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Some CO2-reducing technologies have real-world benefits not captured by regulatory testing methods. This paper documents a two-layer heating, ventilation, and air-conditioning (HVAC) system that facilitates faster engine warmup through strategic increased air recirculation. The performance of this technology was assessed on a 2020 Hyundai Sonata. Empirical performance of the technology was obtained through dynamometer tests at Argonne National Laboratory. Performance of the vehicle across multiple cycles and cell ambient temperatures with the two-layer technology active and inactive indicated fuel consumption reduction in nearly all cases. A thermally sensitive powertrain model, the National Renewable Energy Laboratory’s FASTSim Hot, was calibrated and validated against vehicle testing data. The developed model included the engine, cabin, and HVAC system controls.

This work presents a methodology to determine the off-cycle fuel economy benefit of a 2-Layer HVAC system which reduces ventilation and heat rejection losses of the heater core versus a vehicle using a standard system. Experimental dynamometer tests using EPA drive cycles over a broad range of ambient temperatures were conducted on a highly instrumented 2016 Lexus RX350 (3.5L, 8 speed automatic). These tests were conducted to measure differences in engine efficiency caused by changes in engine warmup due to the 2-Layer HVAC technology in use versus the technology being disabled (disabled equals fresh air-considered as the standard technology baseline). These experimental datasets were used to develop simplified response surface and lumped capacitance vehicle thermal models predictive of vehicle efficiency as a function of thermal state.

A quasi-dimensional model for a direct injection diesel engine was developed based on experiments at Sandia National Laboratory. The Sandia researchers obtained images describing diesel spray evolution, spray mixing, premixed combustion, mixing controlled combustion, soot formation, and NOx formation. Dec [1] combined all of the available images to develop a conceptual diesel combustion model to describe diesel combustion from the start of injection up to the quasi-steady form of the jet. The end of injection behavior was left undescribed in this conceptual model because no clear image was available due to the chaotic behavior of diesel combustion. A conceptual end-of-injection diesel combustion behavior model was developed to capture diesel combustion throughout its life span. The compression, expansion, and gas exchange stages are modeled via zero-dimensional single zone calculations.

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.

It is widely understood that cold ambient temperatures increase vehicle fuel consumption due to heat transfer losses, increased friction (increased viscosity lubricants), and enrichment strategies (accelerated catalyst heating). However, relatively little effort has been dedicated to thoroughly quantifying these impacts across a large set of real world drive cycle data and ambient conditions. This work leverages experimental dynamometer vehicle data collected under various drive cycles and ambient conditions to develop a simplified modeling framework for quantifying thermal effects on vehicle energy consumption. These models are applied over a wide array of real-world usage profiles and typical meteorological data to develop estimates of in-use fuel economy. The paper concludes with a discussion of how this integrated testing/modeling approach may be applied to quantify real-world, off-cycle fuel economy benefits of various technologies.

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).

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).

Response Surface Methodology (RSM) techniques are applied to develop brake specific fuel consumption (BSFC) maps of a test vehicle over standard drive cycles under various ambient conditions. This technique allows for modeling and predicting fuel consumption of an engine as a function of engine operating conditions. Results will be shown from Federal Test Procedure engine starts of 20°C, and colder conditions of -7°C. Fueling rates under a broad range of engine temperatures are presented. Analysis comparing oil and engine coolant as an input factor of the model is conducted. Analysis comparing the model to experimental datasets, as well as some details into the modeling development, will be presented. Although the methodology was applied to data collected from a vehicle, the same technique could be applied to engines run on dynamometers.

For this work, a methodology of modeling and predicting fuel consumption in a hybrid vehicle as a function of the engine operating temperature has been developed for cold ambient operation (-7°C, 266°K). This methodology requires two steps: 1) development of a temperature dependent engine brake specific fuel consumption (BSFC) map, and, 2) a data-fitting technique for predicting engine temperature to be used as an input to the temperature dependent BSFC maps. For the first step, response surface methodology (RSM) techniques were applied to generate brake specific fuel consumption (BSFC) maps as a function of the engine thermal state. For the second step, data fitting techniques were also used to fit a simplified lumped capacitance heat transfer model using several experimental datasets. Utilizing these techniques, an analysis of fuel consumption as a function of thermal state across a broad range of engine operating conditions is presented.

Testing plug-In hybrid vehicles over standardized and real world drive cycles has shown relatively large efficiency differences between ambient cold starts and hot starts(1,2) (CS/HS). This variation is dependent upon the drive cycle and powertrain architecture, and is significant in magnitude. Quantifying this inefficiency is non-trivial as charge-depleting modes, coupled with vehicle calibration sensitivity, consume small portions of fuel resulting in test variations in which thermal effects cannot be decoupled from slight calibration changes that mask thermal influences. In this paper, a methodology for modeling and analyzing the fuel efficiency of a plug-in hybrid vehicle powertrain as a function of the engine operating temperature will be presented. Response surface methodology (RSM) techniques have been applied to generate brake specific fuel consumption (BSFC) maps as a function of the engine thermal state indicated by crankcase oil temperature.

