This thesis deals with modification of an existing four-cylinder diesel engine to a singlecylinder research engine. The work is divided into four main parts. The first part is theoretical, briefly describes research engines, their individual types and provides an overview of their functions. The second part of the work includes the modification of a four-cylinder diesel engine to a single-cylinder research engine, focusing mainly on balancing inertia forces. The third, most extensive chapter contains the structural analysis of the crankshaft. The last part contains the design of a torsional coupling, which ensures the connection of the engine with the dynamometer.

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no / The complexity of powertrain calibration has increased significantly with the development and introduction of new technologies to improve fuel economy and performance while meeting increasingly stringent emissions legislation with given time and cost constraints. This paper presents research to improve the model-based engine calibration optimization using an integrated sequential Design of Experiments (DoE) strategy for engine mapping experiments. This DoE strategy is based on a coherent framework for a model building - model validation sequence underpinned by Optimal Latin Hypercube (OLH) space filling DoEs. The paper describes the algorithm development and implementation for generating the OLH space filling DoEs based on a Permutation Genetic Algorithm (PermGA), subsequently modified to support optimal infill strategies for the model building - model validation sequence and to deal with constrained non-orthogonal variables space. The development, implementation and validation of the proposed strategy is discussed in conjunction with a case study of a GDI engine steady state mapping, focused on the development of an optimal calibration for CO₂ and particulate number (Pn) emissions. The proposed DoE framework applied to the GDI engine mapping task combines a screening space filling DoE with a flexible sequence of model building - model validation mapping DoEs, all based on optimal DoE test plan augmentation using space filling criteria. The case study results show that the sequential DoE strategy offers a flexible way of carrying out the engine mapping experiments, maximizing the information gained and ensuring that a satisfactory quality model is achieved.

After undergoing an extensive study about engine air mass flow measurement approaches as well as engine modelling for air mass flow prediction, a major problem found to exist is that engineers have still not found a suitable technique to accurately measure the air mass flow entering the cylinder of an internal combustion engine. The engine air mass flow is the most important parameter needed during engine development so the fuel control can be accurately calibrated and as a result increase performance and reduce emission output of an engine. The current methods used to determine the air mass flow lead to inaccuracies due to the large amount of mathematical assumptions and also sensor errors and as a result the mapping and calibration process of a new engine family takes approximately 2 years due to extensive modelling and testing required overcoming the above drawbacks. To improve this, the distributed lumped modelling technique (D-L) of the inlet manifold was chosen, where the intake system is separated into very small sections which are distributed continuously throughout the volume of the intake until entering the cylinder. This technique is validated against a CFD model of the engine’s intake system and real engine data as well as a 1D engine model.

Yes / The natural gas as an alternative fuel has economical and environmental benefits. Bi-fuel engines powered by gasoline and compressed natural gas (CNG) are an intermediate and alternative step to dedicated CNG engines. The conversion to bi-fuel CNG engine could be a short-term solution to air pollution problem in many developing countries. In this paper a mathematical model of a bi-fuel four-stroke spark ignition (SI) engine is presented for comparative studies and analysis. It is based on the two-zone combustion model, and it has the ability to simulate turbulent combustion. The model is capable of predicting the cylinder temperature and pressure, heat transfer, brake work , brake thermal and volumetric efficiency, brake torque, brake specific fuel consumption (BSFC), brake mean effective pressure (BMEP), concentration of CO2, brake specific CO (BSCO) and brake specific NOx (BSNOx). The effect of engine speed, equivalence ratio and performance parameters using gasoline and CNG fuels are analysed. The model has been validated by experimental data using the results obtained from a bi-fuel engine. The results show the capability of the model in terms of engine performance optimization and minimization of the emissions. The engine used in this study is a typical example of a modified bi-fuel engine conversion, which could benefit the researchers in the field.

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