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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.

Two modern light-duty passenger vehicles were selected for chassis dynamometer testing to evaluate differences in performance end efficiency resulting from CNG and gasoline combustion in a vehicle-based context. The vehicles were chosen to be as similar as possible apart from fuel type, sharing similar test weights and identical driveline configurations. Both vehicles were tested over several chassis dynamometer driving cycles, where it was found that the CNG vehicle exhibited 3-9% lower fuel economy than the gasoline-fueled subject. Performance tests were also conducted, where the CNG vehicle's lower tractive effort capability and longer acceleration times were consistent with the lower rated torque and power of its engine as compared to the gasoline model. The vehicles were also tested using quasi-steady-state chassis dynamometer techniques, wherein a series of engine operating points were studied.

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 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).

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.

Previous studies and on-road driving by consumers have shown that Hybrid Electric Vehicle fuel economy is very dependent on driver demand in both vehicle speed and vehicle acceleration [1]. The emerging technology of Plug-In Hybrid Vehicles (PHEV) may prove to also be more sensitivity to aggressive driver demand as compared to conventional internal combustion engine vehicles. This is due to the exceptional ability of the PHEV to minimize fuel consumption at mid to low power levels by the significant use of electric propulsion which enables engine downsizing. As vehicle speed and acceleration increase so does the power demand on the powertrain. The fuel consumption is directly affected by this increase in power demand level. To examine the fuel consumption impact of changing driver characteristics on PHEV’s, testing is conducted on two vehicles (parallel PHEV and power-split PHEV) on a four wheel chassis dynamometer at Argonne’s Advanced Powertrain Research Facility.

A study is presented in which light-weight composite materials are used for an engine intake valve. This paper is an interim progress report and documents the successful demonstration of a net-shape, resin transfer molded intake valve in a running engine. A short review of a previous dynamic model is presented showing the advantages in engine performance by using the composite valves. It is shown that the use of reduced mass composite valves allows for increased engine speed and/or more aggressive cam profiles without sacrificing valve strength or stiffness while at the same time maintaining reliable operation. The use of composite materials allows for a significant weight reduction compared to more conventional materials such as steel and titanium. A brief review of the use of composite materials is presented. The development and design process for carbon fiber reinforced valves is discussed.

High performance engine tuners have traditionally relied primarily on empirical techniques for intake flow optimization. This paper describes the use of a commercial Computational Fluid Dynamics (CFD) package to complement the traditional optimization strategies. This paper describes why some experimental methods are difficult to apply, including an example of Particle Image Velocimetry (PIV), and demonstrates the benefits of using computational analysis to investigate geometry changes to the intake or exhaust systems. This paper also illustrates the use of a Coordinate Measurement Machine (CMM) to digitize an existing cylinder head to develop a solid model suitable for CFD analysis. A comparison of results from a CFD prediction from a digitized solid model to a flow bench measurement demonstrates the validity and usefulness of this approach.

Fiber Reinforced Composites (FRCs) offer the possibility for reduced mass and increased performance in internal combustion engines, yet the automotive and aerospace industries have been slow to adopt these materials. Extensive research has been done over the past 25 years, producing nearly every components of an internal combustion engine out of some form of FRC. This Previous work is summarized herein. A prediction of engine weight reduction is made for direct substitution of FRCs. An additional prediction is made to quantify the additive effects of mass reduction on component mass, and power. It is estimated that engine mass might be reduced by as much as 70% using FRCs and reciprocating mass might be reduced by as much as 90%. In addition, increased mechanical efficiency on the order of 2% may be possible from reduced inertial and frictional loads.

A low pressure fuel distillation system is proposed for extracting a high-volatility fraction of gasoline, and to improve start-up and warm-up behavior of SI engines. More complicated methods for generating high-volatility start-up fuels have demonstrated improved cold start driveability and reduced HC emissions, but so far they have not been put into mass production. In this project, a ‘bench-top’ apparatus was used to investigate the feasibility of using sub-atmospheric pressures to extract a lighter and more volatile fraction from the parent gasoline. A series of experiments was conducted to evaluate the characteristics of the extracted fuel vapor as a function of temperature and pressure. The sensitivity to different brands and grades of gasoline was also explored. The results show that the extracted fuel consists mostly of C5 and C6 compounds, and that its Molecular Weight and Stoichiometric A/F ratio show little sensitivity to the pressure level used for the extraction.

