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Particulate emissions from gasoline direct injection (GDI) engines continue to be a topic of substantial research interest. Forthcoming regulation both in the USA and the EU will further reduce their emission and drive innovation. Substantial research effort is spent undertaking experiments to understand, characterize, and research particle number (PN) emissions from engines and vehicles. Recent advances in computing power, data storage, and understanding of artificial intelligence algorithms now mean that these are becoming an important tool in engine research. In this work a random forest (RF) algorithm is used for the prediction of PN emissions from a highly boosted (up to 32 bar BMEP) GDI engine. Particle size, concentration, and the accumulation mode geometric standard deviation (GSD) are all predicted by the model. The results are analysed and an in depth study on parameter importance is carried out.

The use of direct injection spark ignition (DISI) engines for passenger cars has increased; providing greater specific performance and lower CO₂ emissions. DISI engines, however, produce more particulate matter (PM) emissions than Port-Fuel-Injected (PFI) engines. Forthcoming European exhaust emissions legislation is addressing concerns over health effects of PM emissions. Accordingly, research into PM emission formation has increased. A model developed by Aikawa et al., (2010) for PFI engines correlated PM number emissions with the vapor pressure and the double bond equivalent (DBE) of the components of the fuel. However there was no independent control of these parameters. This study investigates a particulate emissions index for DISI engines.

Diesel engine designers often use swirl flaps to increase air motion in cylinder at low engine speeds, where lower piston velocities reduce natural in-cylinder swirl. Such in-cylinder motion reduces smoke and CO emissions by improved fuel-air mixing. However, swirl flaps, acting like a throttle on a gasoline engine, create an additional pressure drop in the inlet manifold and thereby increase pumping work and fuel consumption. In addition, by increasing the fuel-air mixing in cylinder the combustion duration is shortened and the combustion temperature is increased; this has the effect of increasing NOx emissions. Typically, EGR rates are correspondingly increased to mitigate this effect. Late inlet valve closure, which reduces an engine’s effective compression ratio, has been shown to provide an alternative method of reducing NOx emissions.

Particulate emissions from Gasoline Direct Injection (GDI) engines have been an important topic of recent research interest due to their known environmental effects. This review paper will characterise the influence of different gasoline direct injection fuel systems on particle number (PN) emissions. The findings will be reviewed for engine and vehicle measurements with appropriate driving cycles (especially real driving cycles) to evaluate effects of the fuel injection systems on PN emissions. Recent technological developments alongside the trends of the influence of system pressure and nozzle design on injector tip wetting and deposits will be considered. Besides the engine and fuel system it is known that fuel composition will have an important effect on GDI engine PN emissions. The evaporation qualities of fuels have a substantial influence on mixture preparation, as does the composition of the fuel itself.

The European Particle Measurement Program (PMP) defines the current standard for measurement of Particle Number (PN) emissions from vehicles in Europe. This specifies a 50% count efficiency (D50) at 23 nm and a 90% count efficiency (D90) at 41 nm. Particulate emissions from Gasoline Direct Injection (GDI) engines have been widely studied, but usually only in the context of PMP or similar sampling procedures. There is increasing interest in the smallest particles - i.e. smaller than 23 nm - which can be emitted from vehicles. The literature suggest that by moving D50 to 10 nm, PN emissions from GDI engines might increase by between 35 and 50% but there remains a lot of uncertainty.

Several governments are increasing the blending mandate of renewable fuels to reduce the life-cycle greenhouse gas emissions of the road transport sector. Currently, ethanol is a prominent renewable fuel and is used in low-level blends, such as E10 (10 %v/v ethanol, 90 %v/v gasoline) in many parts of the world. However, the exact concentration of ethanol amongst other renewable fuel components in commercially available fuels can vary and is not known. To understand the impact of the renewable fuel content on the emissions from Euro 6d-TEMP emissions specification vehicles, this paper examines the real-driving emissions (RDE) from four 2020 to 2022 model-year vehicles run on E0 and E10 fuels. CO, CO2, NO, and NO2 were measured through a Portable Emissions Measuring System (PEMS).