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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 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.

Diesel spray experimentation at controlled high-temperature and high-pressure conditions is intended to provide a more fundamental understanding of diesel combustion than can be achieved in engine experiments. This level of understanding is needed to develop the high-fidelity multi-scale CFD models that will be used to optimize future engine designs. Several spray chamber facilities capable of high-temperature, high-pressure conditions typical of engine combustion have been developed, but because of the uniqueness of each facility, there are uncertainties about their operation. The Engine Combustion Network (ECN) is a worldwide group of institutions using combustion vessels, whose aim is to advance the state of spray and combustion knowledge at engine-relevant conditions. A key activity is the use of spray chamber facilities operated at specific target conditions in order to leverage research capabilities and advanced diagnostics of all ECN participants.

Knowledge of fuel mass injected in an individual cycle is important for engine performance and modeling. At the moment, such measurements are not possible on engine or in real time. In this article, a new method using Coriolis flow meters (CFMs) and a new, patented, signal processing technique, known as the Prism, are introduced. CFMs are extensively used for flow measurement both in the automotive industry and further afield and, when coupled with the Prism, have the potential to make these challenging high-speed measurements. A rig-based feasibility study was conducted injecting very small quantities of diesel (3 mg) at pressures of up to 1000 bar at simulated engine speeds of up to 4000 rpm. The results show that these small quantities can in principle be measured. The results also reveal a previously unknown behavior of CFMs when measuring very low flow rates at high speed.

This paper discusses a method of measuring the instantaneous exhaust gas temperature by thermocouples. Measuring the exhaust gas temperature is useful for a better understanding of engine processes. Thermocouples do not measure the instantaneous exhaust gas temperature because of their limited dynamic response. A thermocouple compensation technique has been developed to estimate the time constant in situ. This method has been commissioned in a simulation study and a controlled experiment with a reference temperature. The studies have shown that the signal bandwidth has to be restricted, since noise will be amplified in the temperature reconstruction. The technique has been successfully applied to some engine exhaust measurements. A comparison between two independent pairs of thermocouples has shown that temperature variations at frequencies up to 80Hz can be recovered.

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.

Methanol fueled spark ignition (SI) engines have the potential for very high efficiency using an advanced heat recovery system for fuel reforming. In order to allow simulation of such an engine system, several sub-models are needed. This paper reports the development of two laminar burning velocity correlations, corresponding to two reforming concepts, one in which the reformer uses water from an extra tank to produce hydrogen rich gas (syngas) and another that employs the water vapor in the exhaust gas recirculation (EGR) stream to produce reformed-EGR (R-EGR). This work uses a one-dimensional (1D) flame simulation tool with a comprehensive chemical kinetic mechanism to predict the laminar burning velocities of methanol/syngas blends and correlate it. The syngas is a mixture of H2/CO/CO2 with a CO selectivity of 6.5% to simulate the methanol steam reforming products over a Cu-Mn/Al catalyst.

The present work details a study of the heat flux through the walls of an internal combustion engine. The determination of this heat flux is an important aspect in engine optimization, as it influences the power, efficiency and the emissions of the engine. Therefore, a set of simulation tools in the OpenFOAM® software has been developed, that allows the calculation of the heat transfer through engine walls for ICEs. Normal practice in these types of engine simulations is to apply a wall function model to calculate the heat flux, rather than resolving the complete thermo-viscous boundary layer, and perform simulations of the closed engine cycle. When dealing with a complex engine, this methodology will reduce the overall computational cost. It however increases the need to rely on assumptions on both the initial flow field and the behavior in the near-wall region.

A two-dimensional finite element model has been used to analyze the unsteady heat conduction behavior of an eroding type of surface thermocouple. The impulse response of the thermocouple was analyzed by using both a one-dimensional solution and a two-dimensional model. The experimental impulse response of the thermocouple was investigated by a laser impulse excitation experiment to validate the modeling results. The modeling results showed that there was a significant difference between the two-dimensional modeling and the one-dimensional analytical solution, especially before 1 ms. The two-dimensional modeling result is closer to the laser impulse experiment result, which implies the existence of a multi-dimensional effect on the transient heat conduction within the eroding thermocouple.

Accurate modeling of the initial transient period of spray development is critical within diesel engines, as it impacts on the amount of vapor penetration and hence the combustion characteristics of the spray. In addition, in multiple injection schemes shorter injections will be mostly, if not totally, within the initial transient period. This paper investigates how two different commercially available Computational Fluid Dynamics (CFD) codes (hereafter noted as Code 1 and Code 2) simulate transient diesel spray atomization, in a non-combusting environment. The case considered for comparison is a single-hole injection of n-dodecane representing the Engine Combustion Network’s ‘Spray A’ condition. It was identified that the different spray break-up models used by the codes (Reitz-Diwakar for Code 1, Kelvin-Helmholtz/Rayleigh-Taylor (KH-RT) for Code 2) had a significant impact on the transient liquid penetration.

