Design and development of auxiliary components for a new two-stroke, stratified-charge, lean-burn gasoline engine

A unique stepped-piston engine was developed by a group of research engineers at Universiti Teknologi Malaysia (UTM), from 2003 to 2005. The development work undertaken by them engulfs design, prototyping and evaluation over a predetermined period of time which was iterative and challenging in nature. The main objective of the program is to demonstrate local R&D capabilities on small engine work that is able to produce mobile powerhouse of comparable output, having low-fuel consumption and acceptable emission than its crankcase counterpart of similar displacement. A two-stroke engine work was selected as it posses a number of technological challenges, increase in its thermal efficiency, which upon successful undertakings will be useful in assisting the group in future powertrain undertakings in UTM. In its carbureted version, the single-cylinder aircooled engine incorporates a three-port transfer system and a dedicated crankcase breather. These features will enable the prototype to have high induction efficiency and to behave very much a two-stroke engine but equipped with a four-stroke crankcase lubrication system. After a series of analytical work the engine was subjected to a series of laboratory trials. It was also tested on a small watercraft platform with promising indication of its flexibility of use as a prime mover in mobile platform. In an effort to further enhance its technology features, the researchers have also embarked on the development of an add-on auxiliary system. The system comprises of an engine control unit (ECU), a directinjector unit, a dedicated lubricant dispenser unit and an embedded common rail fuel unit. This support system was incorporated onto the engine to demonstrate the finer points of environmental-friendly and fuel economy features. The outcome of this complete package is described in the report, covering the methodology and the final characteristics of the mobile power plant

Modelling of Crankcase Gas Behaviour in a Heavy-Duty Diesel Engine

The origin of many environmental and health hazardous emissions from diesel engines are the crankcase gases. Since no regulations of the emission levels from the crankcase have existed in the past, no attention has been paid to cleaning crankcase gases. New regulations are coming up and they will all demand lower emissions from the engine. This has lead to the introduction of the Alfdex separator. The Alfdex separator is built to separate oil droplets and soot from the crankcase gases. In the research work made in this master thesis, we have investigated the possibilities to model the crankcase gases with respect to flow rate and oil content with some parameters of the engine. The model could then be used as an input to a controller that controls the separator speed. Since the test engine used here is old and is not in production anymore, the idea of the modelling is to find more general characteristics rather than specifics for the tested engine. The work made in this master thesis shows that the crankcase gas flow rate can be modelled in a good way. The identifying process done here is accomplished by field tests on a Volvo bus equipped with a TD123E motor, which is a 6 cylinder, 12 litres, turbocharged diesel engine. Since no prior testing had been made, the project involved much practical work such as test rig building, mounting on the bus etc. The measurements on crankcase gases have been made both at stationary modes and dynamically. The project also involves measurements of the oil content in crankcase gases. These measurements have been made at steady state, with no possibility to investigate the dynamic behaviour of the oil aerosol. The tests made on the size distribution of oil in the crankcase gases gives a hint to the future development of a controller

Development of hybrid algorithms for vehicular emissions modelling and prediction

University of Technology Sydney. Faculty of Engineering and Information Technology.The overwhelming accumulation of traffic volumes and relentless changes in travel-related characteristics significantly increase vehicular emissions, and hence, seriously affect urban air quality. It is difficult, however, to accurately estimate vehicular emissions in traffic intersections, junctions, and at signalized roadways because rate models for predicting vehicular emissions are insensitive to the vehicle modes of operations, such as cruising, idling, acceleration and deceleration. The reason is that these models are usually based on the average trip speed, not vehicle dynamics. These contribute to the increased complexity of such a model and degradation of its predictive performance. This thesis advocates the feasibility of using variables such as vehicle speed, acceleration, load, power and ambient temperature to predict transport emissions to ensure that emission inventories are accurate for the sake of air quality modelling and management planning. A variety of algorithms has been developed, based on Multivariate Adaptive Regression Splines (MARS), Boosting Multivariate Adaptive Regression Splines (BMARS), Artificial Neural Networks (ANNs), as well as the non-parametric Classification and Regression Trees (CART) and a combination of them in hybrid models to improve the accuracy of the emission prediction using vehicles’ on-board measurements and chassis dynamometer testing. Several performance indices are used to evaluate: accuracy, flexibility and computational efficiency. The obtained results suggest that the CART-BMARS hybrid methodology appears to be a useful and fairly accurate tool for predicting microscale vehicle emissions and may be adopted by regulatory agencies. The significance of this thesis is in providing of feasible and effective solutions for the implementation of vehicular emissions models to address the problem of air quality modelling and control in metropoles and mega-cities

Engine modelling for virtual mapping. Development of a physics based cycle-by-cycle virtual engine that can be used for cyclic engine mapping applications, engine flow modelling, ECU calibration, real-time engine control or vehicle simulation studies.

