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The presented work describes how numerical modeling techniques were extended to simulate a full Selective Catalytic Reduction (SCR) NOx aftertreatement system. Besides predicting ammonia-to-NOX ratio (ANR) and uniformity index (UI) at the SCR inlet, the developed numerical model was able to predict NOx reduction and ammonia slip. To reduce the calculation time due to the complexity of the chemical process and flow field within the SCR, a semi-1D approach was developed and applied to model the SCR catalyst, which was subsequently coupled with a 3D model of the rest of the exhaust system. Droplet depletion of urea water solution (UWS) was modeled by vaporization and thermolysis techniques while ammonia generation was modeled by the thermolysis and hydrolysis method. Test data of two different SCR systems were used to calibrate the simulation results. Results obtained using the thermolysis method showed better agreement with test data compared to the vaporization method.

Water injection is an effective method for knock control in spark-ignition engines. However, the requirement of a separate water source and the cost and complexity associated with a fully integrated system creates a limitation of this method to be used in volume production engines. The engine exhaust typically contains 10-15% water vapor by volume which could be condensed and potentially stored for future use. In this study, the exhaust condensate composition was assessed for its use as an effective replacement for distilled water. Specifically, condensate samples were collected pre and post-three-way catalyst (TWC) and analyzed for acidity and composition. The composition of the pre and post-TWC condensates was found to be similar however, the pre-TWC condensate was mildly acidic. The mild acidity has the potential to corrode certain components in the intake air circuit.

As the efforts to push capabilities of current engine hardware to their durability limits increases, more accurate and reliable analysis is necessary to ensure that designs are robust. This paper evaluates a method of Conjugate Heat Transfer (CHT) analysis for a gasoline and a diesel engine that combines combustion Computational Fluid Dynamics (CFD), engine Finite Element Analysis (FEA), and cooling jacket CFD with the goal of obtaining more accurate temperature distribution and heat loss predictions in an engine compared to standard de-coupled CFD and FEA analysis methods. This novel CHT technique was successfully applied to a 2.5 liter GM LHU gasoline engine at 3000 rpm and a 15.0 liter Cummins ISX heavy duty diesel engine operating at 1250 rpm. Combustion CFD simulations results for the gasoline and diesel engines are validated with the experimental data for cylinder pressure and heat release rate.

With the increasing level of electrification of on-road, off-road and stationary applications, use of larger lithium-ion battery packs has become essential. These packs require large capital investments on the order of millions of dollars and pose a significant risk of self-annihilation without rigorous safety evaluation and management. Testing these larger battery packs to validate design changes can be cost prohibitive. A reliable numerical simulation tool to predict battery thermal runaway under various abuse scenarios is essential to engineer safety into the battery pack design stage. A comprehensive testing & simulation workflow has been established to calibrate and validate the numerical modeling approach with the test data for each of the individual sub model - electrochemical, internal short circuit and thermal abuse model. A four-equation thermal abuse model was built and validated for lithium-ion 21700 form factor cylindrical cells using NCA cathodes.

General agreement exists that the ultimate goals of traffic accident research are to reduce fatality, mitigate injury and decrease economic loss to society. Although massive quantities of data have been collected in local, national and international programs, attempts by analysts to use these data to explore ideas or support hypotheses have been met by a variety of problems. Specifically, the coded variables in the different files are not consistent and little information on accident etiology is collected. Examples of the inadequacies of present data in terms of the collected and coded variables are shown. The vehicular, environmental and human (consisting of human factors and injury factors) variables are disproportionately represented in most existing data files in terms of recognized statistical evidence of accident causation. A systems approach is needed to identify critical, currently neglected variables and develop units of measurement and data collection procedures.

Accurately characterizing vehicle drive cycles plays a fundamental role in assessing the performance of new vehicle technologies. Repeatable, short duration representative drive cycles facilitate more informed decision making, resulting in improved test procedures and more successful vehicle designs. With continued growth in the deployment of onboard telematics systems employing global positioning systems (GPS), large scale, low cost collection of real-world vehicle drive cycle data has become a reality. As a result of these technological advances, researchers, designers, and engineers are no longer constrained by lack of operating data when developing and optimizing technology, but rather by resources available for testing and simulation. Experimental testing is expensive and time consuming, therefore the need exists for a fast and accurate means of generating representative cycles from large volumes of real-world driving data.

Until recently, U.S. government efforts to dramatically reduce emissions, greenhouse gases and vehicle fuel consumption have primarily focused on passenger car applications. Similar aggressive reductions need to be extended to heavy vehicles such as delivery trucks, buses, and motorhomes. However, the wide range of torques, speeds, and powers that such vehicles must operate under makes it difficult for any current powertrain system to provide the desired improvements in emissions and fuel economy. Hybrid electric powertrains provide the most promising, near-term technology that can satisfy these requirements. This paper highlights the configuration and benefits of a hybrid electric powertrain capable of operating in either a parallel or series mode. It describes the hybrid electric components in the system, including the electric motors, power electronics and batteries.

