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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.

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.

Ingestion of high altitude atmospheric ice particles can be hazardous to gas turbine engines in flight. Ice accretion may occur in the core compression system, leading to blockage of the core gas path, blade damage and/or flameout. Numerous engine powerloss events since 1990 have been attributed to this mechanism. An expansion in engine certification requirements to incorporate ice crystal conditions has spurred efforts to develop analytical models for phenomenon, as a method of demonstrating safe operation. A necessary component of a complete analytical icing model is a thermodynamic accretion model. Continuity and energy balances are performed using the local flow conditions and the mass fluxes of ice and water that are incident on a surface to predict the accretion growth rate.

The analysis of thermal fields in the underhood region is complicated by the complex geometry and the influence of a multitude of different heat sources. This complexity means that running full CFD analyses to predict the thermal field in this region is both computationally expensive and time consuming. A method of predicting the thermal field using linear superposition has been developed in order to analyse the underhood region of a simplified Formula One race car, though the technique is applicable to all vehicles. The use of linear superposition allows accurate predictions of the thermal field within a complex geometry for varying boundary conditions with negligible computational costs once the initial characterisation CFD has been run. A quarter scale, rear end model of a Formula One race car with a simplified internal assembly is considered for analysis, though the technique can also be applied to commercial and industrial vehicles.

Models for the convective heat transfer from the combustion gases to the walls inside a spark ignition engine are an important keystone in the simulation tools which are being developed to aid engine optimization. The existing models have, however, been cited to be inaccurate for hydrogen, one of the alternative fuels currently investigated. One possible explanation for this inaccuracy is that the models do not adequately capture the effect of the gas properties. These have never been varied in a wide range because air and ‘classical’ fossil fuels have similar values, but they are significantly different in the case of hydrogen. As a first step towards a fuel independent heat transfer model, we have investigated the effect of the gas properties on the heat flux in a spark ignition engine.

A wide-ranging investigation into the sensitivity of the hybrid RANS-LES based OpenFOAM CFD process at Audi was undertaken. For a range of cars (A1, TT, Q3 & A4) the influence of the computational grid resolution, turbulence model formulation and spatial & temporal discretization is assessed. It is shown that SnappyHexMesh, the Cartesian-prismatic built-in OpenFOAM mesher is unable to generate low y+ grids of sufficient quality for the production Audi car geometries. For high y+ grids there was not a consistent trend of additional refinement leading to improved correlation between CFD and experimental data. Similar conclusions were found for the turbulence models and numerical schemes, where consistent improvements over the baseline setup for all aerodynamic force coefficients were in general not possible. The A1 vehicle exhibited the greatest sensitivity to methodology changes, with the TT showing the least sensitivity.

Homogeneous charge compression ignition (HCCI) engines are a promising alternative to traditional spark- and compression-ignition engines, due to their high thermal efficiency and near-zero emissions of NOx and soot. Simulation software is an essential tool in the development and optimization of these engines. The heat transfer submodel used in simulation software has a large influence on the accuracy of the simulation results, due to its significant effect on the combustion. In this work several empirical heat transfer models are assessed on their ability to accurately predict the heat flux in a CFR engine during HCCI operation. Models are investigated that are developed for traditional spark- and compression-ignition engines such as those from Annand [1], Woschni [2] and Hohenberg [3] and also models developed for HCCI engines such as those from Chang et al. [4] and Hensel et al. [5].

Spray guided Direct Injection Gasoline Engines are a key enabler to reducing CO2 emissions and improving the fuel economy of light duty vehicles. Particulate emissions from these engines have been shown to be lower than from first generation direct injection gasoline engines, but they may still be significantly higher than port fuel injected engines due to the reduced time available for mixture preparation and increased incidence of fuel impingement on the piston crown and combustion chamber surfaces. These factors are particularly severe in the period following a cold start. Both nuclei and accumulation mode particle size and number concentration were measured using a Cambustion differential mobility spectrometer. These data are reported for different coolant temperature intervals during the warm-up period. The bulk composition was determined using thermo-gravimetric analysis, and PM mass fractions are given for different volatility ranges and for elemental carbon.

A single cylinder Direct Injection Spark Ignition (DISI) engine with optical access has been used for combustion studies with both early injection and late injection for stratified charge operation. Cylinder pressure records have been used for combustion analysis that has been synchronised with the imaging. A high speed cine camera has been used for imaging combustion within a cycle, while a CCD camera has been used for imaging at fixed crank angles, so as to obtain information on cycle-by-cycle variations. The CCD images have also been analysed to give information on the quantity of soot present during combustion. Tests have been conducted with a reference unleaded gasoline (ULG), and pure fuel components: iso-octane (a representative alkane), and toluene (a representative aromatic). The results show diffusion-controlled combustion occurring in so-called homogeneous combustion with early injection.

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).

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.

In-cylinder temperatures and their cyclic variations strongly influence many aspects of internal combustion engine operation, from chemical reaction rates determining the production of NOx and particulate matter to the tendency for auto-ignition leading to knock in spark ignition engines. Spatially resolved measurements of temperature can provide insights into such processes and enable validation of Computational Fluid Dynamics simulations used to model engine performance and guide engine design. This work uses a combination of Two-Colour Planar Laser Induced Fluorescence (TC-PLIF) and Laser Induced Grating Spectroscopy (LIGS) to measure the in-cylinder temperature distributions of a firing optically accessible spark ignition engine. TC-PLIF performs 2-D temperature measurements using fluorescence emission in two different wavelength bands but requires calibration under conditions of known temperature, pressure and composition.

