder deactivation (CDA) were evaluated. The base engine was a production gasoline 2.0L four-cylinder engine with 75 degrees of intake cam phase authority and a 14:1 geometric compression ratio. An open ECU and cEGR hardware were installed on the engine so that the CO2 reduction effectiveness could be evaluated. Additionally, two cylinders were deactivated to determine what CO2 benefits could be achieved. Once a steady state calibration was complete, two-cycle (FTP and HwFET) CO2 reduction estimates were made using fuel weighted operating modes and a full vehicle model (ALPHA) cycle simulation.

The Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) tool was created by EPA to evaluate the Greenhouse Gas (GHG) emissions of Light-Duty (LD) vehicles [1]. ALPHA is a physics-based, forward-looking, full vehicle computer simulation capable of analyzing various vehicle types combined with different powertrain technologies. The software tool is a MATLAB/Simulink based desktop application. The ALPHA model has been updated from the previous version to include more realistic vehicle behavior and now includes internal auditing of all energy flows in the model [2]. As a result of the model refinements and in preparation for the mid-term evaluation (MTE) of the 2022-2025 LD GHG emissions standards, the model is being revalidated with newly acquired vehicle data. This paper presents an analysis of the effects of varying the absolute and relative gear ratios of a given transmission on carbon emissions and performance.

The Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) tool was created by EPA to evaluate the Greenhouse Gas (GHG) emissions of Light-Duty (LD) vehicles [1]. ALPHA is a physics-based, forward-looking, full vehicle computer simulation capable of analyzing various vehicle types combined with different powertrain technologies. The software tool is a MATLAB/Simulink based desktop application. The ALPHA model has been updated from the previous version to include more realistic vehicle behavior and now includes internal auditing of all energy flows in the model [2]. As a result of the model refinements and in preparation for the mid-term evaluation (MTE) of the 2022-2025 LD GHG emissions standards, the model is being revalidated with newly acquired vehicle data.

The Advanced Light-Duty Powertrain and Hybrid Analysis tool was created by EPA to evaluate the Greenhouse Gas (GHG) emissions of Light-Duty (LD) vehicles. It is a physics-based, forward-looking, full vehicle computer simulator capable of analyzing various vehicle types combined with different powertrain technologies. The software tool is a freely-distributed, MATLAB/Simulink-based desktop application. Version 1.0 of the ALPHA tool was applicable only to conventional, non-hybrid vehicles and was used to evaluate off-cycle technologies such as air-conditioning, electrical load reduction technology and road load reduction technologies for the 2017-2025 LD GHG rule. The next version of the ALPHA tool will extend its modeling capabilities to include power-split and P2 parallel hybrid electric vehicles and their battery pack energy storage systems. Future versions of ALPHA will incorporate plug-in hybrid electric vehicle (PHEV) and electric vehicle (EV) architectures.

The Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) tool was created by EPA to evaluate the Greenhouse Gas (GHG) emissions of Light-Duty (LD) vehicles. It is a physics-based, forward-looking, full vehicle computer simulator capable of analyzing various vehicle types combined with different powertrain technologies. The software tool is a freely-distributed, MATLAB/Simulink-based desktop application. Version 1.0 of the ALPHA tool was applicable only to conventional, non-hybrid vehicles and was used to evaluate off-cycle technology such as air-conditioning, electrical load reduction technology and road load reduction technologies for the 2017-2025 LD GHG and Fuel Economy rule. The next version of the ALPHA tool extends its modeling capabilities to include power-split and P2 parallel hybrid electric vehicles and their battery pack energy storage systems. Future versions of ALPHA will incorporate plug-in hybrid electric vehicle (PHEV) and electric vehicle (EV) architectures.

Worldwide, Fuel Economy (FE) legislation increasingly influences vehicle and engine design, and drives friction reduction. The link between lubricant formulation and mechanical friction is complex and depends on engine component design and test cycle. This Motored Friction Tear Down (MFTD) study characterizes the friction within a 3.6L V6 engine under operating conditions and lubricant choices relevant to the legislated FE cycles. The high-fidelity MFTD results presented indicate that the engine is a low-friction engine tolerant of low viscosity oils. Experiments spanned four groups of engine hardware (reciprocating, crankshaft, valvetrain, oil pump), five lubricants (four candidates referenced against an SAE 0W-20) and five temperature regimes. The candidate lubricants explored the impact of base oil viscosity, viscosity modifier (VM) and friction modifier (FM) content.

This paper describes the features and capabilities of a comprehensive yet flexible computational tool ORBIT developed for analyzing journal bearings (e.g. connecting rod bearings and crankshaft bearings) in internal combustion engines. Several techniques for solving the hydrodynamic Reynolds Equation have been developed within this methodology which can be used appropriately by bearing designers/analysts depending on the level of detail required. Besides ideal circular bearings, this simulation tool also enables the analyst to consider the influence of a) non-circular journal bearing geometry, b) oil-feed holes/grooves, c) surface roughness, d) journal misalignment, e) rise in oil temperature and f) bearing elasticity effects (EHL) on bearing performance. The capabilities of the simulation code are demonstrated through a series of validation and case studies.

In preparation for the midterm evaluation (MTE) of the 2022-2025 Light-Duty Greenhouse Gas (LD GHG) emissions standards, the Environmental Protection Agency (EPA) is refining and revalidating their Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) tool using newly acquired data from model year 2013-2015 engines and vehicles. ALPHA is a physics-based, forward-looking, full vehicle computer simulation capable of analyzing various vehicle types with different powertrain technologies, showing realistic vehicle behavior, and auditing of all internal energy flows in the model. As part of the validation of ALPHA, the EPA obtained model year 2014 Dodge Chargers equipped with 3.6 liter V6 engines and either a NAG1 five-speed automatic transmission or an 845RE eight-speed automatic transmission.