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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.

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).

As new advanced-technology vehicles are becoming more mainstream, analysts are studying their potential impact on petroleum use, carbon emissions, and smog emissions. Determining the potential impacts of widespread adoption requires testing and careful analysis. PHEVs possess unique operational characteristics that require evaluation in terms of actual in-use driving habits. SAE J2841, “Utility Factor Definitions for Plug-In Hybrid Electric Vehicles Using 2001 U.S. DOT National Household Travel Survey Data,” published by SAE in 2009 with a revision in 2010, is a guide to using DOT's National Household Travel Survey (NHTS) data to estimate the relative split between driving in charge-depleting (CD) mode and charge-sustaining (CS) mode for a particular PHEV with a given CD range. Without this method, direct comparisons of the merits of various vehicle designs (e.g., efficiency and battery size) cannot be made among PHEVs, or between PHEVs and other technologies.

A quasidimensional engine simulation which uses the concepts of fractal geometry to model the effects of turbulence on flame propagation in a homogeneous charge SI engine has been developed. Heat transfer and blowby/crevice flow submodels are included in this code and the submodels chosen are found to be reasonable. The model predictions of cylinder pressure histories are then compared with experimental data over a range of loads, equivalence ratios, and engine speeds. The model is not adjusted in any manner to yield better agreement with the data, other than by tuning the simple turbulence model used so as to yield agreement with data for the nonreacting flow. However, current information about the flame wrinkling scales in an engine is inadequate. Therefore, predictions are made for three different assumptions about the flame wrinkling scales which span the range of physically possible scales.

An investigation of cyclic variability in a spark ignition engine is reported. Specifically, the predictions of an engine code have been compared with experimental data obtained using a well-characterized SI engine. The engine used for the experimental work and modeled in the code is the single cylinder research engine developed at Sandia National Laboratories and now operating at Drexel University. The data used for comparison were cylinder pressure histories for 110 engine cycles gathered during operation at a single engine operating condition. The code allows the various factors that could influence cyclic variability to be examined independently. Specifically, a model has been used to independently examine the effects of variations in equivalence ratio and of the turbulence intensity on cycle-to-cycle variations in the peak cylinder pressure, the crankangle of occurrence of peak pressure, the flame development angle, and the rapid burning angle.

Condensation of fuel vapor on the cold surfaces within the combustion chamber is investigated as a possible mechanism for increased HC emissions from SI engines during cold start. A one-dimensional, transient, mass diffusion analysis is used to examine the condensation of single-species fuels on the surfaces of the combustion chamber as the pressure within the cylinder rises during compression and combustion, and re-vaporization during expansion, blowdown, and exhaust. The effects of wall temperature, fuel volatility, and engine load and speed on this mechanism are also discussed. This analysis shows that low-volatility fuel components can condense on the surfaces of the combustion chamber when the surface temperatures are sufficiently low. This condensed fuel may re-vaporize during the power and exhaust strokes, or it may remain in the combustion chamber until surface temperatures rise, perhaps tens of seconds later.

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.

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.

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 railplug is a new type of ignitor for SI engines. A model for optimizing energy deposition in a railplug ignition system is developed. The model is experimentally validated using a low voltage railplug ignition circuit. The effect of various ignition circuit parameters on the energy deposition and its rate are discussed. Durability of railplugs is an important factor in railplug circuit design. As for all spark ignitors, durability of a railplug decreases as energy deposition is increased. Therefore recommendations are made to minimize wear and increase durability, while depositing sufficient energy to attain ignition, using a railplug.

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.

Improved submodels for use in a dynamic engine/vehicle model have been developed and the resulting code has been used to analyze the tip-in, tip-out behavior of a computer-controlled port fuel injected SI engine. This code consists of four submodels. The intake simulation submodel is similar to prior intake models, but some refinements have been made to the fuel flow model to more properly simulate a timed port injection system, and it is believed that these refinements may be of general interest. A general purpose engine simulation code has been used as a subroutine for the cycle simulation submodel. A conventional vehicle simulation submodel is also included in the model formulation. Perhaps most importantly, a submodel has been developed that explicitly simulates the response of the on-board computer (ECM) control system.

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).

Reductions in vehicle drive losses are as important to improving fuel economy as increases in powertrain efficiencies. In order to measure vehicle fuel economy, chassis dynamometer testing relies on accurate road load determinations. Road load is currently determined (with some exceptions) using established test track coastdown testing procedures. Because new vehicle technologies and usage cases challenge the accuracy and applicability of these procedures, on-road experiments were conducted using axle torque sensors to address the suitability of the test procedures in determining vehicle road loads in specific cases. Whereas coastdown testing can use vehicle deceleration to determine load, steady-state testing can offer advantages in validating road load coefficients for vehicles with no mechanical neutral gear (such as plug-in hybrid and electric vehicles).

