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In response to the stipulations of the Energy Policy and Conservation Act and the global momentum toward carbon mitigation, there has been a pronounced tightening of fuel economy standards for manufacturers. This stricter regulation is coupled with an accelerated transition to electric vehicles, catalyzed by advances in electrification technology and a decline in battery cost. Improvements in the fuel economy of medium- and heavy-duty vehicles through electrification are particularly noteworthy. Estimating the magnitude of fuel economy improvements that result from technological advances in these vehicles is key to effective policymaking. In this research, we generated vehicle models based on assumptions regarding advanced transportation component technologies and powertrains to estimate potential vehicle-level fuel savings. We also developed a systematic approach to evaluating a vehicle’s fuel economy by calibrating the size of the components to satisfy performance requirements.

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.

It is widely understood that cold ambient temperatures negatively impact vehicle system efficiency. This is due to a combination of factors: increased friction (engine oil, transmission, and driveline viscous effects), cold start enrichment, heat transfer, and air density variations. Although the science of quantifying steady-state vehicle component efficiency is mature, transient component efficiencies over dynamic ambient real-world conditions is less understood and quantified. This work characterizes wheel assembly efficiencies of a conventional and electric vehicle over a wide range of ambient conditions. For this work, the wheel assembly is defined as the tire side axle spline, spline housing, bearings, brakes, and tires. Dynamometer testing over hot and cold ambient temperatures was conducted with a conventional and electric vehicle instrumented to determine the output energy losses of the wheel assembly in proportion to the input energy of the half-shafts.

This paper introduces control strategy analysis and performance degradation for the 2010 Toyota Prius under different thermal conditions. The goal was to understand, in as much detail as possible, the impact of thermal conditions on component and vehicle performances by analyzing a number of test data obtained under different thermal conditions in the Advanced Powertrain Research Facility (APRF) at Argonne National Laboratory. A previous study analyzed the control behavior and performance under a normal ambient temperature; thus the first step in this study was to focus on the impact when the ambient temperature is cold or hot. Based on the analyzed results, thermal component models were developed in which the vehicle controller in the simulation was designed to mimic the control behavior when temperatures of the components are cold or hot. Further, the performance degradation of the components was applied to the mathematical models based on analysis of the test data.

The first commercially available Plug-In Hybrid Electric Vehicle (PHEV), the General Motors (GM) Volt, was introduced into the market in December 2010. The Volt's powertrain architecture provides four modes of operation, including two that are unique and maximize the Volt's efficiency and performance. The electric transaxle has been specially designed to enable patented operating modes both to improve the electric driving range when operating as a battery electric vehicle and to reduce fuel consumption when extending the range by operating with an internal combustion engine (ICE). However, details on the vehicle control strategy are not widely available because the supervisory control algorithm is proprietary. Since it is not possible to analyze the control without vehicle test data obtained from a well-designed Design-of-Experiment (DoE), a highly instrumented GM Volt, including thermal sensors, was tested at Argonne National Laboratory's Advanced Powertrain Research Facility (APRF).

The Rotating Liner Engine (RLE) is an engine design concept where the cylinder liner rotates in order to reduce piston assembly friction and liner/ring wear. The reduction is achieved by the elimination of the mixed and boundary lubrication regimes that occur near TDC. Prior engines for aircraft developed during WW2 with partly rotating liners (Sleeve Valve Engines or SVE) have exhibited reduction of bore wear by factor of 10 for high BMEP operation, which supports the elimination of mixed lubrication near the TDC area via liner rotation. Our prior research on rotating liner engines experimentally proved that the boundary/mixed components near TDC are indeed eliminated, and a high friction reduction was quantified compared to a baseline engine. The added friction required to rotate the liner is hydrodynamic via a modest sliding speed, and is thus much smaller than the mixed and boundary friction that is eliminated.

The Prius - a power-split hybrid electric vehicle from Toyota - has become synonymous with the word “Hybrid.” As of October 2010, two million of these vehicles had been sold worldwide, including one million vehicles purchased in the United States. In 2004, the second generation of the vehicle, the Prius MY04, enhanced the performance of the components with advanced technologies, such as a new magnetic array in the rotors. However, the third generation of the vehicle, the Prius MY10, features a remarkable change of the configuration - an additional reduction gear has been added between the motor and the output of the transmission [1]. In addition, a change in the energy management strategy has been found by analyzing the results of a number of tests performed at Argonne National Laboratory's Advanced Powertrain Research Facility (ARRF).

