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A fully instrumented Tesla Model 3 was used to collect thousands of hours of real-world automated driving data, encompassing both Autopilot and Full Self-Driving modes. This comprehensive dataset included vehicle operational parameters from the data busses, capturing details such as powertrain performance, energy consumption, and the control of advanced driver assistance systems (ADAS). Additionally, interactions with the surrounding traffic were recorded using a perception kit developed in-house equipped with LIDAR and a 360-degree camera system. We collected the data as part of a larger program to assess energy-efficient driving behavior of production connected and automated vehicles. One important aspect of characterizing the test vehicle is predicting its car-following behavior. Using both uncontrolled on-road tests and dedicated tests with a lead car performing set speed maneuvers, we tuned conventional adaptive cruise control (ACC) equations to fit the vehicle’s behavior.

The National Highway Traffic Safety Administration (NHTSA) plays a crucial role in guiding the formulation of Corporate Average Fuel Economy (CAFE) standards, and at the forefront of this regulatory process stands Argonne National Laboratory (Argonne). Argonne, a U.S. Department of Energy (DOE) research institution, has developed Autonomie—an advanced and comprehensive full-vehicle simulation tool that has solidified its status as an industry standard for evaluating vehicle performance, energy consumption, and the effectiveness of various technologies. Under the purview of an Inter-Agency Agreement (IAA), the DOE Argonne Site Office (ASO) and Argonne have assumed the responsibility of conducting full-vehicle simulations to support NHTSA's CAFE rulemaking initiatives. This paper introduces an innovative approach that hinges on a large-scale simulation process, encompassing standard regulatory driving cycles tailored to various vehicle classes and spanning diverse timeframes.

A multi-dimensional cathode spot generation model is proposed to study the interaction between the plasma arc and cathode surface of a spark plug during the ignition process. The model is focused on the instationary (high current) arc phase immediately following breakdown, and includes detailed physics for the phenomena during spot formation such as ion collision, thermal-field emission, and metal vaporization, to simulate the surface heat source, current density and surface pressure. The spot formation for a platinum cathode is simulated using the VOF (volume of fluid) model within FLUENT, where the local metal is melted and deformed by pressure differences on the surface. A random walk model has been integrated to consider the movement of the arc center, resulting in the formation of different types of spots.

An experimental study of the spark ignition process for SI engines was conducted to study spark plug erosion and the effect of breakdown voltage/energy on electrode surface deformation. The experiments were conducted outside of an engine, in both a pressurized constant volume optical chamber and in a high-pressure vessel heated within a furnace with gas temperatures as high as 730°C. J-gap spark plugs designed for natural gas engines were studied at elevated temperature and under a range of pressures to investigate electrode wear characteristics. Both iridium-alloy and platinum-alloy cathode (center electrode) and anode (ground strap) spark plugs were investigated. In addition, single spark events were performed on polished platinum cathode surfaces to allow the visualization of craters from individual spark events in order to quantify how their size and shape were affected by energy deposition and breakdown characteristics.

The establishment of Corporate Average Fuel Economy (CAFE) standards by the Energy Policy and Conservation Act (EPCA) of 1975 marked a pivotal moment in the automotive industry's pursuit of greater fuel efficiency. The responsibility for the development and enforcement of these standards was assigned to the U.S. Department of Transportation (DOT), with the National Highway Traffic Safety Administration (NHTSA) assuming a critical role in their oversight and implementation. In collaboration with Argonne National Laboratory (Argonne), supported by the U.S. Department of Energy (DOE), significant strides have been made in advancing fuel efficiency through the development of Autonomie, a leading full-vehicle simulation tool. Through an Inter-Agency Agreement between the DOE Argonne Site Office and Argonne, comprehensive full-vehicle simulations are conducted to support NHTSA's CAFE rulemaking processes.

A multi-dimensional model of the spark ignition process for SI engines was developed as a user defined function (UDF) integrated into the commercial engine simulation software CONVERGE CFD. The model simulates spark plasma movement in an inert flow environment without combustion. The UT model results were compared with experiments for arc movement in a crossflow and also compared with calorimeter measurements of thermal energy deposition under quiescent conditions. The arc motion simulation is based on a mean-free-path physical model to predict the arc movement given the contours of the crossflow velocity through the gap and the interaction of the spatially resolved electric field with the electrons making up the arc. A further development is the inclusion of a model for the thermal energy deposition of the arc as it is stretched by the interaction of the flow and the electric field.

Spark discharge properties were studied and characterized for varying gas compositions and spark plug geometries using a spark calorimeter and constant volume optical vessel. Two different 18 mm natural gas engine spark plugs were used in the experiments. All measurements were recorded under quiescent conditions and with a spark gap of 0.30 mm. The spark plug calorimeter was used for measuring thermal energy deposition to the gas for gas compositions of nitrogen, a stoichiometric mixture of nitrogen and methane, a stoichiometric mixture of nitrogen and methane diluted with 30% carbon dioxide by volume, and for air. Other measurements of interest included breakdown voltage, electrical energy delivered to the spark gap, electrical-to-thermal energy conversion efficiency, and spark duration, for pressures up to 28 bar at 300 K. The optical vessel was used for the combusting mixture of stoichiometric air and methane at pressures up to 28 bar.

