965 resultados para Diesel engine generator
Resumo:
"February 1968."
Resumo:
"July 1977."
Resumo:
"10 October 1989."
Resumo:
"March 1979."
Resumo:
Starting induction motors on isolated or weak systems is a highly dynamic process that can cause motor and load damage as well as electrical network fluctuations. Mechanical damage is associated with the high starting current drawn by a ramping induction motor. In order to compensate the load increase, the voltage of the electrical system decreases. Different starting methods can be applied to the electrical system to reduce these and other starting method issues. The purpose of this thesis is to build accurate and usable simulation models that can aid the designer in making the choice of an appropriate motor starting method. The specific case addressed is the situation where a diesel-generator set is used as the electrical supplied source to the induction motor. The most commonly used starting methods equivalent models are simulated and compared to each other. The main contributions of this thesis is that motor dynamic impedance is continuously calculated and fed back to the generator model to simulate the coupling of the electrical system. The comparative analysis given by the simulations has shown reasonably similar characteristics to other comparative studies. The diesel-generator and induction motor simulations have shown good results, and can adequately demonstrate the dynamics for testing and comparing the starting methods. Further work is suggested to refine the equivalent impedance presented in this thesis.
Resumo:
Päästöjen vähentäminen on ollut viime vuosina tärkeässä osassa polttomoottoreita kehitettäessä.Monet viralliset tahot asettavat uusia tiukempia päästörajoituksia. Päästörajatovat tyypillisesti olleet tiukimmat autoteollisuuden valmistamille pienille nopeakäyntisille diesel-moottoreille, mutta viime aikoina paineita on kohdistunut myös suurempiin keskinopeisiin ja hidaskäyntisiin diesel-moottoreihin. Päästörajat ovat erilaisia riippuen moottorin tyypistä, käytetystä polttoaineesta ja paikasta missä moottoria käytetään johtuen erilaisista paikallisista laeista ja asetuksista. Eniten huomiota diesel-moottorin päästöissä täytyy kohdistaa typen oksideihin, savun muodostukseen sekä partikkeleihin. Laskennallisen virtausmekaniikan (CFD) avulla on hyvät mahdollisuudet tutkia diesel-moottorin sylinterissä tapahtuvia ilmiöitä palamisen aikana. CFD on hyödyllinen työkalu arvioitaessa moottorin suorituskykyä ja päästöjen muodostumista. CFD:llä on mahdollista testata erilaisten parametrien ja geometrioiden vaikutusta ilman kalliita moottorinkoeajoja. CFD:tä voidaan käyttää myös opetustarkoituksessa lisäämään paloprosessin tuntemusta. Tulevaisuudessa palamissimuloinnit CFD:llä tulevat epäilemättä olemaan tärkeä osa moottorin kehityksessä. Tässä diplomityössä on tehty palamissimuloinnit kahteen erilaisilla poittoaineenruiskutuslaitteistoilla varustettuun Wärtsilän keskinopeaan diesel-moottoriin. W46 moottorin ruiskutuslaitteisto on perinteinen mekaanisesti ohjattu pumppusuutin ja W46-CR moottorissa on elektronisesti ohjattu 'common rail' ruiskutuslaitteisto. Näiden moottorien ja käytössä olevien ruiskutusprofiilien lisäksi on simuloinneilla testattu erilaisia uusia ruiskutusprofiileja, jotta erityyppisten profiilien hyvät ja huonot ominaisuudet tulisivat selville. Matalalla kuormalla kiinnostuksen kohteena on nokipäästöjen muodostus ja täydellä kuormalla NOx-päästöjen muodostus ja polttoaineen kulutus. Simulointien tulokset osoittivat, että noen muodostusta matalalla kuormalla voidaan selvästi vähentää monivaiheisella ruiskutuksella, jossa yksi ruiskutusjakso jaetaan kahteen tai useampaan jaksoon. Erityisen tehokas noen vähentämisessä vaikuttaa olevan ns. jälkiruiskutus (post injection). Matalat NOx-päästöt ja hyvä polttoaineen kulutus täydellä kuormalla on mahdollista saavuttaaasteittain nostettavalla ruiskutusnopeudella.
Resumo:
Brazil is doing a major effort to find alternatives to diesel oil as combustible. Some study lines are oriented to the development of vegetable oils used as fuel, as a source of getting cheaper and have higher energy density than the converted vegetable oils, and less risk of environmental contamination. The aim of this study was to evaluate the performance, the useful life of the lubricant and some components of a Diesel Cycle engine, with an electronic injection system, in a long-term test operating with a preheated blend (65°C) of 50% (v v-1) of soybean oil in petrodiesel. There was a reduction of the useful life of the injectors which presented failure because of high wear with 264 hours of operation and showed an increase in emissions of particulate matter (opacity) which may be assigned to the failures occurred in the injection system. An increase in the useful life of the lubricant, when compared with the literature was also observed. The electronic injection system may favor the burning of the tested fuel. The test was interrupted with 264 hours because of failures in the injection system.
