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A simulation method is presented for the analysis of combustion in spark ignition (SI) engines operated at elevated exhaust gas recirculation (EGR) level and employing multiple spark plug technology. The modeling is based on a zero-dimensional (0D) stochastic reactor model for SI engines (SI-SRM). The model is built on a probability density function (PDF) approach for turbulent reactive flows that enables for detailed chemistry consideration. Calculations were carried out for one, two, and three spark plugs. Capability of the SI-SRM to simulate engines with multiple spark plug (multiple ignitions) systems has been verified by comparison to the results from a three-dimensional (3D) computational fluid dynamics (CFD) model. Numerical simulations were carried for part load operating points with 12.5%, 20%, and 25% of EGR. At high load, the engine was operated at knock limit with 0%, and 20% of EGR and different inlet valve closure timing.

The use of complex reaction schemes is accompanied by high computational cost in 3D CFD simulations but is particularly important to predict pollutant emissions in internal combustion engine simulations. One solution to tackle this problem is to solve the chemistry prior the CFD run and store the chemistry information in look-up tables. The approach presented combines pre-tabulated progress variable-based source terms for auto-ignition as well as soot and NOx source terms for emission predictions. The method is coupled to the 3D CFD code CONVERGE v2.4 via user-coding and tested over various speed and load passenger-car Diesel engine conditions. This work includes the comparison between the combustion progress variable (CPV) model and the online chemistry solver in CONVERGE 2.4. Both models are compared by means of combustion and emission parameters. A detailed n-decane/α-methyl-naphthalene mechanism, comprising 189 species, is used for both online and tabulated chemistry simulations.

This paper reports on a fast predictive combustion tool employing detailed chemistry. The model is a stochastic reactor based, discretised probability density function model, without spatial resolution. Employing detailed chemistry has the potential of predicting emissions, but generally results in very high CPU costs. Here it is shown that CPU times of a couple of minutes per cycle can be reached when applying detailed chemistry, and CPU times below 10 seconds per cycle can be reached when using reduced chemistry while still catching in-cylinder in-homogeneities. This makes the tool usable for efficient engine performance mapping and optimisation. To meet CPU time requirements, automatically load balancing parallelisation was included in the model. This allowed for an almost linear CPU speed-up with number of cores available.

In one-dimensional engine simulation programs the simulation of engine performance is mostly done by parameter fitting in order to match simulations with experimental data. The extensive fitting procedure is especially needed for emissions formation - CO, HC, NO, soot - simulations. An alternative to this approach is, to calculate the emissions based on detailed kinetic models. This however demands that the in-cylinder combustion-flow interaction can be modeled accurately, and that the CPU time needed for the model is still acceptable. PDF based stochastic reactor models offer one possible solution. They usually introduce only one (time dependent) parameter - the mixing time - to model the influence of flow on the chemistry. They offer the prediction of the heat release, together with all emission formation, if the optimum mixing time is given.

Interactions between in-cylinder combustion and emission aftertreatment need to be understood for optimizing the overall powertrain system. Numerical investigations can aid this process. For this purpose, simple and numerically fast, but still accurate models are needed for in-cylinder combustion and exhaust aftertreatment. The chemical processes must be represented in sufficient detail to predict engine power, fuel consumption, and tailpipe emission levels of NOx, soot, CO and unburned hydrocarbons. This paper reports on a new transient one-dimensional catalyst model. This model makes use of a detailed kinetic mechanism to describe the catalytic reactions. A single-channel or a set of representative channels are used in the presented approach. Each channel is discretized into a number of cells. Each cell is treated as a perfectly stirred reactor (PSR) with a thin film layer for washcoat treatment. Heat and mass transport coefficients are calculated from Nusselt and Sherwood laws.

Today numerical models are a major part of the diesel engine development. They are applied during several stages of the development process to perform extensive parameter studies and to investigate flow and combustion phenomena in detail. The models are divided by complexity and computational costs since one has to decide what the best choice for the task is. 0D models are suitable for problems with large parameter spaces and multiple operating points, e.g. engine map simulation and parameter sweeps. Therefore, it is necessary to incorporate physical models to improve the predictive capability of these models. This work focuses on turbulence and mixing modeling within a 0D direct injection stochastic reactor model. The model is based on a probability density function approach and incorporates submodels for direct fuel injection, vaporization, heat transfer, turbulent mixing and detailed chemistry.

The development of future gasoline engines is dominated by the study of new technologies aimed at reducing the engine negative environmental impact and increase its thermal efficiency. One common trend is to develop smaller engines able to operate in stoichiometric conditions across the whole engine map for better efficiency, lower fuel consumption, and optimal conversion rate of the three-way catalyst (TWC). Water injection is one promising technique, as it significantly reduces the engine knock tendency and avoids fuel enrichment for exhaust temperature mitigation at high power operation. With the focus on reducing the carbon footprint of the automotive sector, another vital topic of research is the investigation of new alternative CO2-neutral fuels or so-called eFuels. Several studies have already shown how these new synthetic fuels can be produced by exploiting renewable energy sources and can significantly reduce engine emissions.

