The ever increasing demands on today's engine performance and emissions control is forcing the automotive industry to make use of innovative solutions. One of these is to apply the technology of VNT turbos on commercial petrol vehicles. When using a VNT turbo, the aspect ratio of the turbine can be altered while driving to suit the current operating window. In order to actually gain performance while using a VNT, the vanes have to be properly controlled using a suitable control strategy. In this project, direct collocation have been utilized through the usage of YOP which is an adaptation of CasADi in MATLAB to solve non-linear optimization problems. Comprehensive models of the turbocharger and the cylinders have been built and validated to properly represent a VEP4 LP engine from AUROBAY. The models are implemented in YOP to create and simulate different OCPs using the turbo speed as state and position of the vanes as control signal. With this model in YOP together with the air mass flow per second as reference, a good reference following together with decent values for relevant parameters can be accomplished. Other objective functions such as minimum time and maximal volumetric efficiency are also investigated in the project which yield likewise results. From the results it can be concluded that this type of model and control strategy can be used with success when studying optimal control of a VNT turbo.

In this thesis, exergy based SI engine model optimisation (EBSIEMO) is studied and evaluated. A four-stroke bi-fuel spark ignition (SI) engine is modelled for optimisation of engine performance based upon exergy analysis. An artificial neural network (ANN) is used as an emulator to speed up the optimisation processes. Constrained particle swarm optimisation (CPSO) is employed to identify parameters such as equivalence ratio and ignition time for optimising of the engine performance, based upon maximising ¿total availability¿. In the optimisation process, the engine exhaust gases standard emission were applied including brake specific CO (BSCO) and brake specific NOx (BSNOx) as the constraints. The engine model is developed in a two-zone model, while considering the chemical synthesis of fuel, including 10 chemical species. A computer code is developed in MATLAB software to solve the equations for the prediction of temperature and pressure of the mixture in each stage (compression stroke, combustion process and expansion stroke). In addition, Intake and exhaust processes are calculated using an approximation method. This model has the ability to simulate turbulent combustion and compared to computational fluid dynamic (CFD) models it is computationally faster and efficient. The selective outputs are cylinder temperature and pressure, heat transfer, brake work, brake thermal and volumetric efficiency, brake torque, brake power (BP), brake specific fuel consumption (BSFC), brake mean effective pressure (BMEP), concentration of CO2, brake specific CO (BSCO) and brake specific NOx (BSNOx). In this model, the effect of engine speed, equivalence ratio and ignition time on performance parameters using gasoline and CNG fuels are analysed. In addition, the model is validated by experimental data using the results obtained from bi-fuel engine tests. Therefore, this engine model was capable to predict, analyse and useful for optimisation of the engine performance parameters. The exergy based four-stroke bi-fuel (CNG and gasoline) spark ignition (SI) engine model (EBSIEM) here is used for analysis of bi-fuel SI engines. Since, the first law of thermodynamic (the FLT), alone is not able to afford an appropriate comprehension into engine operations. Therefore, this thesis concentrates on the SI engine operation investigation using the developed engine model by the second law of thermodynamic (the SLT) or exergy analysis outlook (exergy based SI engine model (EBSIEM)) In this thesis, an efficient approach is presented for the prediction of total availability, brake specific CO (BSCO), brake specific NOx (BSNOx) and brake torque for bi-fuel engine (CNG and gasoline) using an artificial neural network (ANN) model based on exergy based SI engine (EBSIEM) (ANN-EBSIEM) as an emulator to speed up the optimisation processes. In the other words, the use of a well trained an ANN is ordinarily much faster than mathematical models or conventional simulation programs for prediction. The constrained particle swarm optimisation (CPSO)-EBSIEM (EBSIEMO) was capable of optimising the model parameters for the engine performance. The optimisation results based upon availability analysis (the SLT) due to analysing availability terms, specifically availability destruction (that measured engine irreversibilties) are more regarded with higher priority compared to the FLT analysis. In this thesis, exergy based SI engine model optimisation (EBSIEMO) is studied and evaluated. A four-stroke bi-fuel spark ignition (SI) engine is modelled for optimisation of engine performance based upon exergy analysis. An artificial neural network (ANN) is used as an emulator to speed up the optimisation processes. Constrained particle swarm optimisation (CPSO) is