Enhanced combustion model with fuel-wall impingement oriented to injection pattern tuning in automotive Diesel engines

Nowadays the high competition reached by the automotive market forces original equipment manufacturers (OEMs) towards innovative solutions. Strict emission standards and fuel economy targets make the work hard to be accomplished. Therefore modern engines feature complex architecture and embed new devices for exhaust gas recirculation (EGR), turbocharging (e.g. multi-stage compressors), gas after-treatment (e.g. selective catalyst reduction (SCR)) and fuel injection (either high or low pressure). In this context the engine management system (EMS) plays a fundamental role to optimize engine operation. The paper deals with fuel spray and combustion simulation by a multi-zone phenomenological model aimed at the optimal tuning of the injection pattern. The fuel spray model simulates the injection process, the fuel-air mixture formation, the in-cylinder gas mixture evolution and accounts for the fuel-wall impingement that usually occurs in case of low-medium injection pressure or advanced injection timing. This feature is fundamental to investigate a wide range of injection pattern set-points, as those applied for advanced combustion concepts (i.e. Premixed Charge Compression Ignition (PCCI)). The impingement of the spray on cylinder walls is modeled by a zero-dimensional approach, simulating dynamics and evaporation of the fuel film with two different semi-empirical models. The numerical and experimental analyses have been performed with respect to an automotive Common-Rail Diesel engine, equipped with high pressure EGR and VGT turbocharger. The experimental measurements have been carried out at the engine test stand, investigating operating conditions with highly advanced injection timing and low rail pressure, in order to induce the fuel impingement process. Model validation against the experimental data exhibits satisfactory accuracy in predicting the impact of injection pattern control on impingement.