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With the aim of identifying technical solutions to lower the particulate matter emissions, the engine research community made a consistent effort to investigate the root causes leading to soot formation. Nowadays, the computational power increase allows the use of advanced soot emissions models in 3D-CFD turbulent reacting flows simulations. However, the adaptation of soot models originally developed for Diesel applications to gasoline direct injection engines is still an ongoing process. A limited number of studies in literature attempted to model soot produced by gasoline direct injection engines, obtaining a qualitative agreement with the experiments. To the authors’ best knowledge, none of the previous studies provided a methodology to quantitatively match particulate matter, particulate number and particle size distribution function measured at the exhaust without a case-by-case soot model tuning.

The recent interest in alternative non-fossil fuels has led researchers to evaluate several alcohol-based formulations. However, one of the main requirements for innovative fuels is to be compatible with existing units’ hardware, so that full replacement or smart flexible-fuel strategies can be smoothly adopted. n-Butanol is considered as a promising candidate to replace commercial gasoline, given its ease of production from bio-mass and its main physical and chemical properties similar to those of Gasoline. The compared behavior of n-butanol and gasoline was analyzed in an optically-accessible DISI engine in a previous paper [1]. CFD simulations explained the main outcomes of the experimental campaign in terms of combustion behavior for two operating conditions. In particular, the first-order role of the slower evaporation rate of n-butanol compared to gasoline was highlighted when the two fuels were operated under the same injection phasing.

Liquids with stable suspensions of nanoscale materials are defined as nanofluids. As reported in recent scientific literature, a very small amount of suspended nanostructures has the potential to enhance the thermo physical, transport and radiative properties of the base fluid. One of the main applications of this technology is in the field of combustion and fuels. In fact, adding nanomaterials (such as metals, oxides, carbides, nitrides, or carbon-based nanostructures) to liquid fuels is able to enhance ignition and combustion. The focus of this research is to gain a fundamental understanding of the characteristics of a nanofluid fuel prepared using carbon nanoparticles (CNPs) and multi-walled carbon nanotubes (MWCNTs) dispersed in butanol. This study starts with the investigation of the optical properties of the mixtures. The transmission spectra of the nanofluids are measured in a wide wavelength range from UV (250 nm) to near IR (800 nm).

Application of more and more complex control strategies in spark ignition (SI) engines is required for ensuring high conversion efficiency and effective emissions reduction. Closed loop fuel injection is being implemented on an ever wider scale in small size SI units that generally feature single cylinder architecture. For such systems the readings from the exhaust gas oxygen sensor are essential for controlling air-fuel ratio and indirectly combustion. The present study looked at the influence of pressure oscillations on the values given by the sensor, for different equivalence ratio settings in wide open throttle conditions for an experimental SI unit. As expected, the readings were found to be influenced by pressure oscillations in the exhaust line during lean operation, while with stoichiometric and rich fueling the effects were minimal. Fuel type was also found to be an important aspect.