The master’s thesis deals with modelling of various architectures of hybrid powertrains for three vehicle sizes in GT-SUITE and compares them in daily commuting operating mode. On top of making of the hybrid vehicle simulation models, control algorithms had to be created to manage the energy split between the internal combustion engine and the electric motor for each of the architectures. Routes to work and back were logged using the GPS and postprocessed to obtain the speed and the road grade profiles. Resulting data was used as an input in simulations of daily commuting. To compare all hybrid powertrain architectures, fuel economy and electricity consumption were evaluated for WLTP and daily commuting operating modes. Finally, the environmental impact of each topology was assessed based on an estimation of corresponding well-to-wheel emissions.

Determining the characteristics of piston engines with a propeller is a complex task. Accurate calculations are based on engine and propeller characteristics from the manufacturers, which are, however, quite demanding. It is also possible to use simplified models that can predict the achievable values of propeller efficiency and fuel consumption. They are based on a simple propeller efficiency and maximum power. However, these models are often very inaccurate, which is a significant disadvantage. Therefore, it is possible to use the universal characteristics of propeller propulsion units, which offers a more accurate calculation of power and fuel consumption using a relatively simple model. The diploma thesis deals with a summary description of all characteristics of reciprocating internal combustion engines and propellers. A mathematical model was created here, which works according to a certain algorithm based on the joint work of the engine and the propeller. This model can predict the required power and fuel consumption in different flight modes much more accurately. The results were applied to the performance of ultralight aircraft, especially to the range, which was significantly increased.

The work deals with the analysis of various possibilities of increasing the efficiency of a small internal combustion engine potentially usable for use in the field of autonomous devices of smaller dimensions. It contains an outline of the problems of modern smaller autonomous means and an analysis of available drives designed for them, especially an analysis of propulsion by internal combustion engines. In his next part of the work he provides information about the created mathematical model of the demonstration internal combustion engine in the GT-Power program and an analysis of places where and in what ways its efficiency can be increased. The design of two such components together with the evaluation of the achieved results offers the conclusion of this work.

This diploma thesis is concerned about installation of AR64304 engine into Alfa Romeo 75. The main goal of this thesis is a design of exhaust system for AR64304 engine installed in the engine bay of the vehicle. The design of the exhaust system was done with a respect to the noise and emission requirements, as well as with a respect to the performance of the engine. Lotus Engine Simulation software was used for the simulation of the engine with proposed exhaust system. Input data for the simulation were obtained from measurements of the cylinder head on a flow bench and precise measurement of camshaft profile. The essential contribution of this work is a set of construction parameters of the exhaust system. This thesis also contains technical specifications of AR64304 engine and the installation process.

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Heavy-duty trucks are important links in the logistic chains of transport. Critical components in trucks include fuel injectors in which inaccuracies can lead to severe financial damage and higher emissions. Intelligent and efficient ways to detect such scenarios are thus of high importance. This thesis applies machine learning algorithms to measured or estimated engine data, focused on gas exchange signals, to detect inaccuracies in fueling quantities. The fueling inaccuracies considered were of low deviations from the nominal curve, with magnitudes not covered by the currently used fueling diagnostics. The data used for the models was generated from Scania test cell engines where different setups of injectors were deliberately set to over- or underfuel.  Seven different machine learning models were used on the data and evaluated on how well they could detect deviations from nominal fueling. The tests were mainly done with a pure data-driven approach but also improved through different data selection techniques and using domain knowledge. An investigation to connect the findings within the thesis to real customer data was initiated in order to make the results useful for e.g. predictive maintenance. The complications connected to why this was not ultimately achieved were discussed.

Controlling the temperature of the exhaust valves is paramount for proper functioning of engines and for the long lifespan of valve train components. The majority of the heat outflow from the valve takes place along the valve-seat-cylinder head-coolant thermal path which is significantly influenced by the thermal contact resistance (TCR) present at the valve/seat and seat/head interfaces. A test rig facility and experimental procedure were successfully developed to assess the effect of the valve/seat and seat/head interfaces on heat outflow from the valve, in particular the effects of the valve/seat interface geometry, seat insert assembly method, i.e. press or shrink fit, and seat insert metallic coating on the operating temperature of the valve. The results of tests have shown that the degree of the valve-seat geometric conformity is more significant than the thermal conductivity of the insert: for low conforming assemblies, the mean valve head temperature recorded during tests on copper-infiltrated insert seats was higher than that recorded during tests on noninfiltrated seats of higher conformance. The effect of the insert-cylinder head assembly method, i.e. shrink-fitted versus press-fitted inserts, has proved negligible: results have shown insignificant valve head temperature variations, for both tin-coated and uncoated inserts. On the other hand, coating the seat inserts with a layer of tin (20-22¿m) reduced the mean valve head temperature by approximately 15°C as measured during tests on uncoated seats. The analysis of the valve/seat and seat/head interfaces has indicated that the surface asperities of the softer metal in contact would undergo plastic deformation. Suitable thermal contact conductance (TCC) models, available in the public domain, were used to evaluate the conductance for the valve/seat and seat/cylinder head interfaces. Finally, a FE thermal model of the test rig has been developed with a view to assess the quality of the calculated TCC values for the valve/seat and seat/head interfaces. The results of the thermal analysis have shown that predicted temperatures at chosen control points agree with those measured during tests on thermometric seats with an acceptable level of accuracy, proving the effectiveness of the used TCC models.

Uncertainty analysis is crucial to any thorough analysis of an engineering system. Traditional uncertainty analysis can be a tedious task involving numerous steps that can be error prone if conducted by hand. If conducted with the aid of a computer, these tasks can be computationally expensive. In either case, the process is quite rigid. If a parameter of the system is modified or the system configuration is changed, the entire uncertainty analysis process must be conducted again giving more opportunities for calculation errors or computation time. Modular uncertainty analysis provides a method to overcome all these obstacles of traditional uncertainty analysis. The modular technique is well suited for computation by a computer which makes the process somewhat automatic after the initial setup and computation errors are reduced. The modular technique implements matrix operations to conduct the analysis. This in turns makes the process more efficient than traditional methods because computers are well suited for matrix operations. Since the modular technique implements matrix operations, the method is adaptable to system parameter or configuration modifications. The modular technique also lends itself to quickly calculating other uncertainty analysis parameters such as the uncertainty magnification factor, and the uncertainty percent contribution. This dissertation will focuson the modular technique, the extension of the technique in the form the uncertainty magnification factor and uncertainty percent contribution, and the application of the modular technique to different type of energy systems. The modular technique is applied to an internal combustion engine with a bottoming organic Rankine cycle system, a combined heat and power system, and a heating, ventilation, and air conditioning system. The results show that the modular technique is well suited to evaluate complex engineering systems. The modular technique is also shown to perform well when system parameters or configurations are modified.

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