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This paper presents the fuel consumption results of engine and vehicle simulation modeling for a wide variety of individual technologies and technology packages applied to a long haul heavy duty vehicle. Based on the simulation modeling, up to 11% in fuel savings is possible using commercially available and emerging technologies applied to a 15L DD15 engine alone. The predicted fuel savings are up to 17% in a Kenworth T700 tractor-trailer unit equipped with a range of vehicle technologies, but using the baseline DD15 diesel engine. A combination of the most aggressive engine and vehicle technologies can provide savings of up to 29%, averaged over a range of drive cycles. Over 30% fuel savings were found with the most aggressive combination on a simulated long haul duty cycle. Note that not all of these technologies may prove to be cost-effective. The fuel savings benefits for individual technologies vary widely depending on the drive cycles and payload.

Medium- and Heavy Duty Truck fuel consumption and the resulting greenhouse gas (GHG) emissions are significant contributors to overall U.S. GHG emissions. Forecasts of medium- and heavy-duty vehicle activity and fuel use predict increased use of freight transport will result in greatly increased GHG emissions in the coming decades. As a result, the National Highway Traffic Administration (NHTSA) and the United States Environmental Protection Agency (EPA) finalized a regulation requiring reductions in medium and heavy truck fuel consumption and GHGs beginning in 2014. The agencies are now proposing new regulations that will extend into the next decade, requiring additional fuel consumption and GHG emissions reductions. To support the development of future regulations, a research project was sponsored by NHTSA to look at technologies that could be used for compliance with future regulations.

This paper presents the results of engine and vehicle simulation modeling for a wide variety of individual technologies and technology packages applied to two medium-duty vocational vehicles. Simulation modeling was first conducted on one diesel and two gasoline medium-duty engines. Engine technologies were then applied to the baseline engines. The resulting fuel consumption maps were run over a range of vehicle duty cycles and payloads in the vehicle simulation model. Results were reported for both individual engine technologies and combinations or packages of technologies. Two vehicles, a Kenworth T270 box delivery truck and a Ford F-650 tow truck were evaluated. Once the baseline vehicle models were developed, vehicle technologies were added. As with the medium-duty engines, vehicle simulation results were reported for both individual technologies and for combinations. Vehicle technologies were evaluated only with the baseline 2019 diesel medium-duty engine.

Advanced combustion strategies used to improve efficiency, emissions, and performance in internal combustion engines (IC) alter the chemical composition of engine-out emissions. The characterization of exhaust chemistry from advanced IC engines requires an analytical system capable of measuring a wide range of compounds. For many years, the widely accepted Coordinating Research Council (CRC) Auto/Oil procedure[1,2] has been used to quantify hydrocarbon compounds between C1 and C12 from dilute engine exhaust in Tedlar polyvinyl fluoride (PVF) bags. Hydrocarbons greater than C12+ present the greatest challenge for identification in diesel exhaust. Above C12, PVF bags risk losing the higher molecular weight compounds due to adsorption to the walls of the bag or by condensation of the heavier compounds. This paper describes two specialized exhaust gas sampling and analytical systems capable of analyzing the mid-range (C10 - C24) and the high range (C24+) hydrocarbon in exhaust.

This paper describes advances in variable speed supercharging, including benefits for both fuel economy and low speed torque improvement. This work is an extension of the work described in SAE Paper 2012-01-0704 [8]. Using test stand data and state-of-the-art vehicle simulation software, a NuVinci continuously variable planetary (CVP) transmission driving an Eaton R410 supercharger on a 2.2 liter diesel was compared to the same base engine/vehicle with a turbocharger to calculate vehicle fuel economy. The diesel engine was tuned for Tier 2 Bin 5 emissions. Results are presented using several standard drive cycles. A Ford Mustang equipped with a 4.6 liter SI engine and prototype variable speed supercharger has also been constructed and tested, showing low speed torque increases of up to 30%. Dynamometer test results from this effort are presented. The combined results illustrate the promise of variable speed supercharging as a viable option for the next generation of engines.

A zero-dimensional cycle simulation model coupled with a chemical equilibrium model and a two-zone combustion model has been extended to predict nitric oxide formation and emissions from spark-ignited, lean-burn natural gas engines. It is demonstrated that using the extended Zeldovich mechanism alone, the NOx emissions from an 8.1-liter, 6-cylinder, natural gas engine were significantly under predicted. However, by combining the predicted NOx formation from both the extended Zeldovich thermal NO and the Fenimore prompt NO mechanisms, the NOx emissions were predicted with fair accuracy over a range of engine powers and lean-burn equivalence ratios. The effect of injection timing on NOx emissions was under predicted. Humidity effects on NOx formation were slightly under predicted in another engine, a 6.8-liter, 6-cylinder, natural gas engine. Engine power was well predicted in both engines, which is a prerequisite to accurate NOx predictions.

