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A fast time-scale 1-D dynamic diesel particulate filter model capable of resolving the pressure pulsations due to individual cylinder firing events is presented. The purpose of this model is to investigate changes in the firing frequency component of the pulsating exhaust flow at different particulate loadings. Experimental validation data and simulation results clearly show that the magnitude and phase of the firing frequency components are directly correlated to the mass of particulate stored in a diesel particulate filter. This dynamic pressure signal information may prove particularly useful for monitoring particulate load during vehicle operation.

An experimental apparatus and a numerical model have been designed and developed to examine the lubrication condition and frictional losses at the piston and cylinder interface. The experimental apparatus utilizes components from a single cylinder, ten horsepower engine in a novel suspended liner arrangement. The test rig has been specifically designed to reduce the number of operating variables while utilizing actual components and geometry. A mixed lubrication model for the complete ring-pack and piston skirt was developed to correlate with experimental measurements and provide further insight into the sources of frictional losses. The results demonstrate the effects of speed and viscosity on the overall friction losses at the piston and cylinder liner interface. Comparisons between the experimental and analytical results show good agreement.

An experimental-analytic method of determining the stress distribution in narrow faced spur gear teeth is presented. The successful application of photostress to this contact problem is reported. It utilizes a digital computer routine developed for separating stresses in any general two-dimensional region. Results for two pairs of gears are presented. Comparison is made with values predicted by the modified Lewis formula, the Kelley and Pedersen equation, and by the Belajef solution of the Hertz contact problem for two cylinders.

Mobile Earth Moving Machinery like Skid-steer loaders have tight turning radius in limited spaces due to a short wheelbase which prevents the use of suspensions in these vehicles. The absence of a suspension system exposes the vehicle to ground vibrations of high magnitude and low frequency. Vibrations reduce operator comfort, productivity and life of components. Along with vibrations, the machine productivity is also hampered by material spillage which is caused by the tilting of the bucket due to the extension of the boom. The first part of the paper focuses on vibration damping. The chassis’ vibrations are reduced by the use of an active suspension element which is the hydraulic boom cylinder which is equivalent to a spring-damper. With this objective, a linear model for the skid steer loader is developed and a state feedback control law is implemented.

The firing frequency components of the dynamic diesel particulate filter pressure signals carry significant information about the particulate load. Specifically, the normalized magnitude and relative phase of the firing frequency components exhibit clear dependence on the particulate load in a filter. Further, the test-to-test variation and back-to-back repeatability in this work was better for the dynamic pressure signal features than for the mean value pressure drop. This work provides a promising extension or alternative to the mean value pressure drop correlation to particulate load through Darcy's Law. The results may be particularly useful for filter monitoring and control.

Diesel engine cylinder deactivation (CDA) can be used to reduce petroleum consumption and greenhouse gas (GHG) emissions of the global freight transportation system. Heavy duty trucks require complex exhaust aftertreatment (A/T) in order to meet stringent emission regulations. Efficient reduction of engine-out emissions require a certain A/T system temperature range, which is achieved by thermal management via control of engine exhaust flow and temperature. Fuel efficient thermal management is a significant challenge, particularly during cold start, extended idle, urban driving, and vehicle operation in cold ambient conditions. CDA results in airflow reductions at low loads. Airflow reductions generally result in higher exhaust gas temperatures and lower exhaust flow rates, which are beneficial for maintaining already elevated component temperatures. Airflow reductions also reduce pumping work, which improves fuel efficiency.

In this paper, computations of pulsating flows in a duct with multiple inlets using the lattice Boltzmann method (LBM) are reported. As future emissions standards present a significant challenge for Diesel engine manufacturers, several options are being investigated to identify strategies to meet such regulations. Exhaust gas aftertreatment is one of the most important among them. As the performance of the various aftertreatment devices is sensitive to the flow conditions in the exhaust, a greater understanding of the flows under pulsating conditions in the presence of multiple cylinders is needed. The Lattice Boltzmann Method (LBM) is a relatively new and promising computational approach for applications to fluid dynamics problems. Two advantages of the method relative to traditional methods are ease of implementation and ease of parallelization and performance on parallel computers.

A gravimetric particulate measurement system, which extracts samples isokinetically from raw exhaust, is presented to quantify the particulate mass stored in diesel particulate filters. The purpose of this measurement system is to facilitate the study of wall-flow filter behavior at different particulate load levels. Within this paper, the design considerations for the particulate measurement system are detailed and its operation is described. The accuracy of the measurement is examined through a theoretical error analysis and direct experimental comparison to the differential weight of a diesel particulate filter. Experimental results are also presented to validate the ability of the system to maintain the isokinetic sampling condition.

The latest US emission regulations require dramatic reductions in Nitrogen Oxide (NOx) emissions from vehicular diesel engines. Selective Catalytic Reduction (SCR) is the current technology that achieves NOx reductions of up to 90%. It is typically mounted downstream of the existing after-treatment system, i.e., after the Diesel Oxidation Catalyst (DOC) and Diesel Particulate Filter (DPF). Accurate prediction of input NO₂:NO ratio is useful for control of SCR urea injection to reduce NOx output and NH₃ slippage downstream of the SCR catalyst. Most oxidation of NO to NO₂ occurs in the DOC since its main function is to oxidize emission constituents. The DOC thus determines the NO₂:NO ratio as feedgas to the SCR catalyst. The prediction of NO₂:NO ratio varies as the catalyst in the DOC ages or deteriorates due to poisoning. Thus, the DOC prediction model has to take into account the correlation of DOC conversion effectiveness and the aging of the catalyst.

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.