An innovative pedal-assist system for bicycles has been designed and demonstrated by RevoPower Inc. This system incorporates a single-cylinder piston-ported two stroke engine, mounted radially within the front wheel hub of a bicycle. This design is light, compact, and easily adaptable to any common bicycle. However, this application presents some unique challenges for the engine and drivetrain. This paper describes a project undertaken to further develop this self-contained engine-driven bicycle wheel to improve its performance and reduce its noise emission. As described, a variety of computational end experimental techniques were used to analyze and improve the initial engine and wheel design. The work presented here resulted in a tripling of engine power over the baseline configuration, and a simultaneous overall sound reduction of nearly 20 dB(A).

Specification (spec) race engines are intended to reduce costs and increase the competitiveness in many racing classes. However, engines prepared by the best race engine builders routinely outperform truly ‘standard’ engines or engines prepared by less experienced tuners. This paper describes how engines can be modified to increase their power output and discusses various spec engine preparation techniques. Experimental and computational evidence is used to quantify the potential benefits that can be expected from each of the modifications discussed. By combining several relatively small improvements, a well prepared engine may be expected to enjoy a 5-8 % power benefit over an ‘average’ race engine, and perhaps as much as a 14-17 % benefit in power versus a truly standard production engine off the assembly line. This analysis also reveals the claims of much larger power improvements by some high-performance engine tuners can not be substantiated unless further modifications are made.

A technology path has been identified for development of a high efficiency, durable, gasoline engine, targeted at achieving performance and emissions levels necessary to meet heavy-duty, on-road standards of the foreseeable future. Initial experimental and numerical results for the proposed technology concept are presented. This work summarizes internal research efforts conducted at Southwest Research Institute. An alternative combustion system has been numerically and experimentally examined. The engine utilizes gasoline as the fuel, with a combination of enabling technologies to provide high efficiency operation at ultra-low emissions levels. The concept is based upon very highly-dilute combustion of gasoline at high compression ratio and boost levels. Results from the experimental program have demonstrated engine-out NOx emissions of 0.06 g/hp/hr, at single-cylinder brake thermal efficiencies (BTE) above thirty-four percent.

A technique was developed for measuring the Laminar Burning Velocity (LBV) of multi-component fuel blends for use in high-performance spark-ignition engines. This technique involves the use of a centrally-ignited spherical combustion chamber, and a complementary analysis code. The technique was validated by examining several single-component fuels, and the computational procedure was extended to handle multi-component fuels without requiring detailed knowledge of their chemical composition. Experiments performed on an instrumented high-speed engine showed good agreement between the observed heat-release rates of the fuels and their predicted ranking based on the measured LBV parameters.

The impingement of liquid fuel onto the surfaces of the combustion chamber (wall-wetting) has been shown to be an important source of HC emissions from direct-injected SI engines, and can even result in pool fires and diffusion flames. Some degree of wall wetting, particularly on the piston top, is believed to occur in every current DIG engine design, but the behavior of the wall-bound fuel throughout the engine cycle is poorly understood. The goal of this study was to gain a better understanding of the fundamental interaction between liquid fuel droplets and the piston under engine-like conditions, by observing the vaporization of individual fuel drops as the surface temperature and ambient pressures were varied in a controlled environment. The vaporization of several single-component fuels, binary mixtures, and multi-component fuels was examined in the range of surface temperatures between 50 and 300 °C and ambient pressures between 50 and 1270 kPa (abs).

A new combustion concept has been developed and tested for improving the low to moderate load efficiency and NOx emissions of natural gas engines. This concept involves operation of a dual-fuel natural gas engine on Homogeneous Charge Compression Ignition (HCCI) in the load regime of idle up to 35 % of the peak torque. A dual-fuel approach is used to control the combustion phasing of the engine during HCCI operation, and conventional spark-ignited natural gas combustion is used for the high-load regime. This concept has resulted in an engine with power output and high-load fuel efficiency that are unchanged from the base engine, but with a 10 - 15 % improvement to the low to moderate load fuel efficiency. In addition, the engine-out NOx emissions during HCCI operation are over 90% lower than on spark-ignited natural gas operation over the equivalent load range.

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 Prius is a major achievement by Toyota: it is the first mass-produced HEV with the first available HEV-optimized engine. Argonne National Laboratory's Advanced Powertrain Test Facility has been testing the Prius for model validation and technology performance and assessment. A significant part of the Prius test program is focused on testing and mapping the engine. A short-length torque sensor was installed in the powertrain in-situ. The torque sensor data allow insight into vehicle operational strategy, engine utilization, engine efficiency, and specific emissions. This paper describes the design and process necessary to install a torque sensor in a vehicle and shows the high-fidelity data measured during chassis dynamometer testing. The engine was found to have a maximum thermodynamic efficiency of 36.4%. Emissions and catalyst efficiency maps were also produced.