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Noise concerns regarding snowmobiles have increased in the recent past. Current standards, such as SAE J192 are used as guidelines for government agencies and manufacturers to regulate noise emissions for all manufactured snowmobiles. Unfortunately, the test standards available today produce results with variability that is much higher than desired. The most significant contributor to the variation in noise measurements is the test surface. The test surfaces can either be snow or grass and affects the measurement in two very distinct ways: sound propagation from the source to the receiver and the operational behavior of the snowmobile. Data is presented for a known sound pressure speaker source and different snowmobiles on various test days and test surfaces. Relationships are shown between the behavior of the sound propagation and track interaction to the ground with the pass-by noise measurements.

Building on two decades of expertise, a fourth generation fleet test protocol is presented for assessing the response of engine performance to gasoline additive treatment. In this case, the ability of additives to remove pre-existing deposit from the intake systems of port fuel injected vehicles has been examined. The protocol is capable of identifying real benefits under realistic market conditions, isolating fuel performance from other effects thereby allowing a direct comparison between different fuels. It is cost efficient and robust to unplanned incidents. The new protocol has been applied to the development of a candidate fuel additive package for the North American market. A vehicle fleet of 5 quadruplets (5 sets of 4 matched vehicles, each set of a different model) was tested twice, assessing the intake valve clean-up performance of 3 test fuels relative to a control fuel.

Hydrogen is widely considered a promising fuel for future transportation applications for both, internal combustion engines and fuel cells. Due to their advanced stage of development and immediate availability hydrogen combustion engines could act as a bridging technology towards a wide-spread hydrogen infrastructure. Although fuel cell vehicles are expected to surpass hydrogen combustion engine vehicles in terms of efficiency, the difference in efficiency might not be as significant as widely anticipated [1]. Hydrogen combustion engines have been shown capable of achieving efficiencies of up to 45 % [2]. One of the remaining challenges is the reduction of nitric oxide emissions while achieving peak engine efficiencies. This paper summarizes research work performed on a single-cylinder hydrogen direct injection engine at Argonne National Laboratory.

The US Army is currently assessing the feasibility and defining the requirements of a Single Common Powertrain Lubricant (SCPL). This new lubricant would consist of an all-season (arctic to desert), fuel-efficient, multifunctional powertrain fluid with extended drain capabilities. As a developmental starting point, diesel engine testing has been conducted using the current MIL-PRF-46167D arctic engine oil at high temperature conditions representative of desert operation. Testing has been completed using three high density military engines: the General Engine Products 6.5L(T) engine, the Caterpillar C7, and the Detroit Diesel Series 60. Tests were conducted following two standard military testing cycles; the 210 hr Tactical Wheeled Vehicle Cycle, and the 400 hr NATO Hardware Endurance Cycle. Modifications were made to both testing procedures to more closely replicate the operation of the engine in desert-like conditions.

Conventional diesel fuel has been in the market for decades and used successfully to run diesel engines of all sizes in many applications. In order to reduce emissions and to foster energy source diversity, new fuels such as alternative and renewable, as well as new fuel formulations have entered the market. These include biodiesel, gas-to-liquid, and alternative formulations by states such as California. Performance variations in fuel economy, emissions, and compatibility for these fuels have been evaluated and debated. In some cases contradictory views have surfaced. “Sustainable”, “Renewable”, and “Clean” designations have been interchanged. Adding to the confusion, results from one fuel in one type of engine such as an older heavy-duty engine, is at times compared to that of another type such as a modern light-duty. This study was an attempt to compare the performance of several fuels in an identical environment, using the same engine, for direct comparison.

A prototype 2007 ISL Cummins diesel engine equipped with a diesel oxidation catalyst (DOC), diesel particle filter (DPF), variable geometry turbocharger (VGT), and cooled exhaust gas recirculation (EGR) was tested at Southwest Research Institute (SwRI) under a high-load accelerated durability cycle for 1000 hours with B20 soy-based biodiesel blends and ultra-low sulfur diesel (ULSD) fuel to determine the impact of B20 on engine durability, performance, emissions, and fuel consumption. At the completion of the 1000-hour test, a thorough engine teardown evaluation of the overhead, power transfer, cylinder, cooling, lube, air handling, gaskets, aftertreatment, and fuel system parts was performed. The engine operated successfully with no biodiesel-related failures. Results indicate that engine performance was essentially the same when tested at 125 and 1000 hours of accumulated durability operation.

