Modélisation et contrôle du moteur à allumage commandé pour Euro 6

Cette thèse a été développé grâce à une Conventions Industrielles de Formation par la Recherche (CIFRE). Cette convention fait partie d un programme de l Association nationale de la recherche et de la technologie (ANRT), coordonné par le Centre nationale de la recherche scientifique (CNRS). L accord CIFRE subventionne les entreprises françaises qui engagent un thésard pour conduire un projet scientifique dans l entreprise, en partenariat avec un laboratoire publique de recherche. Pour cette thèse, l accord CIFRE a été signé par Renault et les laboratoires GIPSA Lab de Grenoble et PRISME d Orléans.Cette thèse se focalise sur la modélisation 0D, en particulier sur une description plus détaillé du processus de la combustion et l estimation des masses enfermées dans la chambre de combustion d un moteur à allumage commandé (Spark Ignited (SI) engine). Les principaux développements comportent des points suivants :- L impact flamme parois pendant la combustion : un nouveau modèle pour prendre en compte ce phénomène dans le cadre d un modèle de combustion 0D à deux zones a été développé. Ce modèle permet de prendre en compte la géométrie de la chambre de combustion et la proportion de flamme que brûle proche des parois du cylindre. Plusieurs études ont montré qu une grand proportion (20% au 30%) du mélange frais brûle dans ce mode de combustion ce qui montre l importance de prendre en compte ce phénomène. - L estimation de la mass totale enfermée dans la chambre de combustion après la fermeture des soupapes est un phénomène très intéressant qui présente un Challenger pour les chercheurs motoristes. Une estimation plus précise de la mass enfermée dans la chambre de combustion permet d avoir un meilleur contrôle de l injection du carburant et une amélioration dans le traitement des polluants.- Le dernier point à traiter dans cette thèse est la commande d un système d injection common rail . Ce point a pour but de compléter la modélisation de la combustion en ajoutant une thématique liée à l injection, lequel est un paramètre crucial dans le processus de la combustion. L objectif d un système d injection common rail est de contrôler l avance de l injection, la durée et la pression, de façon indépendante dans chaque cylindre, pour avoir un meilleur contrôle de la combustion, en dépendant des conditions d opération. Cette injection permet de réguler le carburant en quantités très petites, ce qu aide à réduire la consommation, les émissions polluantes, et aussi à améliorer la performance du moteur.This thesis has been developed thanks to a Conventions Industrielles de Formation par la Recherche (CIFRE)1 agreement, that is a program of the french agency Association nationale de la recherche et de la Technologie(ANRT), coordinated by the Centre nationale de la recherche scientifique (CNRS). The CIFRE program grants the Franch companies who engage a PhD student to carry out a research project of the company within a public research lab. For this thesis, a CIFRE agreement has been accorded between the automobile company Renault France and the scientific laboratories Gipsa Lab in Grenoble and PRISME in Orléans.This thesis is focused on the modeling of a detailed description of the 0D combustion process and the estimation of the enclosed mass in the combustion chamber for a Spark Ignited (SI) engine. The main developments are summarized as follows:- The combustion process is frequently modeled as growing flame inside of the combustion chamber. Many 0D thermodynamical Engine models mostly focus on the laminar characteristics of such a free developing ame, but they lack of a suitable approximation of the combustion when the ame reaches the cylinder walls. In this thesis, a flame-wall interaction model is proposed as a complement of a 0D two zones thermodynamical model.- The estimation of the total mass enclosed in the combustion chamber is an interesting and challenging task for the engine control community. In this thesis, two nonlinear observers are synthesized for the enclosed mass estimation: a classical nonlinear high gain observer and an extended linear parameter varying (LPV) high gain observer.- A controller for a common rail injection system is developed in this thesis. First, an input state linearization of a common rail model is performed, in order to overcome the strong nonlinearities and build a virtual linear model. Using the virtual model, two linear control strategies are implemented to regulate the common rail pressure: an optimal linear quadratic regulator LQR with integral action and an optimal LQR tracking (feedforward) with integral action strategy.SAVOIE-SCD - Bib.électronique (730659901) / SudocGRENOBLE1/INP-Bib.électronique (384210012) / SudocGRENOBLE2/3-Bib.électronique (384219901) / SudocSudocFranceF

