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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.

Homogeneous Charge Compression Ignition (HCCI) combustion is a process dominated by chemical kinetics of the fuel-air mixture. The hottest part of the mixture ignites first, and compresses the rest of the charge, which then ignites after a short time lag. Crevices and boundary layers generally remain too cold to react, and result in substantial hydrocarbon and carbon monoxide emissions. Turbulence has little effect on HCCI combustion, and may be most important as a factor in determining temperature gradients and boundary layer thickness inside the cylinder. The importance of thermal gradients inside the cylinder makes it necessary to use an integrated fluid mechanics-chemical kinetics code for accurate predictions of HCCI combustion. However, the use of a fluid mechanics code with detailed chemical kinetics is too computationally intensive for today's computers.

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.

A previously presented robust and fast diagnostic NOx model was modified into a predictive model. This was done by using simple yet physically-based models for fuel injection, ignition delay, premixed heat release rate and diffusion combustion heat release rate. The model can be used both for traditional high temperature combustion and for high-EGR low temperature combustion. It was possible to maintain a high accuracy and calculation speed of the NOx model itself. The root mean square of the relative model error is 16 % and the calculation speed is around one second on a PC. Combustion characteristics such as ignition delay, CA50 and the general shape of the heat release rate are well predicted by the combustion model. The model is aimed at real time NOx calculation and optimization in a vehicle on the road.

In this paper a fast NOx model is presented which can be used for engine optimization, aftertreatment control or virtual mapping. A cylinder pressure trace is required as input data. High calculation speed is obtained by using table interpolation to calculate equilibrium temperatures and species concentrations. Test data from a single-cylinder engine and from a complete six-cylinder engine have been used for calibration and validation of the model. The model produces results of good agreement with emission measurements using approximately 50 combustion product zones and a calculation time of one second per engine cycle. Different compression ratios, EGR rates, injection timing, inlet pressures etc. were used in the validation tests.

The emission control in heavy-duty vehicles today is based on predefined injection strategies and after-treatment systems such as SCR (selective catalytic reduction) and DPF (diesel particulate filter). State-of-the-art engine control is presently based on cycle-to-cycle resolution. The introduction of the crank angle resolved pressure measurement, from a piezo-based pressure sensor, enables the possibility to control the fuel injection based on combustion feedback while the combustion is occurring. In this paper a study is presented on the possibility to control NOx (nitrogen oxides) formation with a crank angle resolved NOx estimator as feedback. The estimator and the injection control are implemented on an FPGA (Field-Programmable Gate Array) to manage the inherent time constraints. The FPGA is integrated with the rest of the engine control system for injection control and measurement.

Stringent emission regulations and the anticipated climate change call for a paradigm shift in the design of the conventional internal combustion engines. One way to combat this problem is oxy-fuel combustion in which the combustion products are mainly water vapor and carbon dioxide. Water vapor can be easily separated by condensation and carbon dioxide is then easily captured and stored. However, many technical challenges are associated with this mode of combustion. There are many challenges facing oxy-fuel combustion before it find its way to commercial production especially for internal combustion engines. One such challenge is the relatively high temperature of the oxy-fuel combustion. A solution to this problem is the recirculation of the generated CO2 to moderate the in-cylinder temperature. Therefore, careful study of the effect of recirculating the CO2 back to combustion chamber is needed before the implementation of such a concept.

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.

A Scania 13 1 engine modified for single cylinder operations was run using nine fuels in the boiling point range of gasoline, but very different octane number, together with PRF20 and MK1-diesel. The eleven fuels were tested in a load sweep between 5 and 26 bar gross IMEP at 1250 rpm and also at idle (2.5 bar IMEP, 600 rpm). The boost level was proportional to the load while the inlet temperature was held constant at 303 K. For each fuel the load sweep was terminated if the ignitibility limit was reached. A lower load limit of 15 and 10 bar gross IMEP was found with fuels having an octane number range of 93-100 and 80-89 respectively, while fuels with an octane number below 70 were able to run through the whole load range including idle. A careful selection of boost pressure and EGR in the previously specified load range allowed achieving a gross indicated efficiency between 52 and 55% while NOx ranged between 0.1 and 0.5 g/kWh.

Partially Premixed Combustion (PPC) is a promising combustion concept with high thermodynamic efficiency and low emission level, and also with minimal modification of standard engine hardware. To use PPC in a production oriented engine, the optimal intake charge conditions for PPC should be included in the analysis. The experiments in this paper investigated and confirmed that the optimal intake conditions of net indicated efficiency for PPC are EGR between 50% and 55% as possible and the lambda close to 1.4. Heat-transfer energy and exhaust gas waste-energy contribute to the majority of the energy loss in the engine. The low EGR region has high heat-transfer and low exhaust gas enthalpy-waste, while the high EGR region has low heat-transfer and high exhaust gas waste-enthalpy. The optimal EGR condition is around 50% where the smallest energy loss is found as a trade-off between heat transfer and exhaust-gas enthalpy-waste.

