The search for next generation transportation fuels in order to fully or partially replace petrol based fuels has resulted in use of varieties of fuels and fuel blends in internal combustion engines. However, the engine management systems are fuel specific and therefore, every major change in fuel composition requires significant amount of calibration work to optimize the operating variables in order to meet legislative emission targets and reduce the real-world emission and improve fuel economy levels. The current work has successfully devised a numerical simulation for the operation of a modern 4-cylinder turbocharged engine using an adaptive combustion modelling methodology that identifies a fuel type during engine start itself, and adapts engine operating parameters for optimum performance. A strategy was devised to use commercially available sensors to obtain and correlate measurable cylinder pressure based information for fuel identification.The engine model for a 1.6L turbocharged GDI engine was built in 1-D code and fully validated with measured data. This model was used to simulate combustion of four different fuels and build fuel specific correlations for engine start and higher operating speeds. Correlations for peak pressure, rate of pressure rise and emissions were used to develop strategies for fuel identification. Finally, these strategies were implemented using a GT-POWER-MATLAB coupling, for demonstration of the ‘smart’ engine operation. This report presents a detailed step-by-step methodology for the model validation, drawing up of the operating correlations and strategies, and implementation of the same through a program code.