employed to identify parameters such as equivalence ratio and ignition time for optimising of the engine performance, based upon maximising ¿total availability¿. In the optimisation process, the engine exhaust gases standard emission were applied including brake specific CO (BSCO) and brake specific NOx (BSNOx) as the constraints. The engine model is developed in a two-zone model, while considering the chemical synthesis of fuel, including 10 chemical species. A computer code is developed in MATLAB software to solve the equations for the prediction of temperature and pressure of the mixture in each stage (compression stroke, combustion process and expansion stroke). In addition, Intake and exhaust processes are calculated using an approximation method. This model has the ability to simulate turbulent combustion and compared to computational fluid dynamic (CFD) models it is computationally faster and efficient. The selective outputs are cylinder temperature and pressure, heat transfer, brake work, brake thermal and volumetric efficiency, brake torque, brake power (BP), brake specific fuel consumption (BSFC), brake mean effective pressure (BMEP), concentration of CO2, brake specific CO (BSCO) and brake specific NOx (BSNOx). In this model, the effect of engine speed, equivalence ratio and ignition time on performance parameters using gasoline and CNG fuels are analysed. In addition, the model is validated by experimental data using the results obtained from bi-fuel engine tests. Therefore, this engine model was capable to predict, analyse and useful for optimisation of the engine performance parameters. The exergy based four-stroke bi-fuel (CNG and gasoline) spark ignition (SI) engine model (EBSIEM) here is used for analysis of bi-fuel SI engines. Since, the first law of thermodynamic (the FLT), alone is not able to afford an appropriate comprehension into engine operations. Therefore, this thesis concentrates on the SI engine operation investigation using the developed engine model by the second law of thermodynamic (the SLT) or exergy analysis outlook (exergy based SI engine model (EBSIEM)) In this thesis, an efficient approach is presented for the prediction of total availability, brake specific CO (BSCO), brake specific NOx (BSNOx) and brake torque for bi-fuel engine (CNG and gasoline) using an artificial neural network (ANN) model based on exergy based SI engine (EBSIEM) (ANN-EBSIEM) as an emulator to speed up the optimisation processes. In the other words, the use of a well trained an ANN is ordinarily much faster than mathematical models or conventional simulation programs for prediction. The constrained particle swarm optimisation (CPSO)-EBSIEM (EBSIEMO) was capable of optimising the model parameters for the engine performance. The optimisation results based upon availability analysis (the SLT) due to analysing availability terms, specifically availability destruction (that measured engine irreversibilties) are more regarded with higher priority compared to the FLT analysis.

This work concerns a systematic study of IC engine operation with 100% biogas as fuel (as opposed to the dual-fuel mode) with particular emphasis on operational issues and the quest for high efficiency strategies. As a first step, a commercially available 1.2 kW genset engine is modified for biogas operation. The conventional premixing of air and biogas is compared with a new manifold injection strategy. The effect of biogas composition on engine performance is also studied. Results from the genset engine study indicate a very low overall efficiency of the system. This is mainly due to the very low compression ratio (4.5) of the engine. To gain further insight into factors that contribute to this low efficiency, thermodynamic engine simulations are conducted. Reasonable agreement with experiments is obtained after incorporating estimated combustion durations. Subsequently, the model is used as a tool to predict effect of different parameters such as compression ratio, spark timing and combustion durations on engine performance and efficiency. Simulations show that significant improvement in performance can be obtained at high compression ratios. As a step towards developing a more efficient system and based on insight obtained from simulations, a high compression ratio (9.2) engine is selected. This engine is coupled to a 3 kW alternator and operated on 100% biogas. Both strategies, i.e., premixing and manifold injection are implemented. The results show very high overall (chemical to electrical) efficiencies with a maximum value of 22% at 1.4 kW with the manifold injection strategy. The new manifold injection strategy proposed here is found to be clearly superior to the conventional premixing method. The main reasons are the higher volumetric efficiency (25% higher than that for the premixing mode of supply) and overall lean operation of the engine across the entire load range. Predictions show excellent agreement with measurements, enabling the model to be used as a tool for further study. Simulations suggest that a higher compression ratio (up to 13) and appropriate spark advance can lead to higher engine power output and efficiency.