EmiSense Technologies, LLC (www.emisense.com) is commercializing its electronic particulate matter (PM) sensor that is based on technology developed at the University of Texas at Austin (UT). To demonstrate the capability of this sensor for real-time PM measurements and on board diagnostics (OBD) for failure detection of diesel particle filters (DPF), independent measurements were performed to characterize the engine PM emissions and to compare with the PM sensor response. Computational fluid dynamics (CFD) modeling was performed to characterize the hydrodynamics of the sensor's housing and to develop an improved PM sensor housing with reproducible hydrodynamics and an internal baffle to minimize orientation effects. PM sensors with the improved housing were evaluated in the truck exhaust of a heavy duty (HD) diesel engine tested on-road and on a chassis dynamometer at the University of California, Riverside (UCR) using their Mobile Emissions Laboratory (MEL).

Over the past couple of years, numerous Hybrid Electric Vehicle (HEV) powertrain configurations have been introduced into the marketplace. Currently, the dominant architecture is the power-split configuration, notably the input splits from Toyota Motor Sales and Ford Motor Company. This paper compares two vehicle-level control strategies that have been developed to minimize fuel consumption while maintaining acceptable performance and drive quality. The first control is rules based and was developed on the basis of test data from the Toyota Prius as provided by Argonne National Laboratory's (Argonne's) Advanced Powertrain Research Facility. The second control is based on an instantaneous optimization developed to minimize the system losses at every sample time. This paper describes the algorithms of each control and compares vehicle fuel economy (FE) on several drive cycles.

As natural gas engines are designed to operate leaner and with increased boost pressure, durability of the spark plugs becomes problematic. Among the various new ignition devices that have been considered to solve some of the problems facing spark plugs, railplugs appear to hold clear advantages in some areas. There are two types of railplugs: coaxial rail and parallel rail. This paper reports the results of an experimental study of various parameters that affect the performance of parallel railplugs. Their performance was quantified by the distance that the arc traveled along the rails from the initiation point. Travel along the rails is thought to be an important performance metric because rail-travel limits excessive local wear and produces a distributed ignition source which can potentially reduce mixture inhomogeneity induced ignition problems.

It is a very challenging problem to reliably ignite extremely lean mixtures, especially for the low speed, high load conditions of large-bore natural gas engines. If these engines are to be use for the distributed power generation market, it will require operation with higher boost pressures and even leaner mixtures. Both place greater demands on the ignition system. The railplug is a very promising ignition system for lean burn natural gas engines with its high-energy deposition and high velocity plasma arc. It requires care to properly design railplugs for this new application, however. For these engines, in-cylinder pressure and mixture temperature are very high at the time of ignition due to the high boost pressure. Hot spots may exist on the electrodes of the ignitor, causing pre-ignition problems. A heat transfer model is proposed in this paper to aid the railplug design. The electrode temperature was measured in an operating natural gas engine.

The On-Board Distillation System (OBDS) extracts, from gasoline, a highly volatile crank fuel that enables simultaneous reduction of start-up fuel enrichment and significant ignition timing retard during cold-starting. In a previous paper we reported reductions in catalyst light-off time of >50% and THC emissions reductions >50% over Phase I of the FTP drive cycle. The research presented herein is a further development of the OBDS concept. For this work, OBDS was improved to yield higher-quality start-up fuel. The PCM calibration was changed as well, in order to improve the response to intake manifold pressure transients. The test vehicle was tested over the 3-phase FTP, with exhaust gases speciated to determine NMOG and exhaust toxics emissions. Also, the effectiveness of OBDS at generating a suitable starting fuel from a high driveability index test gasoline was evaluated.

Time-resolved current and voltage measurements for an inductive automotive spark system were made. Also presented are measurements of the total energy delivered to the spark gap. The measurements were made in air for a range of pressures from 1-18 atm, at ambient temperatures. The measured voltage and current characteristics were found to be a function of many ignition parameters; some of these include: spark gap distance, internal resistance of the spark plug and high tension wire, and pressure. The voltages presented were measured either at the top of the spark plug or at the spark gap. The measurements were made at different time resolutions to more accurately resolve the voltage and current behavior throughout the discharge process. This was necessary because the breakdown event occurs on a time scale much shorter than the arc and glow phases.