Driven by legislation, economics and increasing societal awareness, engine and vehicle manufacturers are facing increasing pressure to reduce vehicle emissions and deliver improved fuel economy. Significant reductions in carbon dioxide (CO2) emissions will need to be achieved to meet these requirements whilst at the same time satisfying the more stringent forthcoming emissions regulations. This focus on techniques to reduce the tailpipe CO2 is increasing the interest in novel combustion technologies, including dilute combustion in gasoline engines. The pre-chamber based jet ignition concept produces high energy jets of partially combusted species that induce ignition at multiple locations in the main combustion chamber to enable rapid, stable combustion, even with dilute mixtures. The present study focusses on the beneficial synergies of the pre-chamber system with high geometric compression ratio (CR), Miller cycle operation and cooled external exhaust gas recirculation (EGR).

Today’s car manufactures inevitably have to focus on the reduction of fuel consumption while maintaining high performance standards. In this respect, the downsized turbocharged DISI (Direct Injection Spark Ignition) engine represents an appealing solution. However, downsizing is limited because of knocking phenomena occurring at high- and full-load conditions due to autoignition of the unburned mixture ahead the flame front. A common way of reducing knock tendencies is provided by Exhaust Gas Recirculation (EGR). However, EGR modifies the chemical composition of the cylinder charge and recirculated species like nitric oxide (NO) or unburned Hydrocarbons (HC) particularly increase the reactivity of the unburned mixture. In other words, the EGR influences the Octane Number (ON) of the in-cylinder gases.

Engine downsizing is a key approach employed by many vehicle manufacturers to help meet fleet average CO2 emissions targets. With gasoline engines in particular reducing engine swept volume while increasing specific output via technologies such as turbocharging, direct injection (DI) and variable valve timing can significantly reduce frictional and pumping losses in engine operating areas commonly encountered in legislative drive cycles. These engines have increased susceptibility to abnormal combustion phenomena such as knock due to the high brake mean effective pressures which they generate. This ultimately limits fuel efficiency benefits by demanding use of a lower geometric compression ratio and sub-optimal late combustion phasing at the higher specific loads experienced by these engines.

The automobile industry is under intense pressure to reduce carbon dioxide (CO2) emissions of vehicles. There is also increasing pressure to reduce the other tail-pipe emissions from vehicles to combat air pollution. Electric powertrains offer great potential for eliminating tailpipe CO2 and all other tailpipe emissions. However, current battery technology and recharging infrastructure still present limitations for some applications, where a continuous high-power demand is required. Furthermore, not all markets have the infrastructure to support a sizeable electric fleet and until the grid energy generation mix is of a sufficiently low carbon intensity, then significant vehicle life-cycle CO2 savings could not be realized by the Battery Electric Vehicles. This investigation examines the effects of combustion, efficiencies, and emissions of two alcohol fuels that could help to significantly reduce CO2 in both tailpipe and the whole life cycle.

Several models for ignition, combustion and emission formation under diesel engine conditions for multi-dimensional computational fluid dynamics have been proposed in the past. It has been recognized that the use of a reasonably detailed chemistry model improves the combustion and emission prediction especially under low temperature and high exhaust gas recirculation conditions. The coupling of the combustion chemistry and the turbulent flow can be achieved with different assumptions. In this paper we investigate a selection of n-heptane spray experiments published by the Engine Combustion Network (ECN spray H) with three different combustion models: well-stirred reactor model, transient interactive flamelet model and progress variable based conditional moment closure. All models cater for the use of detailed chemistry, while the turbulence-chemistry interaction modeling and the ability to consider local effects differ.

Stringent exhaust emission limits and new vehicle test cycles require sophisticated operating strategies for future diesel engines. Therefore, a methodology for predictive combustion simulation, focused on multiple injection operating points is proposed in this paper. The model is designated for engine performance map simulations, to improve prediction of NOx, CO and HC emissions. The combustion process is calculated using a zero dimensional direct injection stochastic reactor model based on a probability density function approach. Further, the formation of exhaust emissions is described using a detailed reaction mechanism for n-heptane, which involves 56 Species and 206 reactions. The model includes the interaction between turbulence and chemistry effects by using a variable mixing time profile. Thus, one is able to capture the effects of mixture inhomogeneities on NOx, CO and HC emission formation.

