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The internal combustion engine is considered as one of the main sources for air pollution due to hydrocarbon fuel combustion. The increased land transport usage requires improvement of the engine efficiency and combustion process technology to reduce the engine emissions. A turbocharged engine and the gaseous fuel replacement are the green tools proposed by researchers to enhance fuel saving and emissions reduction. In this paper, both methods were investigated. The methane is a preferred gaseous fuel due to its lower carbon to hydrogen ratio, resulting in lesser HC and CO emissions. In this paper, a turbocharged compression ignition engine with methane/diesel dual fuel is simulated using professional GT-power code to investigate the effect of methane percentage in mixture on the engine performance and emissions. A turbocharged 6 cylinders compression ignition engine has been built and investigated. During the simulation, the methane/diesel ratios were varied from pure diesel with zero percent methane to 90% methane concentration by mass with 10% increment every run. The results show that the engine brake power and specific fuel consumption increased while the thermal efficiency decreased for lower CH 4 concentration. For higher CH 4 percentage, the brake power and thermal efficiency increased while specific fuel consumption decreased. Moreover, NO emission has 35% reduction compared to neat diesel fuel when 50% of methane was added to the mixture. Conversely, the CO and HC concentration increased when the methane ratio is less than 50% compared to neat diesel combustion. In general, the engine efficiency improved when methane was added to diesel fuel in compression ignition engine with turbocharger boost, resulting in lesser emissions and cleaner environment.

Internal combustion engines are a main power source for vehicles. Improving the engine power is important which involved optimizing combustion timing and quantity of fuel. Variable valve timing (VVT) can be used in this respect to increase peak torque and power. In this work Artificial Neural Network (ANN) is used to model the effect of the VVT on the power and genetic algorithm (GA) as an optimization technique to find the optimal power setting. The same proposed technique can be used to improve fuel economy or a balanced combination of both fuel and power. Based on the findings of this work, it was noticed that the VVT setting is more important at high speed. It was also noticed that optimal power can be obtained by changing the VVT settings as a function of speed. Also to reduce computational time in obtaining the optimal VVT setting, an ANN was successfully used to model the optimal setting as a function of speed.