Development of a Small Scale Rotating Detonation Engine

The Rotating Detonation Engine (RDE) has been researched extensively in recent years, but the minimum size limits of an RDE have not been well investigated. The goal of this research was to build an RDE small enough to produce a detonation frequency above 20 kHz with a single detonation wave while also reducing the engine\u27s mass ow rate. An engine with these design characteristics would reduce hazards associated with previous RDE testing. This research objective resulted in the design of an RDE with an outer diameter sized at 28 mm using ethylene and nitrous oxide as a fuel and oxidizer. The engine was tested over a range of equivalence ratios between 0.5-1.5 and at mass ow rates of 0.025-0.075 kg/s to characterize its operation. Key design parameters were the injection hole diameter, detonation channel gap, detonation channel length, and detonation channel diameter. Detonation was achieved in an RDE of this scale, which proved operability of an engine with these design characteristics was possible

Low-Pressure EGR in Spark-Ignition Engines: Combustion Effects, System Optimization, Transients & Estimation Algorithms

Low-displacement turbocharged spark-ignition engines have become the dominant choice of auto makers in the effort to meet the increasingly stringent emission regulations and fuel efficiency targets. Low-Pressure cooled Exhaust Gas Recirculation introduces important efficiency benefits and complements the shortcomings of highly boosted engines. The main drawback of these configurations is the long air-path which may cause over-dilution limitations during transient operation. The pulsating exhaust environment and the low available pressure differential to drive the recirculation impose additional challenges with respect to feed-forward EGR estimation accuracy. For these reasons, these systems are currently implemented through calibration with less-than-optimum EGR dilution in order to ensure stable operation under all conditions. However, this technique introduces efficiency penalties. Aiming to exploit the full potential of this technology, the goal is to address these challenges and allow operation with near-optimum EGR dilution. This study is focused on three major areas regarding the implementation of Low-Pressure EGR systems: Combustion effects, benefits and constraints System optimization and transient operation Estimation and adaptation Results from system optimization show that fuel efficiency benefits range from 2% – 3% over drive cycles through pumping and heat loss reduction, and up to 16% or more at higher loads through knock mitigation and fuel enrichment elimination. Soot emissions are also significantly reduced with cooled EGR. Regarding the transient challenges, a methodology that correlates experimental data with simulation results is developed to identify over-dilution limitations related to the engine’s dilution tolerance. Different strategies are proposed to mitigate these issues, including a Neural Network-actuated VVT that controls the internal residual and increases the over-dilution tolerance by 3% of absolute EGR. Physics-based estimation algorithms are also developed, including an exhaust pressure/temperature model which is validated through real-time transient experiments and eliminates the need for exhaust sensors. Furthermore, the installation of an intake oxygen sensor is investigated and an adaptation algorithm based on an Extended Kalman Filter is created. This algorithm delivers short-term and long-term corrections to feed-forward EGR models achieving a final estimation error of less than 1%. The combination of the proposed methodologies, strategies and algorithms allows the implementation of near-optimum EGR dilution and translates to fuel efficiency benefits ranging from 1% at low-load up to 10% at high-load operation over the current state-of-the-art

