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The presenter will discuss challenges introduced by OBD in developing a product for worldwide markets and the impact of varying worldwide requirements for OBD performance and certification. Presenter Benjamin Zwissler, Cummins Inc.

The development and release process for Cummins first US HD OBD certified product encountered numerous hurdles. Beyond the purely "technical" difficulties, there were also challenges related to our product development processes. This presentation provides recommendations for HD OBD product development processes & improvements. Topics will include: Training needs for program management, Performance tuning strategies vs. OBD needs, Planning for post-certification product changes, etc. Presenter Greg Moore, Cummins Inc.

This paper presents an extension of our earlier work on Cummins Vehicle Mission Simulation (VMS) software. Previously, we presented VMS as a Windows based analysis tool to simulate vehicle missions quickly and to gauge, communicate, and improve the value proposition of Cummins engines to customers. Presenter Nagesh Belludi, Cummins Inc.

The focus of this research is to perform a detailed investigation of the tradeoffs between mass, efficiency, service factor (SF), power factor (PF), and cost of commercially available induction machines (IMs). To support this effort, data from a large number of IMs is used to establish Pareto-optimal fronts between these competing objectives. From the Pareto-optimal fronts, relatively straightforward models are formulated for the mass versus loss, cost versus loss, SF versus mass, PF versus cost. Parameters of the models are obtained using a genetic algorithm (GA).

The paper will discuss the design and development of heavy-duty diesel engines to meet the US EPA 2010 on-highway standards - 0.2 g/HP-hr NOx and 0.01 g/HP-hr particulate matter (PM). In meeting these standards a combination of in-cylinder control and aftertreatment control for both NOx and particulate has been used. For NOx control, a combination of cooled exhaust gas recirculation (EGR) and selective catalytic reduction (SCR) is used. The SCR catalyst uses copper zeolite to achieve high levels of NOx conversion efficiency with minimal ammonia slip and unparalleled thermal durability. For particulate control, a diesel particulate filter (DPF) with upstream oxidation catalyst (DOC) is used. While the DPF may be actively regenerated when required, it operates predominantly with passive regeneration - enabled by the high NOx levels between the engine and the DPF, associated with high efficiency SCR systems and NO₂ production across the DOC.

In 2006, there were approximately 23,500 rear-end crashes involving heavy trucks (i.e., gross vehicle weight greater than 4,536 kg). The Enhanced Rear Signaling (ERS) for Heavy Trucks project was developed by the Federal Motor Carrier Safety Administration (FMCSA) to investigate methods to reduce or mitigate those crashes where a heavy truck has been struck from behind by another vehicle. Visual warnings have been shown to be effective, assuming the following driver is looking directly at the warning display or has his/her eyes drawn to it. A visual warning can be placed where it is needed and it can be designed so that its meaning is nearly unambiguous. FMCSA contracted with the Virginia Tech Transportation Institute (VTTI) to investigate potential benefit of additional rear warning-light configurations as rear-end crash countermeasures for heavy trucks.

The low-temperature performance characteristics of a commercial lean NOX trap catalyst were evaluated using infra-red thermography (IRT) before and after a high-temperature aging step. Reaction tests included propylene oxidation, oxygen storage capacity measurements, and simulated cycling conditions for NOX reduction, using H₂ as the reductant during the regeneration step of the cycle. Testing with and without NO in the lean phase showed thermal differences between the reductant used in reducing the stored oxygen and that for nitrate decomposition and reduction. IRT clearly demonstrated where NOX trapping and regeneration were occurring spatially as a function of regeneration conditions, with variables including hydrogen content of the regeneration phase and lean- and rich-phase cycle times.

Cu- and Fe-zeolite SCR catalysts emerged in recent years as the primary candidates for meeting the increasingly stringent lean exhaust emission regulations, due to their outstanding activity and durability characteristics. It is commonly known that Cu-zeolite catalysts possess superior activity to Fe-zeolites, in particular at low temperatures and sub-optimal NO₂/NOx ratios. In this work, we elucidate some underlying mechanistic differences between these two classes of catalysts, first based on their NO oxidation abilities, and then based on the relative properties of the two types of exchanged metal sites. Finally, by using the ammonia coverage-dependent NOx performance, we illustrate that state-of-the-art Fe-zeolites can perform better under certain transient conditions than in steady-state.

