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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).

In order to determine the factors that affect fuel economy quantitatively, the power flows through the major powertrain components were measured during operation over transient cycles. The fuel consumption rate and torque and speed of the engine output and axle shafts were measured to assess the power flows in a vehicle with a CVT. The measured power flows were converted to energy loss for each component to get the efficiency. Tests were done at Phase 1 and Phase 3 of the FTP and for two different CVT shift modes. The measured energy distributions were compared with those from the ADVISOR simulation and to results from the PNGV study. For both the Hot 505 and the Cold 505, and for both shift modes, the major powertrain loss occurs in the engine, including or excluding standby losses. However, the efficiency of the drivetrain/transmission is important because it influences the efficiency of the engine.

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.

A nephelometer system was developed to characterize engine particulate emissions from DISI engines. Results were correlated with images showing the location and history of particulates in the cylinder of an optical engine. The nephelometer's operation is based upon the dependence of scattered laser light on particulate size from a flow sampled from the exhaust of an engine. The nephelometer simultaneously measured the scattered light from angles of 20° to 160° from the forward scattering direction in 4° increments. The angular scattering measurements were then compared with calculations using a Mie scattering code to infer information regarding particulate size. Measurements of particulate mass were made based upon a correlation developed between the scattered light intensity and particulate mass samples trapped in a 0.2-micron filter. Measurements were made in a direct injection single-cylinder spark ignition research engine having a transparent quartz cylinder.

We have examined the influence of piston wetting on the size distribution and mass of particulate matter (PM) emissions in a SI engine using several different fuels. Piston wetting was isolated as a source of PM emissions by injecting known amounts of liquid fuel onto the piston top using an injector probe. The engine was run predominantly on propane with approximately 10% of the fuel injected as liquid onto the piston. The liquid fuels were chosen to examine the effects of fuel volatility and molecular structure on the PM emissions. A nephelometer was used to characterize the PM emissions. Mass measurements from the nephelometer were compared with gravimetric filter measurements, and particulate size measurements were compared with scanning electron microscope (SEM) photos of particulates captured on filters. The engine was run at 1500 rpm at the Ford world-wide mapping point with an overall equivalence ratio of 0.9.

Hybrid Electric Vehicles (HEVs) can be designed and operated to satisfy many different operational missions. The three most common HEV types differ with respect to component sizing and operational capabilities. However, HEV technology offers design opportunities beyond these three types. This paper presents a detailed HEV categorization process that can be used to describe unique HEV prototype designs entered in college and university-level HEV design competitions. We explored possible energy management strategies associated with designs that control the utilization of the two on-board energy sources and use the competition vehicles to illustrate various configurations and designs that affect the vehicle's capabilities. Experimental data is used to help describe the details of the power control strategies which determine how the engine and electric motor of HEV designs work together to provide motive power to the wheels.

SunDiesel™ is an alternative bio-fuel derived from wood chips that has certain properties that are superior to those of conventional diesel (D2). In this investigation, 100% SunDiesel was tested in a Mercedes A-Class (model year 1999), 1.7L, turbocharged, direct-injection diesel engine (EURO II) equipped with a common-rail injection system. By using an endoscope system, Argonne researchers collected in-cylinder visualization data to compare the engine combustion characteristics of the SunDiesel with those of D2. Measurements were made at one engine speed and load condition (2,500 rpm, 50% load) and four start-of-injection (SOI) points, because of a limited source of SunDiesel fuel. Significant differences in soot concentration, as measured by two-color optical pyrometry, were observed. The optical and cylinder pressure data clearly show significant differences in combustion duration and ignition delay between the two fuels.

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 1998 Toyota Corona passenger car with a direct injection spark ignition (DISI) engine was tested at constant engine speed (2000 rpm) over a range of loads. Engine-out and tailpipe emissions of gas phase species were measured each second. This allowed examination of the engine-out emissions for late and early injection. Seven fuels were used for these tests: five blended fuels and two pure hydrocarbon fuels. These seven fuels can be divided into groups for examination of the effects of volatility, MTBE, and structure (an aromatic versus an i-alkane). Correlations between the fuel properties and their effects on emissions are presented. Use of steady state tests rather than driving cycles to examine fuel effects on emissions eliminates the complications resulting from accelerations, decelerations, and changes of injection timing but care had to be taken to account for the periodic regenerations of the lean NOx trap/catalyst.

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.

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.

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.