Argonne National Laboratory (Argonne) and Idaho National Laboratory (INL), working with the FreedomCAR and Fuels Partnership, lead activities in vehicle dynamometer and fleet testing as well as in modeling activities. By using Argonne’s Advanced Powertrain Research Facility (APRF), the General Motors (GM) Tahoe 2-mode was instrumented and tested in the 4-wheel-drive test facility. Measurements included both sensors and controller area network (CAN) messages. In this paper, we describe the vehicle instrumentation as well as the test results. On the basis of the analysis performed, we discuss the vehicle model developed in Argonne’s vehicle simulation tool, the Powertrain System Analysis Toolkit (PSAT), and its comparison with test data. Finally, on-road vehicle data, performed by INL, is discussed and compared with the dynamometer results.

This paper presents the latest developments in the design and performance of an electronic particulate matter (PM) sensor developed at The University of Texas at Austin (UT) and suitable, with further development, for applications in active engine control of PM emissions. The sensor detects the carbonaceous mass component of PM in the exhaust and has a time-resolution less than 20 (ms), allowing PM levels to be quantified for engine transients. Sample measurements made with the sensor in the exhaust of a single-cylinder light duty diesel engine are presented for both steady-state and transient operations: a steady-state correlation with gravimetric filter measurements is presented, and the sensor response to rapid increases in PM emission during engine transients is shown for several different tip-in (momentary increases in fuel delivery) conditions.

Combustion chamber pressure measurement in engines via a passage is an old technique that is still widely used in engine research. This paper presents improved passage designs for an off-set electrode spark plug designed to accept a pressure transducer. The spark plug studied was the Champion model 304-063A. Two acoustic models were developed to compute the resonance characteristics. The new designs have a resonance frequency in a range higher than the fundamental frequency expected from knock so that the signal can be lowpass filtered to remove the resonance and not interfere with pressure signal components associated with combustion phenomena. Engine experiments verified the spark plug resonance behavior. For the baseline engine operating condition approximately 50 of 100 cycles had visible passage resonance in the measured pressure traces, at an average frequency of 8.03 kHz.

The Rotating Linear Engine (RLE) derives improved fuel efficiency and decreased maintenance costs via a unique lubrication design, which decreases piston assembly friction and the associated wear for heavy-duty natural gas and diesel engines. The piston ring friction exhibited on current engines accounts for 1% of total US energy consumption. The RLE is expected to reduce this friction by 50-70%, an expectation supported by hot motoring and tear-down tests on the UT single cylinder RLE prototype. Current engines have stationary liners where the oil film thins near the ends of the stroke, resulting in metal-to-metal contact. This metal-to-metal contact is the major source of both engine friction and wear, especially at high load. The RLE maintains an oil film between the piston rings and liner throughout the piston stroke due to liner rotation. This assumption has also been confirmed by recent testing of the single cylinder RLE prototype.

Cylinder liner rotation (Rotating Liner Engine, RLE) is a new concept for reducing piston assembly friction in the internal combustion engine. The purpose of the RLE is to reduce or eliminate the occurrence of boundary and mixed lubrication friction in the piston assembly (specifically, the rings and skirt). This paper reports the results of experiments to quantify the potential of the RLE. A 2.3 L GM Quad 4 SI engine was converted to single cylinder operation and modified for cylinder liner rotation. To allow examination of the effects of liner rotational speed, the rotating liner is driven by an electric motor. A torque cell in the motor output shaft is used to measure the torque required to rotate the liner. The hot motoring method was used to compare the friction loss between the baseline engine and the rotating liner engine. Additionally, hot motoring tear-down tests were used to measure the contribution of each engine component to the total friction torque.

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.

A fiber optic instrumented spark plug was used to make time-resolved measurements of the fuel vapor concentration history near the spark gap in a four-valve DISI engine. Four different bulk flow were investigated. Several early and late injection timings were examined. The fuel concentration at the spark gap was correlated with IMEP. Emissions of CO, HCs, and NOx were related to the type of bulk flow. For both early and late injection the CoVs of fuel concentration were generally lowest for the weakest bulk flow which resulted in a stable stratification. Strong bulk flows convected the inhomogeneities through the measurement area near the spark plug resulting in both large intracycle and cycle-to-cycle variation in equivalence ratio at the time of ignition.

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.

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.