The cold start process is critical to control the emissions in a gasoline direct injection (GDI) engine. However, the optimization is very challenging due to the transient behavior of the engine cold start. A series of engine simulations using CONVERGE CFD™ were carried out to show the detailed process in the very first firing event of a cold start. The engine operating parameters used in the simulations, such as the transient engine speed and the fuel rail pressure (FRP), came from companion experiments. The cylinder pressure traces from the simulations were compared with experiments to help validate the simulation model. The effects of variation of the transient parameters on in-cylinder mixture distribution and combustion are presented, including the effects of the rapidly changing engine speed, the slowly vaporized fuel due to the cold walls, and the low FRP during the first firing cycle of a 4-cylinder engine. Comparison was also made with non-transient steady state operation.

The arc characteristics and discharge behavior of a representative inductive spark ignition system were characterized with a spark plug calorimeter and a constant volume vessel used to create high-pressure crossflow velocities through the gap of the spark plug. A 14 mm diameter natural gas engine spark plug was used for the measurements. The discharges were into a non-combusting gas, primarily nitrogen. The spark plug calorimeter was used to determine the electrical-to-thermal energy conversion in the spark gap under quiescent conditions, while the constant volume vessel was used to study ignition arc structure in convective crossflows and imaged with a high-speed camera. Topics included the effect of crossflow velocity, pressure (up to 20 bar at 300 K), and gap distance on breakdown voltage, arc duration and delivered electrical energy. Also of interest was the amount of remaining electrical energy on the coil versus spark duration in a cross flow.

A multi-dimensional model of the spark ignition process for SI engines was developed as a user defined function (UDF) integrated into the commercial engine simulation software CONVERGE™ CFD. For the present research, the model simulated spark plasma development in an inert flow environment without combustion. The UT model results were then compared with experiments. The UT CONVERGE CFD-based model includes an electrical circuit sub-model that couples the primary and secondary sides of an inductive ignition system to predict arc voltage and current, from which the transient delivered electrical energy to the gap can be determined. Experimentally measured values of the arc resistance and spark plug calorimeter measurements of the efficiency of electrical to thermal energy conversion in the gap were used to determine the thermal energy delivered to the gas in the spark gap for different pressures and gap distances.

The Rotating Liner Engine (RLE) is a design concept for internal combustion engines, where the cylinder liner rotates at a surface speed of 2-4 m/s in order to assist piston ring lubrication. The metal-to-metal contact/boundary friction that exists close to the piston reversal area becomes a significant source of energy loss when the gas pressure that loads the piston rings and skirts is high. Reduction in mechanical friction has a direct impact on brake thermal efficiency. This paper describes fuel consumption measurements of our prototype single cylinder engine, compared to a baseline at idle. The reduction in fuel flow is of the order of 40% when extrapolated to a complete engine. The margin in friction reduction is expected to grow at increasing load, but reduce at increasing speeds. Our earlier models estimated idle fuel consumption reduction to about 25%, at full load about 3.5%, for a Heavy-Duty FTP 6.8 %, and may have been conservative.

Spark plug electrode heat transfer and its relationship with the thermal energy deposition from the spark plasma to the gas in the spark gap was studied under quiescent non-combusting conditions. The thermal energy deposition to the gas (N2) was measured with a spark plug calorimeter as a function of pressure, up to 30 bar. The measurements were carried out for two gap distances of 0.3 mm and 0.9 mm, for three nominally identical spark plugs having different electrode surface area and/or surface thermal conductivity. The unmodified baseline spark plug had a nickel center electrode (cathode) 2.0 mm in diameter, the first modified spark plug had both the ground and center electrodes shaved to a diameter of approximately 0.5 mm, and the second modified spark plug had copper inserts bonded to both electrodes. The experimental results were compared with multi-dimensional simulations of the conjugate heat transfer to the gas and to the metal electrodes, conducted using CONVERGE CFD.

In recent studies, optimal control has shown promise as a strategy for enhancing the energy efficiency of connected autonomous vehicles. To maximize optimization performance, it is important to accurately predict constraints, especially separation from a vehicle in front. This paper proposes a novel prediction method for forecasting the trajectory of the nearest preceding car. The proposed predictor is designed to produce short to medium-length speed trajectories using a locally weighted polynomial regression algorithm. The polynomial coefficients are trained by using two types of information: (1) vehicle-to-vehicle (V2V) messages transmitted by multiple preceding vehicles and (2) vehicle-to-infrastructure (V2I) information broadcast by roadside equipment. The predictor’s performance was tested in a multi-vehicle traffic simulation platform, RoadRunner, previously developed by Argonne National Laboratory.