In the last couple of decades, countries have enacted new laws concerning environmental pollution caused by heavy-duty commercial and passenger vehicles. This is done mainly in an effort to reduce smog and health impacts caused by the different pollutions. One of the legislated pollutions, among a wide range of regulated pollutions, is nitrogen oxides (commonly abbreviated as NOx). The SCR (Selective Catalytic Reduction) was introduced in the automotive industry to reduce NOx emissions leaving the vehicle. The basic idea is to inject a urea solution (AdBlue™) in the exhaust gas before the gas enters the catalyst. The optimal working temperature for the catalyst is somewhere in the range of 300 to 400 °C. For the reactions to occur without a catalyst, the gas temperature has to be at least 800 °C. These temperatures only occur in the engine cylinder itself, during and after the combustion.

The soot distribution as function of ambient O₂ mole fraction in a heavy-duty diesel engine was investigated at low load (6 bar IMEP) with laser-induced incandescence (LII) and natural luminosity. A Multi-YAG laser system was utilized to create time-resolved LII using 8 laser pulses with a spacing of one CAD with detection on an 8-chip framing camera. It is well known that the engine-out smoke level increases with decreasing oxygen fraction up to a certain level where it starts to decrease again. For the studied case the peak occurred at an O₂ fraction of 11.4%. When the oxygen fraction was decreased successively from 21% to 9%, the initial soot formation moved downstream in the jet. At the lower oxygen fractions, below 12%, no soot was formed until after the wall interaction. At oxygen fractions below 11% the first evidence of soot is in the recirculation zone between two adjacent jets.

When applying high amount of EGR (exhaust gas recirculation) in Partially Premixed Combustion (PPC) using diesel fuel, an increase in soot emission is observed as a penalty. To better understand how EGR affects soot particles in the cylinder, a fast gas sampling technique was used to draw gas samples directly out of the combustion chamber in a Scania D13 heavy duty diesel engine. The samples were characterized on-line using a scanning mobility particle sizer for soot size distributions and an aethalometer for black carbon (soot) mass concentrations. Three EGR rates, 0%, 56% and 64% were applied in the study. It was found that EGR reduces both the soot formation rate and the soot oxidation rate, due to lower flame temperature and a lower availability of oxidizing agents. With higher EGR rates, the peak soot mass concentration decreased. However, the oxidation rate was reduced even more.

In-cylinder visualization, combustion stratification, and engine-out particulate matter (PM) emissions were investigated in an optical engine fueled with Haltermann straight-run naphtha fuel and corresponding surrogate fuel. The combustion mode was transited from homogeneous charge compression ignition (HCCI) to conventional compression ignition (CI) via partially premixed combustion (PPC). Single injection strategy with the change of start of injection (SOI) from early to late injections was employed. The high-speed color camera was used to capture the in-cylinder combustion images. The combustion stratification was analyzed based on the natural luminosity of the combustion images. The regulated emission of unburned hydrocarbon (UHC), carbon monoxide (CO) and nitrogen oxides (NOX) were measured to evaluate the combustion efficiency together with the in-cylinder rate of heat release.

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.

This article deals with study of ionization current sensing technique's signal characteristics while operating with pre-chamber spark plug to achieve plasma jet ignition in a 6 cylinder 9 liter turbo-charged natural gas engine under EGR and excess air dilution. Unlike the signal with conventional spark plug which can be divided into distinct chemical and thermal ionization peaks, the signal with pre-chamber spark plug shows a much larger first peak and a negligible second peak thereafter. Many studies in past have found the time of second peak coinciding with the time of maximum cylinder pressure and this correlation has been used as an input to combustion control systems but the absence of second peak makes application of this concept difficult with pre-chamber spark plug.

The blending behavior of ethanol in five different hydrocarbon base fuels with octane numbers of approximately 70 and 84 was examined under Spark-Ignited (SI) and Homogeneous Charge Compression Ignited (HCCI) operating conditions. The Blending octane number (BON) was used to characterize the blending behavior on both a volume and molar basis. Previous studies have shown that the blending behavior of ethanol generally follows several well-established rules. In particular, non-linear blending effects are generally observed on a volume basis (i.e. BON > RON or MON of pure ethanol; 108 and 89, respectively), while linear blending effects are generally observed on a molar basis (i.e. BON = RON or MON of pure ethanol). This work firstly demonstrates that the non-linear volumetric blending effects traditionally observed under SI operating conditions are also observed under HCCI operating conditions.