After undergoing a study about current engine modelling and mapping approaches as well as the engine modelling requirements for different applications, a major problem found to be present is the extensive and time consuming mapping procedure that every engine has to go through so that all control parameters can be derived from experimental data. To improve this, a cycle-by-cycle modelling approach has been chosen to mathematically represent reciprocating engines starting by a complete dynamics crankshaft mechanism model which forms the base of the complete engine model. This system is modelled taking into account the possibility of a piston pin offset on the mechanism. The derived Valvetrain model is capable of representing a variable valve lift and phasing Valvetrain which can be used while modelling most modern engines. A butterfly type throttle area model is derived as well as its rate of change which is believed to be a key variable for transient engine control. In addition, an approximation throttle model is formulated aiming at real-time applications. Furthermore, the engine inertia is presented as a mathematical model able to be used for any engine. A spark ignition engine simulation (SIES) framework was developed in MATLAB SIMULINK to form the base of a complete high fidelity cycle-by-cycle simulation model with its major target to provide an environment for virtual engine mapping procedures. Some experimental measurements from an actual engine are still required to parameterise the model, which is the reason an engine mapping (EngMap) framework has been developed in LabVIEW, It is shown that all the moving engine components can be represented by a single cyclic variable which can be used for flow model development

Non-destructive characterization of thermally sprayed cylinder coatings using laser-excited lock-in thermography

Zur Effizienzsteigerung von Verbrennungsmotoren und der daraus resultierenden Reduktion des CO$_2$-Ausstoßes moderner Antriebsstränge ersetzten thermisch gespritzte Zylinderlaufflächen gegossene Zylinderbuchsen in den vergangenen Jahrzehnten. Um eine langlebige Funktionalität und Haltbarkeit moderner Verbrennungsmotoren zu gewährleisten, wird die Haftung solcher thermisch gespritzter Zylinderlaufflächen an das Kurbelgehäuse laufend innerhalb der Großserienproduktion überwacht. Da die Haftung zwischen der Lauffläche und dem Kurbelgehäuse gegenwärtig nur mittels zerstörendem "Pull-off adhesion testing" (PAT$^{\scriptscriptstyle \textrm{TM}}$) gemessen werden kann, wird eine schnelle und zuverlässige zerstörungsfreie Prüfmethode benötigt, die das Bindungsverhalten der Zylinderlaufflächen bestimmen kann. Das Auftreten von Bindungsfehlern innerhalb der Mikrostruktur verringert die Haftung der Zylinderlaufflächen. Deshalb zeigen zerstörungsfreie Temperaturleitfähigkeitsmessungen, die sensitive auf diese Defektmorphologie reagieren, vielversprechende Korrelationen zwischen den thermischen und mechanischen Eigenschaften der Laufflächen. Die Anwendung solcher Temperaturleitfähigkeitsmessungen als zerstörungsfreies Prüfverfahren zur Bewertung der Haftfestigkeit thermisch gespritzter Zylinderlaufflächen ist Gegenstand dieser Arbeit. Hierzu wird die laserangeregte Lock-In Thermographie verwendet, um Interferenzmessungen thermischer Wellen innerhalb lichtbogendrahtgespritzter Zylinderlaufflächen von PKW-Motoren zu untersuchen. Die daraus gemessenen Temperaturleitfähigkeitswerte der untersuchten Schichten zeigen signifikante Veränderungen innerhalb der Kurbelgehäuse, insbesondere entlang der Laufflächen. Darüber hinaus werden zerstörende Haftzugsmessungen und Mikrostrukturanalysen der untersuchten Zylinderlaufflächen durchgeführt, um die mechanischen und mikrostrukturellen Eigenschaften zu beurteilen. Zusätzliche Bruchstellenanalysen nach den PAT$^{\scriptscriptstyle \textrm{TM}}$-Messungen ermöglichen die quantitative Beurteilung des adhäsiven und kohäsiven Versagens der Schicht. Die Untersuchungen der Zusammenhänge zwischen der Temperaturleitfähigkeit, des Haftzuges und der Mikrostruktur ergeben bedeutende Korrelationen zwischen diesen beobachteten Größen