Resumo:
DI Diesel engine are widely used both for industrial and automotive applications due to their durability and fuel economy. Nonetheless, increasing environmental concerns force that type of engine to comply with increasingly demanding emission limits, so that, it has become mandatory to develop a robust design methodology of the DI Diesel combustion system focused on reduction of soot and NOx simultaneously while maintaining a reasonable fuel economy. In recent years, genetic algorithms and CFD three-dimensional combustion simulations have been successfully applied to that kind of problem. However, combining GAs optimization with actual CFD three-dimensional combustion simulations can be too onerous since a large number of calculations is usually needed for the genetic algorithm to converge, resulting in a high computational cost and, thus, limiting the suitability of this method for industrial processes. In order to make the optimization process less time-consuming, CFD simulations can be more conveniently used to generate a training set for the learning process of an artificial neural network which, once correctly trained, can be used to forecast the engine outputs as a function of the design parameters during a GA optimization performing a so-called virtual optimization. In the current work, a numerical methodology for the multi-objective virtual optimization of the combustion of an automotive DI Diesel engine, which relies on artificial neural networks and genetic algorithms, was developed.
Resumo:
Traditionally, the study of internal combustion engines operation has focused on the steady-state performance. However, the daily driving schedule of automotive engines is inherently related to unsteady conditions. There are various operating conditions experienced by (diesel) engines that can be classified as transient. Besides the variation of the engine operating point, in terms of engine speed and torque, also the warm up phase can be considered as a transient condition. Chapter 2 has to do with this thermal transient condition; more precisely the main issue is the performance of a Selective Catalytic Reduction (SCR) system during cold start and warm up phases of the engine. The proposal of the underlying work is to investigate and identify optimal exhaust line heating strategies, to provide a fast activation of the catalytic reactions on SCR. Chapters 3 and 4 focus the attention on the dynamic behavior of the engine, when considering typical driving conditions. The common approach to dynamic optimization involves the solution of a single optimal-control problem. However, this approach requires the availability of models that are valid throughout the whole engine operating range and actuator ranges. In addition, the result of the optimization is meaningful only if the model is very accurate. Chapter 3 proposes a methodology to circumvent those demanding requirements: an iteration between transient measurements to refine a purpose-built model and a dynamic optimization which is constrained to the model validity region. Moreover all numerical methods required to implement this procedure are presented. Chapter 4 proposes an approach to derive a transient feedforward control system in an automated way. It relies on optimal control theory to solve a dynamic optimization problem for fast transients. From the optimal solutions, the relevant information is extracted and stored in maps spanned by the engine speed and the torque gradient.
Resumo:
This is the first part of a study investigating a model-based transient calibration process for diesel engines. The motivation is to populate hundreds of parameters (which can be calibrated) in a methodical and optimum manner by using model-based optimization in conjunction with the manual process so that, relative to the manual process used by itself, a significant improvement in transient emissions and fuel consumption and a sizable reduction in calibration time and test cell requirements is achieved. Empirical transient modelling and optimization has been addressed in the second part of this work, while the required data for model training and generalization are the focus of the current work. Transient and steady-state data from a turbocharged multicylinder diesel engine have been examined from a model training perspective. A single-cylinder engine with external air-handling has been used to expand the steady-state data to encompass transient parameter space. Based on comparative model performance and differences in the non-parametric space, primarily driven by a high engine difference between exhaust and intake manifold pressures (ΔP) during transients, it has been recommended that transient emission models should be trained with transient training data. It has been shown that electronic control module (ECM) estimates of transient charge flow and the exhaust gas recirculation (EGR) fraction cannot be accurate at the high engine ΔP frequently encountered during transient operation, and that such estimates do not account for cylinder-to-cylinder variation. The effects of high engine ΔP must therefore be incorporated empirically by using transient data generated from a spectrum of transient calibrations. Specific recommendations on how to choose such calibrations, how many data to acquire, and how to specify transient segments for data acquisition have been made. Methods to process transient data to account for transport delays and sensor lags have been developed. The processed data have then been visualized using statistical means to understand transient emission formation. Two modes of transient opacity formation have been observed and described. The first mode is driven by high engine ΔP and low fresh air flowrates, while the second mode is driven by high engine ΔP and high EGR flowrates. The EGR fraction is inaccurately estimated at both modes, while EGR distribution has been shown to be present but unaccounted for by the ECM. The two modes and associated phenomena are essential to understanding why transient emission models are calibration dependent and furthermore how to choose training data that will result in good model generalization.