Ion current sensors have been considered for the feedback electronic control of gasoline and diesel engines and for onboard vehicles powered by both engines, while operating on their conventional cycles or on the HCCI mode. The characteristics of the ion current signal depend on the progression of the combustion process and the properties of the combustion products in each engine. There are large differences in the properties of the combustible mixture, ignition process and combustion in both engines, when they operate on their conventional cycles. In SI engines, the charge is homogeneous with an equivalence ratio close to unity, ignition is initiated by an electric spark and combustion is through a flame propagating from the spark plug into the rest of the charge.

Climate change due to greenhouse gas emissions has led to new vehicle emissions standards which in turn have led to a call for vehicle technologies to meet these standards. Modeling of vehicle fuel consumption and emissions emerged as an effective tool to help in developing and assessing such technologies, to help in predicting aggregate vehicle fuel consumption and emissions, and to complement traffic simulation models. The paper identifies the current state of the art on vehicle fuel consumption and emissions modeling and its utilization to test the environmental impact of the Intelligent Transportation Systems (ITS)’ measures and to evaluate transportation network improvements. The study presents the relevant models to ITS in the key classifications of models in this research area. It demonstrates that the trends of vehicle fuel consumption and emissions provided by current models generally do satisfactorily replicate field data trends.

A Location-Aware Adaptive Vehicle Dynamics System (LAAVDS) is developed to assist the driver in maintaining vehicle handling capabilities through various driving maneuvers. An integral part of this System is an Intervention Strategy that uses a novel measure of handling capability, the Performance Margin, to assess the need to intervene. Through this strategy, the driver's commands are modulated to affect desired changes to the Performance Margin in a manner that is minimally intrusive to the driver's control authority. Real-time implementation requires the development of computationally efficient predictive vehicle models. This work develops one means to alter the future vehicle states: modulating the driver's brake commands. This control strategy must be considered in relationship to changes in the throttle commands. Three key elements of this strategy are developed in this work.

A Location-Aware Adaptive Vehicle Dynamics System (LAAVDS) is developed to assist the driver in maintaining vehicle handling capabilities through various driving maneuvers. An Intervention Strategy uses a novel measure of handling capability, the Performance Margin, to assess the need to intervene. The driver's commands are modulated to affect desired changes to the Performance Margin in a manner that is minimally intrusive to the driver's control authority. Real-time implementation requires the development of computationally efficient predictive vehicle models which is the focus of this work. This work develops one means to alter the future vehicle states: modulating the driver's throttle commands. First, changes to the longitudinal force are translated to changes in engine torque based on the current operating state (torque and speed) of the engine.

Ride control of military vehicles is challenging due to varied terrain and mission requirements such as operating weight. Achieving top speeds on rough terrain is typically considered a key performance parameter, which is always constrained by ride discomfort. Many military vehicles using passive suspensions suffer with compromised performance due to single tuning solution. To further stretch the performance domain to achieving higher speeds on rough roads, semi-active suspensions may offer a wide range of damping possibilities under varying conditions. In this paper, various semi-active control strategies are examined, and improvements have been made, particularly, to the acceleration-driven damper (ADD) strategy to make the approach more robust for varying operating conditions. A seven degrees of freedom ride model and a quarter-car model were developed that were excited by a random road process input modeled using an auto-regressive time series model.

In recent years, the focus on engine parasitic losses has increased as a result of the efforts to increase engine efficiency and reduce greenhouse gasses. The engine gear train, used to time the valve system and drive auxiliary loads, contributes to the overall engine parasitic losses. Anti-backlash gears are often used in engine gear trains to reduce gear rattle noise resulting from the torsional excitation of the gear train by the engine output torque. Friction between sliding surfaces at the gear tooth is a major source of power loss in gear trains. The effect of using anti-backlash gears on the gear friction power loss is not well known. As a part of the effort to reduce parasitic losses, the increase in friction power loss in the Cummins ISX 15 gear train due to the anti-backlash gear was quantitatively determined by modifying the methods given in ISO 14179-2 to fit the anti-backlash gear sub-assembly.