High altitude ice crystals have led to instances of ice accretion on stationary compressor surfaces in aeroengines. Rollback, surge and stall events are known to have been instigated through such accretions due to aerodynamic losses related to ice growth, damage and flameout due to ice shedding. The prevalence of these events has led to a change in certification requirements for icing conditions. Development of accurate numerical models allows the costs of certification and testing to be minimised. An in-house computational code was developed at the Oxford Thermofluids Institute to model glaciated and mixed-phase ice crystal icing. The Ice Crystal Icing ComputationaL Environment (ICICLE) code, comprises a frozen 2D flowfield solution, Lagrangian particle tracking, particle heat transfer and phase change and particle surface interaction modelling.

To speed up the development of the next-generation combustion engines with renewable fuels, the importance of reliable and robust simulations cannot be overemphasized. Compared to gasoline, methanol is a promising fuel for spark-ignited engines due to its higher research octane number to resist auto-ignition, higher flame speed for faster combustion and higher heat of vaporization for intake charge cooling. These advantageous properties all contribute to higher thermal efficiency and lower knock tendency, and they need to be well-captured in the simulation environment in order to generate accurate predictions. In this paper, the sub-models which estimate the burning velocities and ignition delay of methanol are revisited. These building blocks are implemented and integrated in a quasi-dimensional simulation environment to predict the combustion behavior, which are subsequently validated against test data measured on both light-duty and heavy-duty engines.

This paper has two parts. The first compares the measured burned gas temperature using Coherent Anti-Stokes Raman Scattering (CARS) with the predictions of a multiple zone computer simulation of combustion. The second part describes a system that is capable of determining the heat flux into the combustion chamber by means of measuring the chamber surface temperature. It is shown that the multi-zone computer simulation can accurately predict the burned gas temperature once the fuel burn rate has been analyzed and the model tuned correctly. The effect of different fuels (methane and iso-octane) on the burned gas temperature is reported. A high burn rate or more advanced ignition timing gave a lower burned gas temperature towards the end of the engine cycle. The surface heat flux was deduced from measurements of the surface temperature by using a finite difference method.

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.

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.

Accurate modelling for spray vapour fields is critical to enable adequate predictions of spray ignition and combustion characteristics of non-premixed reacting diesel sprays. Spray vapour characteristics are in turn controlled by liquid atomization and the KH-RT liquid jet break-up model is regularly used to predict this: with the KH model used for predicting primary break-up given its definition as a surface wave growth model, and the RT model used for predicting secondary break-up due to it being a drag based, stripping model. This paper investigates how the alteration of the switching position of the KH and RT sub-models within the KH-RT model impacts the resulting vapour field and ignition characteristics. The combustion prediction is handled by the implementation of a 54 species, 269 reaction skeletal mechanism utilising a Well Stirred Reactor model within the Star-CD CFD code.

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].

The present work describes the numerical modeling of medium-speed marine engines, operating in a fumigated dual-fuel mode, i.e. with the second fuel injected in the ports. This engine technology allows reducing engine-out emissions while maintaining the engine efficiency and can be fairly easily retrofitted from current diesel engines. The main premixed fuel that is added can be a low-carbon one and can additionally be of a renewable nature, thereby reducing or even completely removing the global warming impact. To fully optimize the operational parameters of such a large marine engine, computational fluid dynamics can be very helpful. Accurately describing the combustion process in such an engine is key, as the prediction of the heat release and the pollutant formation is crucial. Auto-ignition of the diesel fuel needs to be captured, followed by the combustion and flame propagation of the premixed fuel.

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.

The need for simulation tools for the internal combustion engine is becoming more and more important due to the complex engine design and increasingly strict emission regulation. One needs accurate and fast models, but fuels consist of a complex mixture of different molecules which cannot realistically be handled in computations. Simplifications are required and are realized using fuel surrogates. The main goal of this work is to show that the choice of the surrogates is of importance if simplified models are used and that the performance strongly depends upon the sensitivity of the fuel properties that refer to the main model hypotheses. This paper starts with an overview of surrogates for diesel and bio-diesel as well as the motivation for choosing them. Next, a phenomenological model for vaporizing fuel-sprays is implemented to assess how well-known surrogates for diesel and bio-diesel affect the obtained results.