Combustion process in a Two-Stroke, H2-DI Linear Generator Free-Piston Engine during starting

A two-stroke free piston engine (FPE) for the application of a linear generator (LG) has been developed. It is a direct injection, spark ignition engine fuelled by hydrogen. In the past, the starting strategy of the FPE was based on the crank slider engine. However, the requirement of a different strategy is inevitable since the LG-FPE has no flywheel and has variable compression ratio during motoring. In addition, without a flywheel the engine has no energy storage to maintain its inertia in case of a misfire during starting. The fuelling amount, fuel injection and ignition timing during starting of LG-FPE is different from a conventional crank-slider engine. Starting of the former is done by accelerating a total moving mass of Skg alternately via electrical commutation of the linear motor towards both ends of the cylinders' stroke until sustainable combustions are achieved. The main objective of this research is to empirically investigate and determine the optimum injection and ignition timing during motoring with combustion when starting the LG FPE. Intake airflow measurements were obtained using laminar flow element setup. This is to determine the initial setting for hydrogen fuelling at stoichiometric air-fuel ratio. The investigation was carried out by varying the start of fuel injection (SOF) at constant start of ignition (SOl) and fuel per cycle (FPC) during motoring with combustion experiments of LG-FPE. Next, the SOF and FPC are kept constant while varying the SOL Finally, the FPC was varied at constant SOF and SOl values. Combustion process analyses were done by focusing on the rate of heat release, mass fraction burned, and ignition lag and combustion duration. From these analyses the optimum settings for SOF were found to be at linear position of+25.0 mm for cylinder 1 and -25.0 mm for cylinder 2. Early SOF setting resulted in lower peak pressure and slower rate of heat release while the ignition lag and combustion duration is longer. Whereas, the optimum settings for the SOl were found to be at position +29.5 mm for cylinder I and -30.0 mm for cylinder 2. The SOl must be before the peak pressure of compression (i.e. before the piston reverses direction). The timing must provide sufficient time for the flame to develop so that the piston will be in opposing motion in time for the heat release rate and cylinder pressure to reach its maximum. By using hydrogen instead of CNG, the ignition lag is reduced by 66% while the combustion duration is 50% faster

Towards Adequate Policy Enhancement: An AI-Driven Decision Tree Model for Efficient Recognition and Classification of EPA Status via Multi-Emission Parameters

Accurate and timely evaluation and assessment of emission data and its impact on environmental status has been a key challenge due to the conventional manual approach utilized for independently computing most emission parameters. To resolve this long-standing issue, we proposed an Artificial Intelligence (AI)-driven Decision Tree model to adequately classify Environmental Protection Agency (EPA) status based on multiple Emission Parameters. The model's performance was systematically evaluated using multiple emission parameters obtained from a two-stroke motorcycle dataset collected in Nigeria across various metrics such as K-S Statistics, Confusion Matrix, Correlation Heat Map, Decision Tree, Validation Curve, and Threshold Plot. The K-S Statistics plot's experimental results showed a considerable correlation between HC, CO, and the target variable, with values ranging from 0.75-0.80. At the same time, CO2 and O2 do not correlate with the target variable with values between 0.00 and 0.09. The Confusion Matrix revealed that the proposed model has an overall accuracy of 99.9% with 481 true positive predictions and 75 true negative predictions, indicating the effectiveness of the proposed AI-driven model. In conclusion, our proposed AI-driven model can effectively classify EPA status based on multiple emission parameters with high accuracy, which may spur positive advancement in policy enhancement for proper environmental management

Analysis of crankshaft–crankcase interaction for the prediction of the dynamic structural response and noise radiation of IC engine structures

This thesis presents research work which is concerned with the development of analytical and numerical methods for the dynamic analysis of the crankshaft-crankcase assembly. The effects of interaction of crankshaft and crankcase on the dynamic response of an IC engine block structure are studied. These methods are especially attractive for the simulation of the steady state response of rotating systems with many degrees of freedom which are forced by multiple periodic excitations. A major novelty of the methods is the ability to model the system non-linearities successfully as frequency dependent properties. [Continues.