Resumo:
This is the second part of a study investigating a model-based transient calibration process for diesel engines. The first part addressed the data requirements and data processing required for empirical transient emission and torque models. The current work focuses on modelling and optimization. The unexpected result of this investigation is that when trained on transient data, simple regression models perform better than more powerful methods such as neural networks or localized regression. This result has been attributed to extrapolation over data that have estimated rather than measured transient air-handling parameters. The challenges of detecting and preventing extrapolation using statistical methods that work well with steady-state data have been explained. The concept of constraining the distribution of statistical leverage relative to the distribution of the starting solution to prevent extrapolation during the optimization process has been proposed and demonstrated. Separate from the issue of extrapolation is preventing the search from being quasi-static. Second-order linear dynamic constraint models have been proposed to prevent the search from returning solutions that are feasible if each point were run at steady state, but which are unrealistic in a transient sense. Dynamic constraint models translate commanded parameters to actually achieved parameters that then feed into the transient emission and torque models. Combined model inaccuracies have been used to adjust the optimized solutions. To frame the optimization problem within reasonable dimensionality, the coefficients of commanded surfaces that approximate engine tables are adjusted during search iterations, each of which involves simulating the entire transient cycle. The resulting strategy, different from the corresponding manual calibration strategy and resulting in lower emissions and efficiency, is intended to improve rather than replace the manual calibration process.
Resumo:
Smoke spikes occurring during transient engine operation have detrimental health effects and increase fuel consumption by requiring more frequent regeneration of the diesel particulate filter. This paper proposes a decision tree approach to real-time detection of smoke spikes for control and on-board diagnostics purposes. A contemporary, electronically controlled heavy-duty diesel engine was used to investigate the deficiencies of smoke control based on the fuel-to-oxygen-ratio limit. With the aid of transient and steady state data analysis and empirical as well as dimensional modeling, it was shown that the fuel-to-oxygen ratio was not estimated correctly during the turbocharger lag period. This inaccuracy was attributed to the large manifold pressure ratios and low exhaust gas recirculation flows recorded during the turbocharger lag period, which meant that engine control module correlations for the exhaust gas recirculation flow and the volumetric efficiency had to be extrapolated. The engine control module correlations were based on steady state data and it was shown that, unless the turbocharger efficiency is artificially reduced, the large manifold pressure ratios observed during the turbocharger lag period cannot be achieved at steady state. Additionally, the cylinder-to-cylinder variation during this period were shown to be sufficiently significant to make the average fuel-to-oxygen ratio a poor predictor of the transient smoke emissions. The steady state data also showed higher smoke emissions with higher exhaust gas recirculation fractions at constant fuel-to-oxygen-ratio levels. This suggests that, even if the fuel-to-oxygen ratios were to be estimated accurately for each cylinder, they would still be ineffective as smoke limiters. A decision tree trained on snap throttle data and pruned with engineering knowledge was able to use the inaccurate engine control module estimates of the fuel-to-oxygen ratio together with information on the engine control module estimate of the exhaust gas recirculation fraction, the engine speed, and the manifold pressure ratio to predict 94% of all spikes occurring over the Federal Test Procedure cycle. The advantages of this non-parametric approach over other commonly used parametric empirical methods such as regression were described. An application of accurate smoke spike detection in which the injection pressure is increased at points with a high opacity to reduce the cumulative particulate matter emissions substantially with a minimum increase in the cumulative nitrogrn oxide emissions was illustrated with dimensional and empirical modeling.
Resumo:
The capability to detect combustion in a diesel engine has the potential of being an important control feature to meet increasingly stringent emission regulations, develop alternative combustion strategies, and use of biofuels. In this dissertation, block mounted accelerometers were investigated as potential feedback sensors for detecting combustion characteristics in a high-speed, high pressure common rail (HPCR), 1.9L diesel engine. Accelerometers were positioned in multiple placements and orientations on the engine, and engine testing was conducted under motored, single and pilot-main injection conditions. Engine tests were conducted at varying injection timings, engine loads, and engine speeds to observe the resulting time and frequency domain changes of the cylinder pressure and accelerometer signals. The frequency content of the cylinder pressure based signals and the accelerometer signals between 0.5 kHz and 6 kHz indicated a strong correlation with coherence values of nearly 1. The accelerometers were used to produce estimated combustion signals using the Frequency Response Functions (FRF) measured from the frequency domain characteristics of the cylinder pressure signals and the response of the accelerometers attached to the engine block. When compared to the actual combustion signals, the estimated combustion signals produced from the accelerometer response had Root Mean Square Errors (RMSE) between 7% and 25% of the actual signals peak value. Weighting the FRF’s from multiple test conditions along their frequency axis with the coherent output power reduced the median RMSE of the estimated combustion signals and the 95th percentile of RMSE produced from each test condition. The RMSE’s of the magnitude based combustion metrics including peak cylinder pressure, MPG, peak ROHR, and work estimated from the combustion signals produced by the accelerometer responses were between 15% and 50% of their actual value. The MPG measured from the estimated pressure gradient shared a direct relationship to the actual MPG. The location based combustion metrics such as the location of peak values and burn durations were capable of RMSE measurements as low as 0.9°. Overall, accelerometer based combustion sensing system was capable of detecting combustion and providing feedback regarding the in cylinder combustion process