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Wall wetting of injected fuel onto the intake manifold and cylinder wall causes unpredictable transient behavior of air-fuel mixing which results in a significant emission of unburned hydrocarbon (HC) emission during cold start operation. Heated exhaust gas oxygen (HEGO) sensors cannot measure the air-fuel ratio (A/F) of exhaust gas during cold start condition. Precise and fast estimation of air/fuel ratio of the exhaust gas is required to elucidate the wall wetting phenomena and subsequent HC formation. Refined A/F estimation can enable the control of fuel injection minimizing HC emissions during cold start conditions so that HC emissions can be minimized. A new estimator for A/F of the exhaust gas has been developed. The A/F estimator described in this study utilizes measured exhaust gas temperature and general engine parameters such as engine speed, airflow, coolant temperature, etc.

Prototype intermittent swirl-generating nozzles for gasoline direct injection application were fabricated by modifying MPI injector nozzles. Design parameters include geometric configuration of nozzle internal flow passage such as orifice diameter and length, needle geometry and swirler passage designs. Operating parameters are considered such as injection pressure, ambient pressure, injected fuel mass and duration of injector opening. Performances of the nozzles have been characterized in terms of static and transient flow rate, initial and overall spray angle, penetration, mean droplet diameter and drop size distribution. Computational fluid dynamic modeling of internal flow for the nozzles provided additional insight in addition to the experimental measurements. Sprays from the prototype nozzle used for measurement in this study exhibited the general features of swirl injection sprays.

The concentrations of individual exhaust hydrocarbon species were measured as a function of air-fuel ratio and EGR in a 2-liter four-cylinder engine using a gas chromatography, for natural gas and LPG. NMHC in addition to the species of HC, other emissions such as CO2, CO and NOx were at 1800rpm for two compression ratios (8.6 and 10.6) and various EGR ratios up to 7%. Fuel conversion efficiencies were also investigated together with emissions to study the effect of engine parameters on the combustion performances in gas engines especially under the lean burn conditions. It was found that CO2 emission decreased leaner mixture strength, the higher compression ratio and certainly with smaller C value of fuel. HC emissions from LPG engine consisted primarily of propane (larger 60%), ethylene and propylene, while main emissions from natural gas were methane (larger than 60%), ethane, ethylene and propane on the average.

Influence of the inter-ring crevice, the volume between the top and second piston rings, on unburned hydrocarbon (UHC) emission was experimentally and numerically investigated. The ultimate goal of this study was to estimate the level of UHC emission induced by the blow-up of inter-ring mixture, i.e., unburned gases trapped in the inter-ring crevice. In the experiments, the inter-ring mixture was extracted to the crankcase during the late period of expansion and the early period of exhaust stroke through the engraved grooves on the lower part of cylinder wall. Extraction of the mixture resulted in the significant reductions of UHC emission in proportion to the increments of blowby flow rate, without any losses in efficiency and power. This experimental study has confirmed the importance of inter-ring crevice on UHC emission in an SI engine and established a relationship between the inter-ring mixture and UHC emission.

A new concept of misfire detection in spark ignition engines using a wide-range oxygen sensor is introduced. A wide-range oxygen sensor, installed at the confluence point of the exhaust manifold, was adopted to measure the variation in oxygen concentration in case of a misfire. The signals of the wide-range oxygen sensor were characterized over the various engine-operating conditions in order to decide the monitoring parameters for the detection of the misfire and the corresponding faulty cylinder. The effect of the sensor position, the transient response characteristics of the sensor and the cyclic variation in the signal fluctuation were also investigated. Limited response time of a commercially available sensor barely allowed to observe misfire. It was found that a misfiring could be distinguished more clearly from normal combustion through the differentiation of the sensor response signal. The differentiated signal has twin peaks for a single misfiring in a cylinder.

The present analysis concerns collapse behavior of vehicles under the quasi-static loading condition as analysis for the initial stage of conceptual design. Collapse analysis of a vehicle model with the space-framed structure is carried out using finite element limit analysis. To improve collapse response and strengthen weak parts, the dimension of the section and the position of the frame are locally changed as design parameters. The results demonstrates that the present analysis can easily predict weak parts of the structure and the change of design parameters enhances the load-carrying capacity of vehicle structures and reduces the deflection toward the passenger compartment.

Experiments were performed with a 4-stroke, natural gas fueled SI engine to investigate the effects of several parameters on engine performance under lean operating condition. A favorable effect of charge swirl on stable lean burn operation was observed at a conventional compression ratio. There was an optimum EGR rate which gave a substantial reduction in NOx emissions with minor penalties in efficiency and UHC emissions. Marginal improvement was noticed with lean operations in a long spark duration ignition system. The flame jet ignition system displayed noticeable capability in extending the lean limit. In addition, shadowgraph visualization tests were performed for combustion diagnostic purposes.

The objective of this study is to develop a neuro controlled active suspension for the ride quality improvement. The performance index of the optimal control is represented as the frequency-shaped using Parseval's theorem. The incorporation of frequency-dependent weighting matrices allow one to emphasize the specific variables related to the vibrations of the specific bands of frequencies. Once the active control law is obtained, we use the artificial neural networks to train the neuro controller to learn the relation of road input and control force. From the numerical results, we found that back propagation learning does good pattern matching and the neuro controlled suspension may reduce the vertical acceleration of the driver's seat and sprung mass motions significantly at desired bands of frequencies.