A dilute spark-ignited engine concept has been developed as a potential low cost competitor to diesel engines by Southwest Research Institute (SwRI), with a goal of diesel-like efficiency and torque for light- and medium-duty applications and low-cost aftertreatment. The targeted aftertreatment method is a traditional three-way catalyst, which offers both an efficiency and cost advantage over typical diesel aftertreatment systems. High levels of exhaust gas recirculation (EGR) have been realized using advanced ignition systems and improved combustion, with significant improvements in emissions, efficiency, and torque resulting from using high levels of EGR. The primary motivation for this work was to understand the impact high levels of EGR would have on particulate matter (PM) formation in a port fuel injected (PFI) engine. While there are no proposed regulations for PFI engine PM levels, the potential exists for future regulations, both on a size and mass basis.

Work was performed to determine the feasibility of operating heavy-duty natural gas engines over a wide range of fuel compositions by evaluating engine performance and emission levels. Heavy-duty compressed natural gas engines from various engine manufacturers, spanning a range of model years and technologies, were evaluated using a diversity of fuel blends. Performance and regulated emission levels from these engines were evaluated using natural gas fuel blends with varying methane number (MN) and Wobbe Index in a dynamometer test cell. Eight natural gas blends were tested with each engine, and ranged from MN 75 to MN 100. Test engines included a 2007 model year Cummins ISL G, a 2006 model year Cummins C Gas Plus, a 2005 model year John Deere 6081H, a 1998 model year Cummins C Gas, and a 1999 model year Detroit Diesel Series 50G TK. All engines used lean-burn technology, except for the ISL G, which was a stoichiometric engine.

The addition of exhaust gas recirculation (EGR) has demonstrated the potential to significantly improve engine efficiency by allowing high CR operation due to a reduction in knock tendency, heat transfer, and pumping losses. In addition, EGR also reduces the engine-out emission of nitrogen oxides, particulates, and carbon monoxide while further improving efficiency at stoichiometric air/fuel ratios. However, improvements in efficiency through enhanced combustion phasing at high compression ratios can result in a significant increase in cylinder pressure. As cylinder pressure and temperature are both important parameters for estimating the durability requirements of the engine - in effect specifying the material and engineering required for the head and block - the impact of EGR on surface temperatures, when combined with the cylinder pressure data, will provide an important understanding of the design requirements for future cylinder heads.

An operational scheme with fuel-lean and exhaust gas dilution in spark-ignited engines increases thermal efficiency and decreases NOx emission, while these operations inherently induce combustion instability and thus large cycle-to-cycle variation in engine. In order to stabilize combustion variations, the development of an advanced ignition system is becoming critical. To quantify the impact of spark-ignition discharge, ignitability tests were conducted in an optically accessible combustion vessel to characterize the flame kernel development of lean methane-air mixture with CO₂ simulating exhaust diluent. A shrouded fan was used to generate turbulence in the vicinity of J-gap spark plug and a Variable Output Ignition System (VOIS) capable of producing a varied set of spark discharge patterns was developed and used as an ignition source. The main feature of the VOIS is to vary the secondary current during glow discharge including naturally decaying and truncated with multiple strikes.

The performance of an organic Rankine cycle (ORC) used to recover waste heat from the exhaust of a diesel and a spark ignition engine for electric power generation was modeled. The design elements of the ORC incorporated into the thermodynamic model were based on an experimental study performed at Oak Ridge National Laboratory in which a regenerative organic Rankine cycle system was designed, assembled and integrated into the exhaust of a 1.9 liter 4-cylinder automotive turbo-diesel. This engine was operated at a single fixed-load point at which Rankine cycle state point temperatures as well as the electrical power output of an electric generator coupled to a turbine that expanded R245fa refrigerant were measured. These data were used for model calibration.

High pressure diesel sprays were visualized under vaporizing and combusting conditions in a constant-volume combustion vessel. Near-simultaneous visualization of vapor and liquid phase fuel distribution were acquired using a hybrid shadowgraph/Mie-scattering imaging setup. This imaging technique used two pulsed LED's operating in an alternative manner to provide proper light sources for both shadowgraph and Mie scattering. In addition, combustion cases under the same ambient conditions were visualized through high-speed combustion luminosity measurement. Two single-hole diesel injectors with same nozzle diameters (100μm) but different k-factors (k0 and k1.5) were tested in this study. Detailed analysis based on spray penetration rate curves, rate of injection measurements, combustion indicators and 1D model comparison have been performed.

The diesel engine can be an effective solution to meet future greenhouse gas and fuel economy standards, especially for larger segment vehicles. However, a key challenge facing the diesel is the upcoming LEV III and Tier 3 emission standards which will require significant reductions in hydrocarbon (HC) and oxides of nitrogen (NOx) emissions. The challenge stems from the fact that diesel exhaust temperatures are much lower than gasoline engines, so the time required to achieve effective emissions control after a cold-start with typical aftertreatment devices is considerably longer. To address this challenge, a novel diesel cold-start emission control strategy was investigated on a 2L class diesel engine. This strategy combines several technologies to reduce tailpipe HC and NOx emissions before the start of the second hill of the FTP75. The technologies include both engine tuning and aftertreatment changes.