Vehicle designers make use of vehicle performance programs such as RAPTOR™ to predict the performance of concept vehicles over ranges of industry standard drive cycles. However, the accuracy of such predictions may be greatly influenced by factors requiring more specialist simulation capabilities. For example, fuel economy prediction will be heavily influenced by the performance of the engine cooling system and its impact on the vehicle's aerodynamic drag, and the load from the air-conditioning system. To improve the predictions, specialist simulation capabilities need to be applied to these aspects, and brought together with the vehicle performance calculations through co-simulation. This paper describes the approach used to enable this cosimulation and the benefits achieved by the vehicle designer.

Accurate evaluation of vehicles' transient total power requirement helps achieving further improvements in vehicle fuel efficiency. When operated, the air-conditioning (A/C) system is the largest auxiliary load on a vehicle, therefore accurate evaluation of the load it places on the vehicle's engine and/or energy storage system is especially important. Vehicle simulation models, such as "Autonomie," have been used by OEMs to evaluate vehicles' energy performance. However, the load from the A/C system on the engine or on the energy storage system has not always been modeled in sufficient detail. A transient A/C simulation tool incorporated into vehicle simulation models would also provide a tool for developing more efficient A/C systems through a thorough consideration of the transient A/C system performance. The dynamic system simulation software MATLAB/Simulink® is frequently used by vehicle controls engineers to develop new and more efficient vehicle energy system controls.

Next generation vehicles are under environmental and economic pressure to reduce emissions and increase fuel economy, while maintaining the same ride and performance characteristics of present day combustion engine automobiles. This has prompted researchers to investigate hybrid vehicles as one possible solution to this challenge. At Southwest Research Institute (SwRI), a unique parallel hybrid drivetrain was designed and prototyped. This hybrid drivetrain alleviates the disadvantages of series hybrid drivetrains by directly coupling the driving wheels to two power sources, namely an engine and an electric motor. At the same time, the design allows the engine speed to be decoupled from the vehicle speed, allowing the engine to operate at its most efficient state. This paper describes the drivetrain, its components, and the test stand that was assembled to test the parallel hybrid drivetrain.

A physics-based spark ignition model was developed and integrated into a commercial CFD code. The model predicted the spark discharge process based on the electrical parameters of the secondary ignition circuit, tracked the spark motion as it was stretched by in-cylinder gas motion, and determined the resulting energy deposition to the gas. In concert with the existing kinetic solver in the CFD code, the resulting ignition and flame propagation processes were simulated. The model results have been validated against both imaging rig experiments of the spark in moving air and against engine experimental data. The model was able to replicate the key features of the spark and to capture the cyclic variability of high-dilution combustion when multiple engine cycles were simulated.

Existing expert systems have a high percentage agreement with human experts in a particular field in many situations. However, in many ways their overall behavior is not like that of a human expert. These areas include the inability to give flexible, functional explanations of their reasoning processes and the failure to degrade gracefully when dealing with problems at the periphery of their knowledge. These two important shortcomings can be improved when the right knowledge is available to the system. This paper presents an expert system design, called the Integrated Diagnostic Model (IDM), that integrates two sources of knowledge: a shallow, empirically-oriented, experiential knowledge base and a deep, functionally-oriented, physical knowledge base. To demonstrate the IDM's usefulness in the problem area of diagnosis and repair of electrical and mechanical devices, two implementations and our experience with them is described.

A unique single cylinder engine was used to assess engine performance and combustion characteristics at three different strokes, with all other variables held constant. The engine utilized a production four-valve, pentroof cylinder head with an 86mm bore. The stock piston was used, and a variable deck height design allowed three crankshafts with strokes of 86, 98, and 115mm to be tested. The compression ratio was also held constant. The engine was run with a controlled boost-to-backpressure ratio to simulate turbocharged operation, and the valve events were optimized for each operating condition using intake and exhaust cam phasers. EGR rates were swept from zero to twenty percent under low and high speed conditions, at MBT and maximum retard ignition timings. The increased stroke engines demonstrated efficiency gains under all operating conditions, as well as measurably reduced 10-to-90 percent burn durations.