A novel 0-D Probability Density Function (PDF) based approach for the modelling of Diesel combustion using tabulated chemistry is presented. The Direct Injection Stochastic Reactor Model (DI-SRM) by Pasternak et al. has been extended with a progress variable based framework allowing the use of a pre-calculated auto-ignition table. Auto-ignition is tabulated through adiabatic constant pressure reactor calculations. The tabulated chemistry based implementation has been assessed against the previously presented DI-SRM version by Pasternak et al. where chemical reactions are solved online. The chemical mechanism used in this work for both, online chemistry run and table generation, is an extended version of the scheme presented by Nawdial et al. The main fuel species are n-decane, α-methylnaphthalene and methyl-decanoate giving a size of 463 species and 7600 reactions.

The work examined the practicality of converting a modern production 6 cylinder 7.7 litre heavy-duty diesel engine for flex dual-fuel operation with ammonia as the main fuel. A small amount of diesel fuel (pilot) was used as an ignition source. Ammonia was injected into the intake ports during the intake stroke, while the original direct fuel injection equipment was retained and used for pilot diesel injection. A bespoke engine control unit was used to control the injection of both fuels and all other engine parameters. The aim was to provide a cost-effective retrofitting technology for existing heavy-duty engines, to enable eco-friendly operation with minimal carbon emissions. The tests were carried out at a baseline speed of 600 rpm for the load range of the engine (10-90%), with minimum pilot diesel quantity and as high as 90% substitution ratio of ammonia for diesel fuel.

Partially Premixed Combustion (PPC) engines have demonstrated a potential for high efficiency and low emissions operation. To be able to study the combustion in detail but also to perform parametric studies on the potential of the PPC concept a one dimensional (1D) engine simulation tool was used with 1; a prescribed burn rate 2; predictive combustion tool with reduced chemical model and 3; predictive combustion tool with detailed chemical models. Results indicate that fast executing reduced chemistry work reasonably well in predicting PPC performance and that n-decane is possibly a suitable diesel substitute in PPC modeling while n-heptane is not.

This paper presents results from an experimental programme researching the in-cylinder conditions necessary to obtain homogenous CAI (or HCCI) combustion in a 4-stroke engine. The fuels under investigation include three blends of Unleaded Gasoline, a 95 RON Primary Reference Fuel, Methanol, and Ethanol. This work concentrates on establishing the CAI operating range with regard to Air/Fuel ratio and Exhaust Gas Re-circulation and their effect on the ignition timing, combustion rate and variability, Indicated thermal efficiency, and engine-out emissions such as NOx. Detailed maps are presented, defining how each of the measured variables changes over the entire CAI region. Results indicate that the alcohols have significantly higher tolerance to dilution than the hydrocarbon fuels tested. Also, variations in Gasoline blend have little effect on any of the combustion parameters measured.

The application of controlled auto-ignition (CAI) combustion in gasoline direct injection (GDI) engines is becoming of more interest due to its great potential of reducing both NOx emissions and fuel consumption. Injection timing has been known as an important parameter to control CAI combustion process. In this paper, the effect of injection timing on mixture and CAI combustion is investigated in a single-cylinder GDI engine with an air-assisted injector. The liquid and vapour phases of fuel spray were measured using planar laser induced exciplex fluorescence (PLIEF) technique. The result shows that early injection led to homogeneous mixture but late injection resulted in serious stratification at the end of compression. CAI combustion in this study was realized by using short-duration camshafts and early closure of the exhaust valves. During tests, the engine speed was varied from 1200rpm to 2400rpm and A/F ratio from stoichiometric to lean limit.

Significant reductions in vehicle carbon dioxide (CO2) emissions are required to meet fleet targets and this is increasing the interest in new combustion concepts for internal combustion engines. There is also an increased focus on the use of renewable fuels to reduce environmental impact. This study focusses on the use of methanol as an internal combustion engine fuel. Methanol is a liquid fuel that is readily produced from waste bio-matter, as well as synthetically using renewable energy, and is proposed as a primary energy vector in hard-to-decarbonise sectors, such as Marine, but could be equally applicable to road transportation. In this study, the MAHLE Di3 engine, which is a highly boosted 3-cylinder gasoline direct injection engine capable of operating at over 30 bar BMEP, has been modified to include MAHLE Jet Ignition technology, in both passive and active configurations, as well as utilising a very high compression ratio to maximise thermal efficiency.

Combustion characteristics of neat 2-methylfuran (MF), 10% and 20% volumetric fraction 2-methylfuran gasoline blends were experimentally investigated in a single cylinder spark ignition engine, and the results were benchmarked against that of the research on octane number 97 neat gasoline. The investigation focused on the performance of cyclic variation of MF and its blends, and the effects of spark ignition timing, compression ratio, and exhaust gas recirculation (EGR) were studied. Experiments were conducted at the engine speed of 1500 rpm, and loads between 7 and 11 bar indicated mean effective pressure (IMEP) with using stoichiometric air-fuel ratio mixture. Index of the coefficient of variation of IMEP (COVIMEP) was used to evaluate the combustion stability of the tested fuels. The results show that neat MF and MF gasoline blended fuels have superior combustion stability compared with gasoline.