The current work, through experimental and numerical investigations, analyses the process and cycle level deviations in engine response on fuelling multi-cylinder natural gas engines with producer gas. Producer gas is a low calorific value bio-derived alternative with composition of 19 ± 1% CO and H2, 2 ± 0.5 % CH4, 12 ± 1% CO2 and 46 ± 1% N2 and has thermo-physical properties significantly different from natural gas. Experimental investigations primarily address the energy balance (full cycle analysis) and in-cylinder response (process specific analysis) at various operating conditions covering naturally aspirated and turbocharged mode of operation with natural gas and producer gas. Numerical investigations are based on two thermodynamic scope mathematical models, a zero dimensional model (Wiebe function) and a quasi-dimensional model (propagating flame front heat release). A detailed diagnostic analysis on a six cylinder (E6) indicates, turbocharger mismatch, the first explicit impact of fuel thermo-physical property variation. Turbocharger matching and optimization resulted in a peak load of 72.8 kWe (BMEP 9.47) at a maximum brake torque ignition angles of 22 deg before TDC and compressor pressure ratio of 2.25. Engine energy distribution analysis indicates skewed energy balance with higher cooling load (in excess of 30%) as compared to fossil fuel operation. This is attributed to the presence of nearly 20% H2 which enhances the convective cooling through the higher thermal conductivity. Parametric variation of H2 fraction on a two cylinder engine (E2) with four different syngas compositions (mixture H2 varying from 7.1% to 14.2%) depicts enhanced cooling load from 33.5% to 37.7%. Process level comparison indicates significant deviations in the heat release profile compared to fossil fuels. It has been observed that with an increase in mixture hydrogen fraction (from 7.1% to 14.2%), the fast burn phase combustion duration reduces from 59.6% to 42.6% but the terminal stage duration increases from 25.5% to 48.9%. The enhanced cooling of the mixture (due to the presence of hydrogen), particularly in the vicinity of walls is argued to contribute towards the sluggish terminal phase combustion. Immediate implication of thermo-kinematic response variation is on the magnitude and sensitivity of combustion descriptors and the need for dependent control system calibration for producer gas fuelled operation is established. Descriptor analysis is extended to knocking pressure traces and a new simple methodology is proposed towards identifying the occurrence and regime of knock. Analysing the implications through numerical investigation, the influence of the altered thermo-kinematic response for producer gas fuelled operation impacts 0D simulations. Zero dimensional simulations fail with conventional coefficients requiring fuel specific coefficients. Based on fuel specific coefficients, the suitability of 0D model for the simulation of varying operating conditions ranging from naturally aspirated to turbo charged engines, compression ratios and different engine geometries is established. The analysis is extended to quasi-dimensional through the eddy entrainment and laminar burn up model. The choice of laminar flame speed and turbulent parameters is validated based on the assessment of the flame speed ratio (4.5 ± 0.5 for naturally aspirated operation, turbulent Reynolds number of 2500 ± 250 and 9.0 ± 1.0 for turbocharged operation, turbulent Reynolds number of 5250 ± 250). In the estimation of laminar flame speed, the limitation of GRIMech 3.0 mechanism for H2-CO-CH4 systems is explicitly established and GRIMech 2.11 is used to arrive at experimentally comparable results. In-cylinder engine simulation results covering parametric variation of load, ignition angle and mixture quality, for engine natural gas fuelled naturally aspirated operation and producer gas fuelled naturally aspirated and turbocharged after cooled are compared with experimental results. The quasi dimensional analysis is extended to simulate end gas auto-ignition and is validated by using experimental manifold conditions for turbocharged operation for which knock has been observed. Extending the model to a Waukesha cooperative fuels research engine, motor methane number of 110 is reported for standard composition producer gas. The use of quasi dimensional models with end gas reaction kinetics enabled for knock rating of fuels represents first of its kind initiative.