Brake energy recovery is one of the key components in today's hybrid vehicles that allows for increased fuel economy. Typically, major engineering changes are required in the drivetrain to achieve these gains. The objective of this paper is to present a concept of capturing brake energy in a mild hybrid approach without any major modifications to the drivetrain or other vehicular systems. With fuel costs rising, the additional component cost incurred in the presented concept may be recovered quickly. In today's vehicles, alternators supply the electrical power for the engine and vehicle accessories whenever the engine is running. As vehicle electrical demands increase, this load is an ever-increasing part of the engine's output, negatively impacting fuel economy. By using a regenerative device (alternator) on the drive shaft (or any other part of the power train), electrical energy can be captured during braking.

Hybrid hydraulic power trains are a natural fit for heavy duty vehicle applications due to their high power density. This paper describes the analytical formulae available for sizing a series hybrid hydraulic vehicle without changing the engine size. Sizing of pump, accumulator and motor are addressed specifically. A control strategy is also suggested for operating the engine and powertrain pressure close to the best efficiency zones. An example is then given using an FMTV (Family of Medium Tactical Vehicles) platform with a CAT C7 engine. Simulation results are generated using VPSET (Vehicle Propulsion Systems Evaluation Tool), an SwRI-developed vehicle modeling and simulation tool. The hydraulic components are sized according to the recommendations in this paper. The suggested control strategy is implemented in VPSET and performance of the series hydraulic hybrid configuration is compared with that of a conventional powertrain.

The Texas Department of Transportation (TxDOT) began using an emulsified diesel fuel in July 2002. They initiated a simultaneous study of the effectiveness of this fuel in comparison to 2D on-road diesel fuel, which they use in both their on-road and off-road equipment. The study also incorporated analyses for the fleet operated by the Associated General Contractors (AGC) in the Houston area. Some members of AGC use 2D off-road diesel fuel in their equipment. The study included comparisons of fuel economy and emissions for the emulsified fuel relative to the conventional diesel fuels. Cycles that are known to be representative of the typical operations for TxDOT and AGC equipment were required for use in this study. Four test cycles were developed from data logged on equipment during normal service: 1) the TxDOT Telescoping Boom Excavator Cycle, 2) the AGC Wheeled Loader Cycle, 3) the TxDOT Single-Axle Dump Truck Cycle, and 4) the TxDOT Tandem-Axle Dump Truck Cycle.

Southwest Research Institute developed an Autonomous Ground Vehicle (AGV) capable of navigating in urban environments. The paper first gives an overview of hardware and software onboard the vehicle. The systems onboard are classified into perception, intelligence, and command and control modules to mimic a human driver. Perception deals with sensing from the world and translating it into situation awareness. This awareness is then fed into intelligence modules. Intelligence modules take inputs from the user to understand the need to navigate from its current location to another destination and, then, generate a path between them on urban, drivable surfaces using its internal urban database. Situational awareness helps intelligence to update the path in real time by avoiding any static/moving obstacles while following traffic rules.

A simulation framework with a validated system model capable of estimating fuel consumption is a valuable tool in analysis and design of the hybrid vehicles. In particular, the framework can be used for (1) benchmarking the fuel economy achievable from alternate hybrid powertrain technologies, (2) investigating sensitivity of fuel savings with respect to design parameters (for example, component sizing), and (3) evaluating the performance of various supervisory control algorithms for energy management. This paper describes such a simulation framework that can be used to predict fuel economy of series hydraulic hybrid vehicle for any specified driver demand schedule (drive cycle), developed in MATLAB/Simulink. The key components of the series hydraulic hybrid vehicle are modeled using a combination of first principles and empirical data. A simplified driver model is included to follow the specified drive cycle.

The effects of downspeeding and supercharging a passenger car diesel engine were studied through laboratory investigation and vehicle simulation. Changes in the engine operating range, transmission gearing, and shift schedule resulted in improved fuel consumption relative to the baseline turbocharged vehicle while maintaining performance and drivability metrics. A shift schedule optimization technique resulted in fuel economy gains of up to 12% along with a corresponding reduction in transmission shift frequency of up to 55% relative to the baseline turbocharged configuration. First gear acceleration, top gear passing, and 0-60 mph acceleration of the baseline turbocharged vehicle were retained for the downsped supercharged configuration.

The Scuderi engine is a split cycle design that divides the four strokes of a conventional combustion cycle over two paired cylinders, one intake/compression cylinder and one power/exhaust cylinder, connected by a crossover port. This configuration provides potential benefits to the combustion process, as well as presenting some challenges; it also creates the possibility for pneumatic hybridization of the engine. This paper presents the methodology and results of a comprehensive study to investigate the benefits of air hybrid operation with the Scuderi Split Cycle (SSC) engine. Four air hybrid operating modes are made possible by the Split Cycle configuration, namely air compressor, air expander, air expander & firing and firing & charging. The predicted operating requirements for each individual operating mode are established. The air and fuel flow of the individual modes are fully mapped throughout the engine operating speed and load range and air tank pressure operating range.