A Cambustion Differential Mobility Spectrometer (DMS500), Dekati Electrical Low Pressure Impactor (ELPI), TSI Condensation Particle Counter (CPC) and AVL Photo-Acoustic Soot Sensor (PASS) were compared for measurements of emitted Particulate Matter (PM) from a Direct Injection Spark Ignition (DISI) vehicle on the New European Drive Cycle (NEDC) and at steady speed operating points. The exhaust was diluted in a Constant Volume Sampler (CVS) before being measured. Transient size spectral data from the DMS500 and ELPI is presented. PM Number rate and total PM number emissions are presented for the DMS500, ELPI and CPC. The DMS500 and ELPI data are post-processed for PM mass, and presented with data from the PASS. The instrument responses were correlated against each other. Qualitative agreement was generally found between all instruments. The agreement was closer for PM mass measurements than for measurements of PM number.

A significant number of historical engine powerloss events have recently been attributed to ingestion of high altitude ice crystals, prompting regulators to expand engine certification envelopes to incorporate ‘ice crystal icing’ conditions. There has been a resulting effort by OEMs and academia to develop analytical and semi-empirical models for the phenomenon, partly through use of rig testing. The current study presents results and analysis of experiments conducted in the National Research Council’s Research Altitude Test Facility (RATFac). The experiments used a simplified compressor stator vane test article, designed to produce data to build semi-empirical models and validate an existing ice crystal icing code. Accretion growth rates, extracted from backlit shadowgraphy, are presented as a function of test condition, and the algorithm of a new image processing technique using Canny filtering is discussed.

High altitude ice crystals can pose a threat to aircraft engine compression and combustion systems. Cases of engine damage, surge and rollback have been recorded in recent years, believed due to ice crystals partially melting and accreting on static surfaces (stators, endwalls and ducting). The increased awareness and understanding of this phenomenon has resulted in the extension of icing certification requirements to include glaciated and mixed phase conditions. Developing semi-empirical models is a cost effective way of enabling certification, and providing simple design rules for next generation engines. A comprehensive ice crystal icing model is presented in this paper, the Ice Crystal Icing ComputationaL Environment (ICICLE). It is modular in design, comprising a baseline code consisting of an axisymmetric or 2D planar flowfield solution, Lagrangian particle tracking, air-particle heat transfer and phase change, and surface interactions (bouncing, fragmentation, sticking).

Color-ratio pyrometry (CRP) is a technique for estimating the temperature and loading of soot, based on its thermal emission spectrum. This technique is contrasted with conventional two-color pyrometry which requires absolute measurements of the radiation intensity, either at two specific wavelengths or ranges of wavelengths. CRP uses two ratios, obtained by measuring the radiation intensity for three wavelengths or wavelength bands. CRP has been implemented here by using a digital CCD camera, and full details of the calibration are reported. Because of uncertainties in the emissivity of reference sources (such as tungsten ribbon lamps, in which the emissivity depends on temperature and wavelength), then a spectroscopic calibration of the CCD camera has been used. Use of a CCD camera is not straightforward because of internal digital signal processing (DSP), so full details are given of the calibration and technique implementation.

In-cylinder temperature measurements are vital for the validation of gasoline engine modelling and useful in their own right for explaining differences in engine performance. The underlying chemical reactions in combustion are highly sensitive to temperature and affect emissions of both NOx and particulate matter. The two techniques described here are complementary, and can be used for insights into the quality of mixture preparation by measurement of the in-cylinder temperature distribution during the compression stroke. The influence of fuel composition on in-cylinder mixture temperatures can also be resolved. Laser Induced Grating Spectroscopy (LIGS) provides point temperature measurements with a pressure dependent precision in the range 0.1 to 1.0 % when the gas composition is well characterized and homogeneous; as the pressure increases the precision improves.

In-cylinder spray imaging by Mie scattering has been taken with frame rates up to 27,000 fps, along with high speed video photography of chemiluminescence and soot thermal radiation. Spectroscopic measurements have confirmed the presence of OH*, CH* and C2* emissions lines, and their magnitude relative compared to soot radiation. Filtering for CH* has been used with both the high speed video and a Photo-Multiplier Tube (PMT). The PMT signals have been found to correlate with the rate of heat release derived from in-cylinder pressure measurements. A high power photographic strobe has been used to illuminate the fuel spray. Images show that the fuel spray can strike the ground strap of the spark plug, break up, and a fuel cloud then drifts over and under the strap through the spark plug gap. Tests have conducted at two different spark plug orientations using a single spark strategy.

The introduction of transient test cycles and the focus on real world driving emissions has increased the importance of ensuring the NOx and soot emissions are controlled during transient manoeuvres. At the same time, there is a drive to reduce the number of calibration variables used by engine control strategies to reduce development effort and costs. In this paper, a control orientated combustion model, [1], and model predictive control strategy, [2], that were developed in simulation and reported in earlier papers, are applied to a Diesel engine and demonstrated in a test vehicle. The paper describes how the control approach developed in simulation was implemented in embedded hardware, using an FPGA to accelerate the emissions calculations. The development of the predictive controller includes the application of a simplified optimisation algorithm to enable a real-time calculation in the test vehicle.

In-cylinder flow motion has a significant effect on mixture preparation and combustion. Therefore, it is vital that CFD engine simulations are capable of accurately predicting the in-cylinder velocity fields. High-speed planar Particle Image Velocimetry (PIV) experiments have been performed on a single-cylinder GDI optical engine in order to validate CFD simulations for a range of engine conditions. Novel metrics have been developed to quantify the differences between experimental and simulated velocity fields in both alignment and magnitude. The Weighted Relevance Index (WRI) is a variation of the standard Relevance Index that accounts for the local velocity magnitudes to provide a robust comparison of the alignment between two vector fields. Similarly, the Weighted Magnitude Index (WMI) quantifies the differences in the local magnitudes of the two velocity fields.