Nichtlineare Merkmalsselektion mit der generalisierten Transinformation

In the context of information theory, the term Mutual Information has first been formulated by Claude Elwood Shannon. Information theory is the consistent mathematical description of technical communication systems. To this day, it is the basis of numerous applications in modern communications engineering and yet became indispensable in this field. This work is concerned with the development of a concept for nonlinear feature selection from scalar, multivariate data on the basis of the mutual information. From the viewpoint of modelling, the successful construction of a realistic model depends highly on the quality of the employed data. In the ideal case, high quality data simply consists of the relevant features for deriving the model. In this context, it is important to possess a suitable method for measuring the degree of the, mostly nonlinear, dependencies between input- and output variables. By means of such a measure, the relevant features could be specifically selected. During the course of this work, it will become evident that the mutual information is a valuable and feasible measure for this task and hence the method of choice for practical applications. Basically and without the claim of being exhaustive, there are two possible constellations that recommend the application of feature selection. On the one hand, feature selection plays an important role, if the computability of a derived system model cannot be guaranteed, due to a multitude of available features. On the other hand, the existence of very few data points with a significant number of features also recommends the employment of feature selection. The latter constellation is closely related to the so called "Curse of Dimensionality". The actual statement behind this is the necessity to reduce the dimensionality to obtain an adequate coverage of the data space. In other word, it is important to reduce the dimensionality of the data, since the coverage of the data space exponentially decreases, for a constant number of data points, with the dimensionality of the available data. In the context of mapping between input- and output space, this goal is ideally reached by selecting only the relevant features from the available data set. The basic idea for this work has its origin in the rather practical field of automotive engineering. It was motivated by the goals of a complex research project in which the nonlinear, dynamic dependencies among a multitude of sensor signals should be identified. The final goal of such activities was to derive so called virtual sensors from identified dependencies among the installed automotive sensors. This enables the real-time computability of the required variable without the expenses of additional hardware. The prospect of doing without additional computing hardware is a strong motive force in particular in automotive engineering. In this context, the major problem was to find a feasible method to capture the linear- as well as the nonlinear dependencies. As mentioned before, the goal of this work is the development of a flexibly applicable system for nonlinear feature selection. The important point here is to guarantee the practicable computability of the developed method even for high dimensional data spaces, which are rather realistic in technical environments. The employed measure for the feature selection process is based on the sophisticated concept of mutual information. The property of the mutual information, regarding its high sensitivity and specificity to linear- and nonlinear statistical dependencies, makes it the method of choice for the development of a highly flexible, nonlinear feature selection framework. In addition to the mere selection of relevant features, the developed framework is also applicable for the nonlinear analysis of the temporal influences of the selected features. Hence, a subsequent dynamic modelling can be performed more efficiently, since the proposed feature selection algorithm additionally provides information about the temporal dependencies between input- and output variables. In contrast to feature extraction techniques, the developed feature selection algorithm in this work has another considerable advantage. In the case of cost intensive measurements, the variables with the highest information content can be selected in a prior feasibility study. Hence, the developed method can also be employed to avoid redundance in the acquired data and thus prevent for additional costs.Der Begriff der Transinformation wurde erstmals von Claude Elwood Shannon im Kontext der Informationstheorie, einer einheitlichen mathematischen Beschreibung technischer Kommunikationssysteme, geprägt. Die vorliegenden Arbeit befaßt sich vor diesem Hintergrund mit der Entwicklung einer in der Praxis anwendbaren Methodik zur nichtlinearen Merkmalselektion quantitativer, multivariater Daten auf der Basis des bereits erwähnten informationstheoretischen Ansatzes der Transinformation. Der Erfolg beim Übergang von realen Meßdaten zu einer geeigneten Modellbeschreibung wird maßgeblich von der Qualität der verwendeten Datenmengen bestimmt. Eine qualitativ hochwertige Datenmenge besteht im Idealfall ausschließlich aus den für eine erfolgreiche Modellformulierung relevanten Daten. In diesem Kontext stellt sich daher sofort die Frage nach der Existenz eines geeigneten Maßes, um den Grad des, im Allgemeinen nichtlinearen, funktionalen Zusammenhangs zwischen Ein- und Ausgaben quantitativ korrekt erfassen zu können. Mit Hilfe einer solchen Größe können die relevanten Merkmale gezielt ausgewählt und somit von den redundanten Merkmalen getrennt werden. Im Verlaufe dieser Arbeit wird deutlich werden, daß die eingangs erwähnte Transinformation ein hierfür geeignetes Maß darstellt und im praktischen Einsatz bestens bestehen kann. Die ursprüngliche Motivation zur Erstellung der vorliegenden Arbeit hat ihren durchaus praktischen Hintergrund in der Automobiltechnik. Sie entstand im Rahmen eines komplexen Forschungsprojektes zur Ermittlung von nichtlinearen, dynamischen Zusammenhängen zwischen einer Vielzahl von meßtechnisch ermittelten Sensorsignalen. Das Ziel dieser Aktivitäten war, durch die Identifikation von nichtlinearen, dynamischen Zusammenhängen zwischen den im Automobil verbauten Sensoren, sog. virtuelle Sensoren abzuleiten. Die konkrete Aufgabenstellung bestand nun darin, die Bestimmung einer zentralen Motorgröße so effizient zu gestalten, daß diese ohne zusätzliche Hardware unter harten Echtzeitvorgaben berechenbar ist. Auf den zusätzlichen Einsatz von Hardware verzichten zu können und mit der bereits vorhandenen Rechenleistung auszukommen, stellt aufgrund des resultierenden, enormen Kostenaufwandes insbesondere in der Automobiltechnik eine unglaublich starke Motivation dar. In diesem Zusammenhang trat immer wieder die große Problematik zutage, eine praktisch berechenbare Methode zu finden, die sowohl lineare- als auch nichtlineare Zusammenhänge zuverlässig quantitativ erfassen kann. Im Verlauf der Arbeit werden nun unterschiedliche Selektionsstrategien mit der Transinformation kombiniert und deren Eigenschaften miteinander verglichen. In diesem Zusammenhang erweist sich die Kombination von Transinformation mit der sogenannten Forward Selection Strategie als besonders interessant. Es wird gezeigt, daß diese Kombination die praktische Berechenbarkeit für hochdimensionale Datenräume, im Vergleich zu anderen Vorgehensweisen, tatsächlich erst ermöglicht. Im Anschluß daran wird die Konvergenz dieses neuen Verfahrens zur Merkmalselektion bewiesen. Wir werden weiterhin sehen, daß die erzielten Ergebnisse bemerkenswert nahe an der optimalen Lösung liegen und im Vergleich mit einer alternativen Selektionsstrategie deutlich überlegen sind. Parallel zur eigentlichen Selektion der relevanten Merkmale ist es mit der in dieser Arbeit entwickelten Methode nun auch problemlos möglich, eine nichtlineare Analyse der zeitlichen Abhängigkeiten von ausgewählten Merkmalen durchzuführen. Eine anschließende dynamische Modellierung kann somit wesentlich effizienter durchgeführt werden, da die entwickelte Merkmalselektion zusätzliche Information hinsichtlich des dynamischen Zusammenhangs von Eingangs- und Ausgangsdaten liefert. Mit der in dieser Arbeit entwickelten Methode ist nun letztendlich gelungen was vorher nicht möglich war. Das quantitative Erfassen der nichtlinearen Zusammenhänge zwischen dedizierten Sensorsignalen, um diese in eine effiziente Merkmalselektion einfließen zu lassen. Im Gegensatz zur Merkmalsextraktion, hat die in diese Arbeit entwickelte Methode der nichtlinearen Merkmalselektion einen weiteren entscheidenden Vorteil. Insbesondere bei sehr kostenintensiven Messungen können diejenigen Variablen ausgewählt werden, die hinsichtlich der Abbildung auf eine Ausgangsgröße den höchsten Informationsgehalt tragen. Neben dem rein technischen Aspekt, die Selektionsentscheidung direkt auf den Informationsgehalt der verfügbaren Daten zu stützen, kann die entwickelte Methode ebenfalls im Vorfeld kostenrelevanter Entscheidungen herangezogen werden, um Redundanz und die damit verbundenen höheren Kosten gezielt zu vermeiden