The Automotive Deployment Options Projection Tool (ADOPT) is a light-duty vehicle consumer choice and stock model supported by the U.S. Department of Energy's Vehicle Technologies Office. It estimates technology improvement impacts on future U.S. light-duty vehicles sales, petroleum use, and greenhouse gas emissions. ADOPT uses techniques from the multinomial logit method and the mixed logit method to estimate vehicle sales. Specifically, it estimate sales based on the weighted value of key attributes including vehicle price, fuel cost, acceleration, range and usable volume. The average importance of several attributes changes nonlinearly across its range and changes with income. For several attributes, a distribution of importance around the average value is used to represent consumer heterogeneity. The majority of existing vehicle makes, models, and trims are included to fully represent the market. The Corporate Average Fuel Economy regulations are enforced.

Fuel costs to operate large trucks have risen substantially in the last few years and, based on petroleum supply/demand curves, that trend is expected to continue for the foreseeable future. Non-propulsion or parasitic loads in a large truck account for a significant percentage of overall engine load, leading to reductions in overall vehicle fuel economy. Electrification of parasitic loads offers a way of minimizing non-propulsion engine loads, using the full motive force of the engine for propulsion and maximizing vehicle fuel economy. This paper covers the integration and testing of electrified accessories, powered by a fuel cell auxiliary power unit (APU) in a Class 8 tractor. It is a continuation of the efforts initially published in SAE paper 2005-01-0016.

Increasing fuel costs and the desire for reduced dependence on foreign oil has brought the diesel engine to the forefront of future medium-duty vehicle applications in the United States due to its higher thermal efficiency and superior durability. The main obstacle to the increased use of diesel engines in this platform is the upcoming extremely stringent, Tier 2 emission standard. In order to succeed, diesel vehicles must comply with emissions standards while maintaining their excellent fuel economy. The availability of technologies such as common rail fuel injection systems, low sulfur diesel fuel, NOX adsorber catalysts (NAC), and diesel particle filters (DPFs) allow the development of powertrain systems that have the potential to comply with these future requirements. In meeting the Tier 2 emissions standards, the heavy light-duty trucks (HLDTs) and medium-duty passenger vehicles (MDPVs) will face the greatest technological challenges. In support of this, the U.S.

Increasing fuel costs and the desire for reduced dependence on foreign oil has brought the diesel engine to the forefront of future medium-duty vehicle applications in the United States due to its higher thermal efficiency and superior durability. The main obstacle to the increased use of diesel engines in this platform is the upcoming extremely stringent, Tier 2 emission standard. In order to succeed, diesel vehicles must comply with emissions standards while maintaining their excellent fuel economy. The availability of technologies such as common rail fuel injection systems, low sulfur diesel fuel, NOX adsorber catalysts (NAC), and diesel particle filters (DPFs) allow the development of powertrain systems that have the potential to comply with these future requirements. In meeting the Tier 2 emissions standards, the heavy light-duty trucks (HLDTs) and medium-duty passenger vehicles (MDPVs) will face the greatest technological challenges. In support of this, the U.S.

Fuel cell hybrid vehicles (FCHVs) use an energy management strategy to partition the power supplied by the fuel cell and energy storage system (ESS). This paper presents an adaptive energy management strategy, created in the ADVISOR™ software, for a series FCHV. The strategy uses a local or “real-time” optimization approach, which aims to reduce total energy consumption at each instantaneous time interval by dynamically adjusting the amount of power supplied by the fuel cell and ESS. Compared with a static control strategy, the adaptive strategy improved the simulated FCHV's fuel economy by 1.4%-8.5%, depending on the drive cycle.

It has been shown within the catalyst industry that the emission performance with higher cell density technology and therefore with higher specific geometric area is improved. The focus of this study was to compare the overall performance of high cell density catalysts, up to 1600cpsi, using a MY 2001 production vehicle with a 4.7ltr.V8 engine. The substrates were configured to be on the edge of the design capability. The goal was to develop cost optimized systems with similar emission and back pressure performance, which meet physical and production requirements. This paper will present the results of a preliminary computer simulation study and the final emission testing of a production vehicle. For the pre-evaluation a numerical simulation model was used to compare the light-off performance of different substrate designs in the cold start portion of the FTP test cycle.

Chassis dynamometer tests are often used to determine vehicle fuel economy (FE). Since the entire vehicle is used, these methods are generally accepted to be more representative of ‘real-world’ conditions than engine dynamometer tests or small-scale bench tests. Unfortunately, evaluating vehicle fuel economy via this means introduces significant variability that can readily be mitigated with engine dynamometer and bench tests. Recently, improvements to controls and procedures have led to drastically improved test precision in chassis dynamometer testing. Described herein are chassis dynamometer results from five fully formulated engine oils (utilizing improved testing protocols on the Federal Test Procedure (FTP-75) and Highway Fuel Economy Test (HwFET) cycles) which not only show statistically significant FE changes across viscosity grades but also meaningful FE differentiation within a viscosity grade where additive systems have been modified.