A series of cold start experiments using a 2.0 liter gasoline turbocharged direct injection (GTDI) engine with custom controls and calibration were carried out using gasoline and iso-pentane fuels, to obtain the cold start emissions profiles for the first 5 firing cycles at an ambient temperature of 22°C. The exhaust gases, both emitted during the cold start firing and emitted during the cranking process right after the firing, were captured, and unburned hydrocarbon emissions (HC), CO, and CO2 on a cycle-by-cycle basis during an engine cold start were analyzed and quantified. The HCs emitted during gasoline-fueled cold starts was found to reduce significantly as the engine cycle increased, while CO and CO2 emissions were found to stay consistent for each cycle. Crankcase ventilation into the intake manifold through the positive-crankcase ventilation (PCV) valve system was found to have little effect on the emissions results.

The continuing growth of urban population centers has led to increased traffic congestion for which vehicles can spend considerable periods at low speed/low load and idle conditions. For light-duty diesel vehicles, these low load conditions are characterized by low engine exhaust temperatures (~100oC). Exhaust temperatures can be too low to maintain the activity of the catalytic exhaust aftertreatment devices (usually need >~200oC) which can lead to high emissions that contribute to deteriorating urban air quality. This study is a follow-on to two previous studies on the effects of throttling, post-injection, and cylinder deactivation (CDA) on light-duty diesel engine exhaust temperatures and emissions. The focus of the present study is on fuel consumption, exhaust temperatures, and emissions with and without cylinder deactivation or with fuel cutout, and the sensitivity to or effects of fuel rail pressure, along with observations of apparent idle engine friction.

The U.S. Department of Energy, Vehicle Technologies Office (U.S. DOE-VTO) has been developing more energy-efficient and environmentally friendly highway transportation technologies that would enable the United States to burn less petroleum on the road. System simulation is an accepted approach for evaluating the fuel economy potential of advanced (future) technology targets. U.S. DOE-VTO defines the targets for advancement in powertrain technologies (e.g., engine efficiency targets, battery energy density, lightweighting, etc.) Vehicle system simulation models based on these targets have been generated in Autonomie, reflecting the different EPA classifications of vehicles for different advanced timeframes as part of the DOE Benefits and Scenario (BaSce) Analysis. It is also important to evaluate the progress of these component technical targets compared to existing technologies available in the market.

There is keen interest in understanding the origins of engine-out unburned hydrocarbons emitted during SI engine cold start. This is especially true for the first few firing cycles, which can contribute disproportionately to the total emissions measured over standard drive cycles such as the US Federal Test Procedure (FTP). This study reports on the development of a novel methodology for capturing and quantifying unburned hydrocarbon emissions (HC), CO, and CO2 on a cycle-by-cycle basis during an engine cold start. The method was demonstrated by applying it to a 4 cylinder 2 liter GTDI (Gasoline Turbocharged Direct Injection) engine for cold start conditions at an ambient temperature of 22°C. For this technique, the entirety of the engine exhaust gas was captured for a predetermined number of firing cycles.

Connected automated vehicles (CAVs) are quickly becoming a reality, and their potential ability to communicate with each other and the infrastructure around them has big potential impacts on future mobility systems. Perhaps one of the most important impacts could be on network wide energy consumption. A lot of research has already been performed on the topic of eco-driving and the potential fuel and energy consumption benefits for CAVs. However, most of the efforts to date have been based on simulation studies only, and have only considered conventional vehicle powertrains. In this study, experimental data is presented for the potential eco-driving benefits of two specific intersection approach scenarios, for four different powertrain types.

As emerging automated vehicle technology is making advances in safety and reliability, engineers are also exploring improvements in energy efficiency with this new paradigm. Powertrain efficiency receives due attention, but also impactful is finding ways to reduce driving losses in coordinated-driving scenarios. Efforts focused on simulation to quantify road load improvements require a sufficient amount of background validation work to support them. This study uses a practical approach to directly quantify road load changes by testing the coordinated driving of two vehicles on a test track at various speeds (64, 88, 113 km/h) and vehicle time gaps (0.3 to 1.3 s). Axle torque sensors were used to directly measure the load required to maintain steady-state speeds while following a lead vehicle at various gap distances.

The Toyota Prius Prime is a new generation of Toyota Prius plug-in hybrid electric vehicle, the electric drive range of which is 25 miles. This version is improved from the previous version by the addition of a one-way clutch between the engine and the planetary gear-set, which enables the generator to add electric propulsive force. The vehicle was analyzed, developed and validated based on test data from Argonne National Laboratory’s Advanced Powertrain Research Facility, where chassis dynamometer set temperature can be controlled in a thermal chamber. First, we analyzed and developed components such as engine, battery, motors, wheels and chassis, including thermal aspects based on test data. By developing models considering thermal aspects, it is possible to simulate the vehicle driving not only in normal temperatures but also in hot, cold, or warmed-up conditions.