2 resultados para Cafe - Torrefação

em Digital Commons - Michigan Tech


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The push for improved fuel economy and reduced emissions has led to great achievements in engine performance and control. These achievements have increased the efficiency and power density of gasoline engines dramatically in the last two decades. With the added power density, thermal management of the engine has become increasingly important. Therefore it is critical to have accurate temperature and heat transfer models as well as data to validate them. With the recent adoption of the 2025 Corporate Average Fuel Economy(CAFE) standard, there has been a push to improve the thermal efficiency of internal combustion engines even further. Lean and dilute combustion regimes along with waste heat recovery systems are being explored as options for improving efficiency. In order to understand how these technologies will impact engine performance and each other, this research sought to analyze the engine from both a 1st law energy balance perspective, as well as from a 2nd law exergy analysis. This research also provided insights into the effects of various parameters on in-cylinder temperatures and heat transfer as well as provides data for validation of other models. It was found that the engine load was the dominant factor for the energy distribution, with higher loads resulting in lower coolant heat transfer and higher brake work and exhaust energy. From an exergy perspective, the exhaust system provided the best waste heat recovery potential due to its significantly higher temperatures compared to the cooling circuit. EGR and lean combustion both resulted in lower combustion chamber and exhaust temperatures; however, in most cases the increased flow rates resulted in a net increase in the energy in the exhaust. The exhaust exergy, on the other hand, was either increased or decreased depending on the location in the exhaust system and the other operating conditions. The effects of dilution from lean operation and EGR were compared using a dilution ratio, and the results showed that lean operation resulted in a larger increase in efficiency than the same amount of dilution with EGR. Finally, a method for identifying fuel spray impingement from piston surface temperature measurements was found. Note: The material contained in this section is planned for submission as part of a journal article and/or conference paper in the future.

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For the past three decades the automotive industry is facing two main conflicting challenges to improve fuel economy and meet emissions standards. This has driven the engineers and researchers around the world to develop engines and powertrain which can meet these two daunting challenges. Focusing on the internal combustion engines there are very few options to enhance their performance beyond the current standards without increasing the price considerably. The Homogeneous Charge Compression Ignition (HCCI) engine technology is one of the combustion techniques which has the potential to partially meet the current critical challenges including CAFE standards and stringent EPA emissions standards. HCCI works on very lean mixtures compared to current SI engines, resulting in very low combustion temperatures and ultra-low NOx emissions. These engines when controlled accurately result in ultra-low soot formation. On the other hand HCCI engines face a problem of high unburnt hydrocarbon and carbon monoxide emissions. This technology also faces acute combustion controls problem, which if not dealt properly with yields highly unfavorable operating conditions and exhaust emissions. This thesis contains two main parts. One part deals in developing an HCCI experimental setup and the other focusses on developing a grey box modelling technique to control HCCI exhaust gas emissions. The experimental part gives the complete details on modification made on the stock engine to run in HCCI mode. This part also comprises details and specifications of all the sensors, actuators and other auxiliary parts attached to the conventional SI engine in order to run and monitor the engine in SI mode and future SI-HCCI mode switching studies. In the latter part around 600 data points from two different HCCI setups for two different engines are studied. A grey-box model for emission prediction is developed. The grey box model is trained with the use of 75% data and the remaining data is used for validation purpose. An average of 70% increase in accuracy for predicting engine performance is found while using the grey-box over an empirical (black box) model during this study. The grey-box model provides a solution for the difficulty faced for real time control of an HCCI engine. The grey-box model in this thesis is the first study in literature to develop a control oriented model for predicting HCCI engine emissions for control.