Biodiesel produced from soybean oil, canola oil, yellow grease, and beef tallow was tested in two heavy-duty engines. The biodiesels were tested neat and as 20% by volume blends with a 15 ppm sulfur petroleum-derived diesel fuel. The test engines were a 2002 Cummins ISB and 2003 DDC Series 60. Both engines met the 2004 U.S. emission standard of 2.5 g/bhp-h NOx+HC (3.35 g/kW-h) and utilized exhaust gas recirculation (EGR). All emission tests employed the heavy-duty transient procedure as specified in the U.S. Code of Federal Regulations. Reduction in PM emissions and increase in NOx emissions were observed for all biodiesels in all engines, confirming observations made in older engines. On average PM was reduced by 25% and NOx increased by 3% for the two engines tested for a variety of B20 blends. These changes are slightly larger in magnitude, but in the same range as observed in older engines.

Particle size distribution and number concentration were measured in the dilute exhaust of a heavy-duty diesel engine for steady-state and transient engine operation using two different dilution systems that included a full flow CVS that was coupled to an ejector pump (CVS-EP), and a double-ejector micro-dilution tunnel (DEMDT) that was connected to engine exhaust close to turbocharger outlet. Measurements were performed using a scanning mobility particle sizer (SMPS), an electrical low pressure impactor (ELPI), and a parallel flow diffusion battery (PFDB). Fuels with sulfur content of about 385 ppm and 1 ppm were used for this work. The PFDB performed well in measuring nanoparticles in the size range below 56 nm when compared with the SMPS. This was especially valid when a distinct log-normal size distribution in the size range below 56 nm in diameter, the upper size limit of the PFDB, was present.

The effect of humidity on the lean misfire limit and emissions from a lean burn, natural gas engine is described in this paper, along with a description of a practical humidity compensation method for incorporation into an electronic control system. Experiments to determine the effects of humidity on the lean limit and emissions are described. Humidity increases were shown to decrease the rate of combustion, reduce NOx emissions, and increase the levels of unburned hydrocarbon (HC) and carbon monoxide (CO) emissions. Data and calculations are also presented which demonstrate that increases in humidity will cause enleanment in a typical closed loop control system utilizing a universal exhaust gas oxygen (UEGO) sensor. A prototype system for humidity sensing and subsequent compensation based on these findings was implemented, and the system was found, through additional testing, to compensate for humidity very effectively.

An experimental program was designed to determine friction characteristics between brake pads and metal rotors that could indicate a brake fluid's propensity to cause chatter in wet-brakes. Friction was measured on a bench version of the John Deere wet-brake qualification system. Rotor and pad supports were made very rigid to avoid chatter in the simulator. One type of pad was run on cast-iron and mild steel rotors using two reference oils, one giving unacceptable levels of chatter and the other giving acceptable levels as previously determined in full-scale tests on the Deere system. The outstanding discriminating characteristic was the drop in friction from breakaway of the pad from the rotor. The ratio of the initial drop in the friction coefficient between unacceptable and acceptable oils for all conditions of the testing ranged from 1.7 to 2.0

Trained human raters have been used by organizations such as the Coordinating Research Council (CRC) to assess the vehicle driveability performance effect of fuel volatility. CRC conducts workshops to test fuel effects and their impact on vehicle driveability. CRC commissioned Southwest Research Institute (SwRI) to develop a “Trick Car” vehicle that could trigger malfunctions on-demand that mimic driveability events. This vehicle has been used to train novice personnel on the CRC Driveability Procedure E-28-94. While largely effective, even well-trained human raters can be inconsistent with other raters. Further, CRC rater workshop programs used to train and calibrate raters are infrequent, and there are a limited number of available trained raters. The goal of this program was to augment or substitute human raters with an electronic driveability sensing system.

The ASTM Sequence VE test evaluates lubricant performance for controlling sludge deposits and minimizing overhead camshaft lobe wear. ILSAC asked JAMA to develop a new valve train wear replacement test since the Sequence VE test engine hardware will become obsolete in the year 2000. JAMA submitted the JASO specification M 328-951) KA24E valve train wear test. This first report presents the results of technical studies conducted when JASO M 328-95 was reviewed and the ASTM standardized version of the KA24E test (the Sequence IVA) was proposed. The cam wear mechanism was studied with the goal of improving reproducibility and repeatability. Engine torque was specified to stabilize the NOx concentration in blow-by, which improved test precision. Additionally, the specifications for induction air humidity and temperature, oil temperature control, and test fuel composition were modified when the ASTM version of the KA24E test was proposed.

A new generation of vehicle dynamics and powertrain control technologies are being developed to leverage information streams enabled via vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) connectivity [1, 2, 3, 4, 5]. While algorithms that use these connected information streams to enable improvements in energy efficiency are being studied in detail, methodologies to quantify and analyze these improvements on a vehicle have not yet been explored fully. A procedure to test and accurately measure energy-consumption benefits of a connected and automated vehicle (CAV) is presented. The first part of the test methodology enables testing in a controlled environment. A traffic simulator is built to model traffic flow in Fort Worth, Texas with sufficient accuracy. The benefits of a traffic simulator are two-fold: (1) generation of repeatable traffic scenarios and (2) evaluation of the robustness of control algorithms by introducing disturbances.