Internal Combustion Engines

This book on internal combustion engines brings out few chapters on the research activities through the wide range of current engine issues. The first section groups combustion-related papers including all research areas from fuel delivery to exhaust emission phenomena. The second one deals with various problems on engine design, modeling, manufacturing, control and testing. Such structure should improve legibility of the book and helps to integrate all singular chapters as a logical whole

Development of combustion models for RANS and LES applications in SI engines

Prediction of flow and combustion in IC engines remains a challenging task. Traditional Reynolds Averaged Navier Stokes (RANS) methods and emerging Large Eddy Simulation (LES) techniques are being used as reliable mathematical tools for such predictions. However, RANS models have to be further refined to make them more predictive by eliminating or reducing the requirement for application based fine tuning. LES holds a great potential for more accurate predictions in engine related unsteady combustion and associated cycle-tocycle variations. Accordingly, in the present work, new advanced CFD based flow models were developed and validated for RANS and LES modelling of turbulent premixed combustion in SI engines. In the research undertaken for RANS modelling, theoretical and experimental based modifications have been investigated, such that the Bray-Moss-Libby (BML) model can be applied to wall-bounded combustion modelling, eliminating its inherent wall flame acceleration problem. Estimation of integral length scale of turbulence has been made dynamic providing allowances for spatial inhomogeneity of turbulence. A new dynamic formulation has been proposed to evaluate the mean flame wrinkling scale based on the Kolmogorov Pertovsky Piskunow (KPP) analysis and fractal geometry. In addition, a novel empirical correlation to quantify the quenching rates in the influenced zone of the quenching region near solid boundaries has been derived based on experimentally estimated flame image data. Moreover, to model the spark ignition and early stage of flame kernel formation, an improved version of the Discrete Particle Ignition Kernel (DPIK) model was developed, accounting for local bulk flow convection effects. These models were first verified against published benchmark test cases. Subsequently, full cycle combustion in a Ricardo E6 engine for different operating conditions was simulated. An experimental programme was conducted to obtain engine data and operating conditions of the Ricardo E6 engine and the formulated model was validated using the obtained experimental data. Results show that, the present improvements have been successful in eliminating the wall flame acceleration problem, while accurately predicting the in-cylinder pressure rise and flame propagation characteristics throughout the combustion period. In the LES work carried out in this research, the KIVA-4 RANS code was modified to incorporate the LES capability. Various turbulence models were implemented and validated in engine applications. The flame surface density approach was implemented to model the combustion process. A new ignition and flame kernel formation model was also developed to simulate the early stage of flame propagation in the context of LES. A dynamic procedure was formulated, where all model coefficients were locally evaluated using the resolved and test filtered flow properties during the fully turbulent phase of combustion. A test filtering technique was adopted to use in wall bounded systems. The developed methodology was then applied to simulate the combustion and associated unsteady effects in Ricardo E6 spark ignition engine at different operating conditions. Results show that, present LES model has been able to resolve the evolution of a large number of in-cylinder flow structures, which are more influential for engine performance. Predicted heat release rates, flame propagation characteristics, in-cylinder pressure rise and their cyclic variations are also in good agreement with measurements