Piston wetting can be isolated from the other sources of HC emissions from DISI engines by operating the engine predominantly on a gaseous fuel and using an injector probe to impact a small amount of liquid fuel on the piston top. This results in a marked increase in HC emissions. In a previous study, we used a variety of pure liquid hydrocarbon fuels to examine the influence of fuel volatility and structure on the HC emissions due to piston wetting. It was shown that the HC emissions correspond to the Leidenfrost effect: fuels with very low boiling points yield high HCs and those with a boiling point near or above the piston temperature produce much lower HCs. All of these prior tests of fuel effects were performed at a single operating condition: the Ford World Wide Mapping Point (WWMP). In the present study, the effects of load and engine speed are examined.

Two limited-production hybrid electric vehicles (HEVs) - a 1988 Japanese model Toyota Prius and a 2000 Honda Insight - were tested at Argonne National Laboratory to collect data from vehicle component and systems operation. The test data are used to analyze operation and efficiency and to help validate computer simulation models. Both HEVs have FTP fuel economy greater than 45 miles per gallon and also have attributes very similar to those of conventional gasoline vehicles, even though each HEV has a unique powertrain configuration and operation control strategy. The designs and characteristics of these vehicles are of interest because they represent production technology with all the compromises for production included. This paper will explore both designs, their control strategies, and under what conditions high fuel economy was achieved.

The effects of fuel properties on the emissions of a production vehicle with a gasoline direct injection engine operating over the Federal Test Procedure (FTP) cycle were investigated. The vehicle used was a 1998 Toyota Corona passenger car with a direct injection spark ignition (DISI) engine. Engine-out and tailpipe FTP emissions for six fuels and a California Phase 2 RFG reference fuel are presented. Four of the test fuels were blended from refinery components to meet specified distillation profiles. The remaining test fuels were iso-octane and toluene, an iso-alkane and an aromatic with essentially the same boiling point (at atmospheric pressure) that is near the T50 point for the blended fuels. Statistically significant effects, at the 95% confidence level, of the fuels on tailpipe emissions were found. Correlations were sought between the properties of the five blends and the Emissions Indices for engine-out hydrocarbons and NOx and for tailpipe particulates.

A liquid-phase port injection system for liquefied petroleum gas (LPG) generally consists of a fuel storage tank with extended capability of operating up to 600 psi, a fuel pump, and suitable fuel lines to and from the LPG fuel injectors mounted in the fuel rail manifold. Port injection of LPG in the liquid phase is attractive due to engine emissions and performance benefits. However, maintaining the LPG in the liquid phase at under-hood conditions and re-starting after hot soak can be difficult. Multiphase behavior within a liquid-phase LPG injection system was investigated computationally and experimentally. A commercial chemical equilibrium code (ASPEN PLUS™) was used to model various LPG compositions under operating conditions.

This paper presents the results of an experimental investigation of the fuel-air mixing process in a port-fuel-injected, 4-valve, spark-ignited engine that was motored to simulate cold cranking and start-up conditions. An infrared fiber-optic instrumented spark plug probe was used to measure the local, crank angle resolved, fuel concentration in the vicinity of the spark gap of a single-cylinder research engine with a production head and fuel injector. The crank-angle resolved fuel concentrations were compared for various injection timings including open-intake-valve (OIV) and closed-intake-valve (CIV) injection, using federal certification gasoline. In addition, the effects of speed, intake manifold pressure, and injected fuel mass were examined.

In premixed turbulent combustion models, two mechanisms have been used to explain the increase in the flame speed due to the turbulence. The newer explanation considers the full range of turbulence scales which wrinkle the flame front so as to increase the flame front area and, thus, the flame propagation speed. The fractal combustion model is an example of this concept. The older mechanism assumes that turbulence enables the penetration of unburned mixtures across the flame front via entrainment into the burned mixture zone. The entrainment combustion or eddy burning model is an example of this mechanism. The results of experimental studies of combustion regimes and the flame structures in SI engines has confirmed that most combustion takes place at the wrinkled flame front with additional combustion taking place in the form of flame fingers or peninsulas.

Lean mixture combustion might be an important feature in the next generation of SI engines, while diluents (internal and external EGR) have already played a key role in the reductions of emissions and fuel consumption. Lean burn modeling is even more important for engine modeling tools which are sometimes used for new engine development. The effect of flame strain on flame speed is believed to be significant, especially under lean mixture conditions. Current quasi-dimensional engine models usually do not include flame strain effects and tend to predict burn rate which is too high under lean burn conditions. An attempt was made to model flame strain effects in quasi-dimensional SI engine models. The Ford model GESIM (stands for General Engine SIMulation) was used as the platform. A new strain rate model was developed with the Lewis number effect included.