Reducing fuel consumption, noxious emissions and radiated noise by selection of the optimal control strategy of a Diesel engine

Despite the recent efforts devoted to develop alternative technologies, it is likely that the internal combustion engine will remain the dominant propulsion system for the next 30 years and beyond. Also as a consequence of more and more stringent emissions regulations established in the main industrialized countries, strongly demanded are methods and technologies able to enhance the internal combustion engines performance in terms of both efficiency and environmental impact. Present work focuses on the development of a numerical method for the optimization of the control strategy of a diesel engine equipped with a high pressure injection system, a variable geometry turbocharger and an EGR circuit. A preliminary experimental analysis is presented to characterize the considered six-cylinder engine under various speeds, loads and EGR ratios. The fuel injection system is separately tested on a dedicated test bench, to determine the instantaneous fuel injection rate for different injection strategies. The collected data are employed for tuning proper numerical models, able to reproduce the engine behaviour in terms of performances (in-cylinder pressure, boost pressure, air-flow rate, fuel consumption), noxious emissions (soot, NO) and radiated noise. In particular, a 1D tool is developed with the aim of characterizing the flow in the intake and exhaust systems and predicting the engine-turbocharger matching conditions, by including a short-route EGR circuit; a 3D model (AVL Fire™) is assessed to reproduce into detail the in-cylinder thermo-fluidynamic processes, including mixture formation, combustion, and main pollutants production; an in-house routine, also validated against available data, is finally developed for the prediction of the combustion noise, starting from in-cylinder pressure cycles. Obviously, data exchange between the codes is previewed. The overall numerical procedure is firstly checked with reference to the experimentally analysed operating points. The 1D, 3D and combustion noise models are then coupled to an external optimizer (ModeFRONTIER™) in order to select the optimal combination of the engine control parameters to improve the engine performance and to contemporary minimize noise, emissions and fuel consumption. Under the hypothesis of a pilot-main injection strategy, a multiobjective optimization problem is solved through the employment of a genetic algorithm. Eight degrees of freedom are defined, namely start of injection, dwell time, energizing time of pilot and main pulses, EGR valve opening, throttle valve opening, swirl level, and turbine opening ratio. It is shown that non-negligible improvements can be gained, also depending on the importance given to the various objectives.