6 resultados para HCCI


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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.

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The Homogeneous Charge Compression Ignition (HCCI) engine is a promising combustion concept for reducing NOx and particulate matter (PM) emissions and providing a high thermal efficiency in internal combustion engines. This concept though has limitations in the areas of combustion control and achieving stable combustion at high loads. For HCCI to be a viable option for on-road vehicles, further understanding of its combustion phenomenon and its control are essential. Thus, this thesis has a focus on both the experimental setup of an HCCI engine at Michigan Technological University (MTU) and also developing a physical numerical simulation model called the Sequential Model for Residual Affected HCCI (SMRH) to investigate performance of HCCI engines. The primary focus is on understanding the effects of intake and exhaust valve timings on HCCI combustion. For the experimental studies, this thesis provided the contributions for development of HCCI setup at MTU. In particular, this thesis made contributions in the areas of measurement of valve profiles, measurement of piston to valve contact clearance for procuring new pistons for further studies of high geometric compression ratio HCCI engines. It also consists of developing and testing a supercharging station and the setup of an electrical air heater to extend the HCCI operating region. The HCCI engine setup is based on a GM 2.0 L LHU Gen 1 engine which is a direct injected engine with variable valve timing (VVT) capabilities. For the simulation studies, a computationally efficient modeling platform has been developed and validated against experimental data from a single cylinder HCCI engine. In-cylinder pressure trace, combustion phasing (CA10, CA50, BD) and performance metrics IMEP, thermal efficiency, and CO emission are found to be in good agreement with experimental data for different operating conditions. Effects of phasing intake and exhaust valves are analyzed using SMRH. In addition, a novel index called Fuel Efficiency and Emissions (FEE) index is defined and is used to determine the optimal valve timings for engine operation through the use of FEE contour maps.

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Magdeburg, Univ., Fak. für Maschinenbau, Diss., 2011

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Combustion control is one of the key factors to obtain better performances and lower pollutant emissions for diesel, spark ignition and HCCI engines. An algorithm that allows estimating, as an example, the mean indicated torque for each cylinder, could be easily used in control strategies, in order to carry out cylinders trade-off, control the cycle to cycle variation, or detect misfires. A tool that allows evaluating the 50% of Mass Fraction Burned (MFB50), or the net Cumulative Heat Release (CHRNET), or the ROHR peak value (Rate of Heat Release), could be used to optimize spark advance or to detect knock in gasoline engines and to optimize injection pattern in diesel engines. Modern management systems are based on the control of the mean indicated torque produced by the engine: they need a real or virtual sensor in order to compare the measured value with the target one. Many studies have been performed in order to obtain an accurate and reliable over time torque estimation. The aim of this PhD activity was to develop two different algorithms: the first one is based on the instantaneous engine speed fluctuations measurement. The speed signal is picked up directly from the sensor facing the toothed wheel mounted on the engine for other control purposes. The engine speed fluctuation amplitudes depend on the combustion and on the amount of torque delivered by each cylinder. The second algorithm processes in-cylinder pressure signals in the angular domain. In this case a crankshaft encoder is not necessary, because the angular reference can be obtained using a standard sensor wheel. The results obtained with these two methodologies are compared in order to evaluate which one is suitable for on board applications, depending on the accuracy required.

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El objetivo del presente trabajo fue predecir, en función del tiempo, los campos de velocidad, presión, temperatura y concentración de especies químicas de una mezcla no reactiva de aire, gases de recirculación y combustible (iso-octano), en una pre-cámara de combustión de un motor CFR, mediante la técnica de la simulación numérica de flujo de fluidos. Para ello se revisó el procedimiento de la solución numérica de las ecuaciones de transporte, aplicadas a la pre-cámara de combustión del motor CFR. La simulación se basó en el software CFX 10. Se hizo un estudio de la sensibilidad de malla para adecuar el criterio de·convergencia que el software requiere. La pre-cámara de combustión empleada para este estudio fue una pre-cámara de combustión modificada de un motor CFR para hacer que el mismo funcione como un motor HCCI. El motor CFR está ubicado en la Universidad Politécnica de Madrid.

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The role of computer modeling has grown recently to integrate itself as an inseparable tool to experimental studies for the optimization of automotive engines and the development of future fuels. Traditionally, computer models rely on simplified global reaction steps to simulate the combustion and pollutant formation inside the internal combustion engine. With the current interest in advanced combustion modes and injection strategies, this approach depends on arbitrary adjustment of model parameters that could reduce credibility of the predictions. The purpose of this study is to enhance the combustion model of KIVA, a computational fluid dynamics code, by coupling its fluid mechanics solution with detailed kinetic reactions solved by the chemistry solver, CHEMKIN. As a result, an engine-friendly reaction mechanism for n-heptane was selected to simulate diesel oxidation. Each cell in the computational domain is considered as a perfectly-stirred reactor which undergoes adiabatic constant- volume combustion. The model was applied to an ideally-prepared homogeneous- charge compression-ignition combustion (HCCI) and direct injection (DI) diesel combustion. Ignition and combustion results show that the code successfully simulates the premixed HCCI scenario when compared to traditional combustion models. Direct injection cases, on the other hand, do not offer a reliable prediction mainly due to the lack of turbulent-mixing model, inherent in the perfectly-stirred reactor formulation. In addition, the model is sensitive to intake conditions and experimental uncertainties which require implementation of enhanced predictive tools. It is recommended that future improvements consider turbulent-mixing effects as well as optimization techniques to accurately simulate actual in-cylinder process with reduced computational cost. Furthermore, the model requires the extension of existing fuel oxidation mechanisms to include pollutant formation kinetics for emission control studies.