This paper determines the impact of ambient temperature on energy consumption of a variety of vehicles in the laboratory. Several conventional vehicles, several hybrid electric vehicles, a plug-in hybrid electric vehicle and a battery electric vehicle were tested for fuel and energy consumption under test cell conditions of 20°F, 72°F and 95°F with 850 W/m₂ of emulated radiant solar energy on the UDDS, HWFET and US06 drive cycles. At 20°F, the energy consumption increase compared to 72°F ranges from 2% to 100%. The largest increases in energy consumption occur during a cold start, when the powertrain losses are highest, but once the powertrains reach their operating temperatures, the energy consumption increases are decreased. At 95°F, the energy consumption increase ranges from 2% to 70%, and these increases are due to the extra energy required to run the air-conditioning system to maintain 72°F cabin temperatures.

The mixture preparation process was investigated in a direct-injected, 4-valve, SI engine under motored conditions. The interaction between the high-pressure fuel jet and the intake air-flow was observed. Laser-sheet droplet imaging was used to visualize the in-cylinder droplet distributions, and a single-component LDV system was used to measure in-cylinder velocities. The fuel spray was visualized with the engine motored at 1500 and 750 rpm, and with the engine stopped. It was observed that the shape of the fuel spray was distorted by the in-cylinder air motion generated by the intake air flow, and that this effect became more pronounced with increasing engine speed. Velocity measurements were made at five locations on the symmetry plane of the cylinder, with the engine motored at 750 rpm. Comparison of these measurements with, and without, injection revealed that the in-cylinder charge motion was significantly altered by the injection event.

Predictions of the Fractal Engine Simulation code were compared with SI engine data in a previous paper. These comparisons were extremely good except for the single data set available at a low engine speed. Because of uncertainty regarding whether the lack of agreement for this case resulted from some difficulty with the experimental data or was due to lack of proper speed dependence in the model, additional comparisons are made for a range of speeds from 300-1500 rpm. The fractal burning model is a turbulence driven model (i.e., driven primarily by the turbulence intensity) that divides the combustion process into four sequential phases: 1) kernel formation, 2) early flame growth, 3) fully developed turbulent flame propagation, and 4) end of combustion. The kernel formation process was not included in the previous version of this model, but was found to be required to predict engine speed effects.

Multi-dimensional numerical simulation of the combustion process in spark ignition engines were performed using the Coherent Flame Model (CFM) which is based on the flamelet assumption. The CFM uses a balance equation for the flame surface area to simulate flame surface advection, diffusion, production and destruction in a turbulent reacting flow. There are two model constants in CFM, one associated with the modeling of flame surface production and the other with the modeling of flame surface destruction. Previous experimental results on two test engines charged with propane-air mixtures were used to compare with the computations for different engine speeds, loads, equivalence ratios and spark plug locations. Predicted engine cylinder pressure histories agree well with the experimental results for various operating conditions after the model constants were calibrated against a reference operating condition.

Researchers in the field of turbulent combustion have found fractal geometry to be a useful tool for describing and quantifying the nature of turbulent flames. This paper describes and compares several techniques for the fractal analysis of two dimensional (2-D) turbulent flame images. Four methods of fractal analysis were evaluated: the Area Method, the Box Method, the Caliper Method, and the Area-Caliper Method. These techniques were first applied to a computer-generated fractal image having a known fractal dimension and known cut-offs. It was found that a “window” effect can cause the outer cut-off to be underestimated. The Caliper Method was found to suffer from noise arising from the statistical nature of the analysis. The Area-Caliper Method was found to be superior to the other methods. The techniques were applied to two types of flame images obtained in a spark ignition engine: Mie scattering from particles seeded in the flow and laser induced fluorescence of OH.

A new type of ignitor, the railplug, shows promise of extending the dilution limits for spark ignition engines. While much of the effort expended in our study of railplugs has focused upon demonstrating their effectiveness, it is recognized that railplug durability is presently not acceptable for production engine applications. The goal of the present study was to examine the factors that affect durability. The results of two types of investigations are reported. The effects of rail materials, pressure, delivered energy, and voltage at constant delivered energy on electrode erosion rates were studied for repeated firings in air at constant pressure. Railplug durability in a four-stroke SI engine was also evaluated, including examination of the effects of delivered energy, current pulse characteristics, and materials.