Since transient vehicle HVAC computational fluids (CFD) simulations take too long to solve in a production environment, the goal of this project is to automatically create a lumped-parameter flow network from a steady-state CFD that solves nearly instantaneously. The data mining algorithm k-means is implemented to automatically discover flow features and form the network (a reduced order model). The lumped-parameter network is implemented in the commercial thermal solver MuSES to then run as a fully transient simulation. Using this network a “localized heat transfer coefficient” is shown to be an improvement over existing techniques. Also, it was found that the use of the clustering created a new flow visualization technique. Finally, fixing clusters near equipment newly demonstrates a capability to track localized temperatures near specific objects (such as equipment in vehicles).

Southwest Research Institute (SwRI) converted a 2012 Buick Regal GS to use an engine with Dedicated EGR™ (D-EGR™). D-EGR is an engine concept that uses fuel reforming and high levels of recirculated exhaust gas (EGR) to achieve very high levels of thermal efficiency [1]. To accomplish reformation of the gasoline in a cost-effective, energy efficient manner, a dedicated cylinder is used for both the production of EGR and reformate. By operating the engine in this manner, many of the sources of losses from traditional reforming technology are eliminated and the engine can take full advantage of the benefits of reformate. The engine in the vehicle was modified to add the following components: the dedicated EGR loop, an additional injector for delivering extra fuel for reformation, a modified boost system that included a supercharger, high energy dual coil offset (DCO) ignition and other actuators used to enable the control of D-EGR combustion.

Computer programs and models are playing an increasing role in simulating vehicle crashworthiness, dynamic, and fuel efficiency. To maximize the effectiveness of these models, the validity and predictive capabilities of these models need to be assessed quantitatively. For a successful implementation of Computer Aided Engineering (CAE) models as an integrated part of the current vehicle development process, it is necessary to develop objective validation metric that has the desirable metric properties to quantify the discrepancy between multiple tests and simulation results. However, most of the outputs of dynamic systems are multiple functional responses, such as time history series. This calls for the development of an objective metric that can evaluate the differences of the multiple time histories as well as the key features under uncertainty.

A copula-based approach for model bias characterization was previously proposed [18] aiming at improving prediction accuracy compared to other model characterization approaches such as regression and Gaussian Process. This paper proposes an adaptive copula-based approach for model bias identification to enhance the available methodology. The main idea is to use cluster analysis to preprocess data, then apply the copula-based approach using information from each cluster. The final prediction accumulates predictions obtained from each cluster. Two case studies will be used to demonstrate the superiority of the adaptive copula-based approach over its predecessor.

To date, model validation metric is prominently designed for non-dynamic model responses. Though metrics for dynamic responses are also available, they are specifically designed for the vehicle impact application and uncertainties are not considered in the metric. This paper proposes the validation metric for general dynamic system responses under uncertainty. The metric makes use of the popular U-pooling approach and extends it for dynamic responses. Furthermore, shape deviation metric was proposed to be included in the validation metric with the capability of considering multiple dynamic test data. One vehicle impact model is presented to demonstrate the proposed validation metric.

Simulation based design optimization has become the common practice in automotive product development. Increasing computer models are developed to simulate various dynamic systems. Before applying these models for product development, model validation needs to be conducted to assess their validity. In model validation, for the purpose of obtaining results successfully, it is vital to select or develop appropriate metrics for specific applications. For dynamic systems, one of the key obstacles of model validation is that most of the responses are functional, such as time history curves. This calls for the development of a metric that can evaluate the differences in terms of phase shift, magnitude and shape, which requires information from both time and frequency domain. And by representing time histories in frequency domain, more intuitive information can be obtained, such as magnitude-frequency and phase-frequency characteristics.

Design optimization methods are commonly used for weight reduction subjecting to multiple constraints in automotive industry. One of the major challenges remained is to deal with a large number of design variables for large-scale design optimization problems effectively. In this paper, a new approach based on fuzzy rough set is proposed to address this issue. The concept of rough set theory is to deal with redundant information and seek for a reduced design variable set. The proposed method first exploits fuzzy rough set to screen out the insignificant or redundant design variables with regard to the output functions, then uses the reduced design variable set for design optimization. A vehicle body structure is used to demonstrate the effectiveness of the proposed method and compare with a traditional weighted sensitivity based main effect approach.