In order to continue the effort of converting traditional internal combustion engine (ICE)-based vehicles into hybrid-electric vehicles (HEV), it is important to consider a variety of design architectures in which hybrid-electric operation is achieved. Such architectures include power split, parallel, and series. Of the previously stated architectures, the Purdue EcoMakers of the EcoCar 2 international Advanced Vehicle Technology Competition (AVTC) have chosen a parallel-through-the-road architecture for their 2013 Chevrolet Malibu provided by General Motors. From this, the Purdue EcoMaker vehicle design will be used as a case study for the design challenges and optimization strategies that are experienced when choosing this specific architecture for a light-duty passenger vehicle. This paper will focus on the design procedure and structural analysis of the custom rear suspension cradle created by the Purdue EcoMakers.

Safety and minimal transit time are vital during transportation of essential commodities and passengers, especially in winter conditions. Icy roads are the worst driving conditions with the least available friction, leaving valuable cargo and precious human lives at stake. The study investigates the available friction at the tire-ice interface due to changes in key operational parameters. Experimental analysis of tractive performance of tires on ice was carried out indoor, using the terramechanics rig located at the Advanced Vehicle Dynamics Laboratory (AVDL) at Virginia Tech. The friction-slip ratio curves obtained from indoor testing were inputted into TruckSIM, defining tire behavior for various ice scenarios and then simulating performance of trucks on ice. The shortcomings of simulations in considering the effects of all the operational parameters result in differences between findings of indoor testing and truck performance simulations.

Flexible polyurethane foam is the main cushioning element used in car seats. Optimization of an occupied seat's static and dynamic behavior requires models of foam that are accurate over a wide range of excitation and pre-compression conditions. In this research, a method is described to estimate the parameters of a global model of the foam behavior from data gathered in a series of impulse tests at different settling points. The estimated model is capable of describing the responses gathered from all the impulse tests using a unique set of parameters. The global model structure includes a nonlinear elastic term and a hereditary viscoelastic term. The model can be used to predict the settling point for each mass used and, by expanding the model about that settling point, local linear models of the response to impulsive excitation can be derived. From this analysis the relationship between the local linear model parameters and the global model parameters is defined.

Studying the kinetic and kinematics of the rim-tire combination is very important in full vehicle simulations, as well as for the tire design process. Tire maneuvers are either quasi-static, such as steady-state rolling, or dynamic, such as traction and braking. The rolling of the tire over obstacles and potholes and, more generally, over uneven roads are other examples of tire dynamic maneuvers. In the latter case, tire dynamic models are used for durability assessment of the vehicle chassis, and should be studied using high fidelity simulation models. In this study, a three-dimensional finite element model (FEM) has been developed using the commercial software package ABAQUS. The purpose of this study is to investigate the tire dynamic behavior in multiple case studies in which the transient characteristics are highly involved.

The identification of the dominant noise sources in diesel engines and the assessment of their contribution to far-field noise is a process that can involve both fired and motored testing. In the present work, the cross-spectral densities of signals from cylinder pressure transducers, accelerometers mounted on the engine surface, and microphones (in the near and far fields), were used to identify dominant noise sources and estimate the transfer paths from the various “inputs” (i.e., the cylinder pressures, the accelerometers and the near field microphones) to the far field microphones. The method is based on singular value decomposition of the input cross-spectral matrix to relate the input measurements to independent virtual sources. The frequencies at which a particular input is strongly affected by an independent source are highlighted, and with knowledge of transducer locations, inferences can be drawn as to possible noise source mechanisms.

With increasing energy prices and concerns about the environmental impact of greenhouse gas (GHG) emissions, a growing number of national governments are putting emphasis on improving the energy efficiency of the equipment employed throughout their transportation systems. Within the U.S. transportation sector, energy use in commercial vehicles has been increasing at a faster rate than that of automobiles. A 23% increase in fuel consumption for the U.S. heavy duty truck segment is expected from 2009 to 2020. The heavy duty vehicle oil consumption is projected to grow while light duty vehicle (LDV) fuel consumption will eventually experience a decrease. By 2050, the oil consumption rate by LDVs is anticipated to decrease below 2009 levels due to CAFE standards and biofuel use. In contrast, the heavy duty oil consumption rate is anticipated to double. The increasing trend in oil consumption for heavy trucks is linked to the vitality, security, and growth of the U.S. and global economies.