Analysis and control of a spark ignition free-piston engine generator

PhD ThesisIn this research, the performance analysis and control strategy of a spark-ignited free-piston engine generator were presented. A literature review of the free-piston engine fundamental information and the recent research development on the free-piston engine generator (FPEG) was provided, mainly focussing on previous work on numerical modelling, prototype design as well as the control strategy. The design and simulation of a dual-piston spark-ignited FPEG suitable for operation using either a two-stroke or four-stroke thermodynamic cycle were presented. Model validation and the general engine performance of the system were discussed. For the first time, this research demonstrated the potential advantages and disadvantages of the FPEG on using different thermodynamic gas-exchange cycles. A fast response real time model of the FPEG was designed and validated. The simplicity and flexibility of the proposed model make it feasible to be implemented and coupled with real-time hardware in the loop control system development. In addition, since it revealed how an FPEG operates according to a resonant principle, the model is useful for parameter selection in the design process. For the first time, cascade control was proposed and investigated for the piston stable operation control, using both the measured piston top dead centre of the previous stroke and the measured piston velocity at the current stroke as feedbacks, with the injected fuel mass as the control variable. The system performance was improved by implementing the cascade control compared with single loop control in terms of the controller response time, peak error and settling time

Spark Breakdown Voltage Sampling During Early Stage Compression

This thesis proposes a novel methodology to enable cycle by cycle control of a two-stroke cycle type engine. These engines are well known for offering high specific power density solutions, however, this advantage cannot be fully exploited without new technologies enabling significantly reduced emissions and improved fuel economy. If this could be provided, working with direct fuel injection, new highly efficient, low emission, power units could result. One of the main reasons why this has not previously been achieved has been the inability to accurately measure and quantify the amount of combustible charge available for metering of the Air/Fuel ratio. This is due to the highly dynamic gas conditions in the engine which cause significant cyclic variations of scavenging and trapping efficiencies. Existing combustion control methods are unable to accurately compensate for these conditions because fuel quantity is determined using the results of previous combustion events which do not reflect the actual gases available for each combustion. This thesis proposes a different approach, whereby accurate fuel quantities could be determined cyclically from in-cylinder measurements ahead of each combustion event. The intention being, for optimal fuel quantities and ignition initiation timings to be calculated and provided for each cycle. This technology would significantly improve the ability to achieve an optimal combustion of each individual combustion event. The principle of measurement uses and extends proven existing extensive scientific knowledge of the relationships between the value of Spark Break-Down Voltage (SBDV) to gas density and speciation. The methodology presented, applied pulses of voltage to the spark plug, which is normally used only to initiate ignition, to also function as a non-intrusive in-cylinder sensor. Experimental results were obtained using three items of equipment purposely designed and manufactured for the present work. These consisted of a) A new high frequency spark breakdown voltage electronic circuit. b) A static volume sparking chamber. c). A motored test engine into which exhaust gas was supplied from an auxiliary engine via an air mixing system. The novel use of an auxiliary engine enabled a wide range of mass fractions to be subjected to cyclic compression events for evaluation independent of test engine conditions

THIESEL 2020.Thermo-and Fluid Dynamic Processes in Direct Injection Engines.8th-11th September

'The THIESEL 2020 Conference on Thermo-and Fluid Dynamic Processes in Direct Injection Engines planned in Valencia (Spain) for 8th to 11th September 2020 has been successfully held in a virtual format, due to the COVID19 pandemic. In spite of the very tough environmental demands, combustion engines will probably remain the main propulsion system in transport for the next 20 to 50 years, at least for as long as alternative solutions cannot provide the flexibility expected by customers of the 21st century. But it needs to adapt to the new times, and so research in combustion engines is nowadays mostly focused on the new challenges posed by hybridization and downsizing. The topics presented in the papers of the conference include traditional ones, such as Injection & Sprays, Combustion, but also Alternative Fuels, as well as papers dedicated specifically to CO2 Reduction and Emissions Abatement.Papers stem from the Academic Research sector as well as from the IndustryXandra Marcelle, M.; Desantes Fernández, JM. (2020). THIESEL 2020.Thermo-and Fluid Dynamic Processes in Direct Injection Engines.8th-11th September. Editorial Universitat Politècnica de València. http://hdl.handle.net/10251/150759EDITORIA