Automotive Science and Engineering

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In this study it has been tried, to compare results and convergence rate of sensitivity analysis and conjugate gradient algorithms to reduce fuel consumption and increasing engine performance by optimizing the timing of opening and closing valves in XU7/L3 engine. In this study, considering the strength and accuracy of simulation GT-POWER software in researches on the internal combustion engine, this software has been used. In this paper initially all components of engine have been modeled in GT-POWER. Then considering the experimental result, results confirmed the accuracy of the model. After model verification, GT-POWER model with MATLAB-SIMULINK are coupled each other, to control the inputs and the outputs by sensitivity analysis and conjugate gradient algorithms. Then the results compared with experimental results of initial engine too. The results indicated that optimal valve timing significantly reduced brake specific fuel consumption and when is used variable valve system for opening and closing angle of intake and exhaust valves, the mean improvement percentage in brake specific fuel consumption from sensitivity analysis is nearly 5.87 and from conjugate gradient is about 6.69. too, for example with increasing engine speed late closing intake valve causes optimized brake specific fuel consumption and from 3500rpm this trend stops and in 4000rpm and 4500rpm early closing of intake valve results in more optimized brake specific fuel consumption. Then up to 6000rpm again late closing of valve would be favorable. Also results indicated that convergence rate of conjugate gradient algorithm to reaching the optimal point is more than sensitivity analysis algorithm.

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In this paper, a numerical study is performed to provide the combustion and emission characteristics resulting from fuel-reactivity controlled compression ignition (RCCI) combustion mode in a heavy-duty, single-cylinder diesel engine with gasoline and diesel fuels. In RCCI strategy in-cylinder fuel blending is used to develop fuel reactivity gradients in the combustion chamber that result in a broad combustion event and reduced pressure rise rates (PRR). RCCI has been demonstrated to yield low NOx and soot with high thermal efficiency in light and heavy-duty engines. KIVA-CHEMKIN code with a reduced primary reference fuel (PRF) mechanism are implemented to study injection timings of high reactivity fuel (i.e., diesel) and low reactivity fuel percentages (i.e., gasoline) at a constant engine speed of 1300 rpm and medium load of 9 bar indicated mean effective pressure (IMEP). Significant reduction in nitrogen oxide (NOx), while 49% gross indicated efficiency (GIE) were achieved successfully through the RCCI combustion mode. The parametric study of the RCCI combustion mode revealed that the peak cylinder pressure rise rate (PPRR) of the RCCI combustion mode could be controlled by several physical parameters – PRF number, and start of injection (SOI) timing of directly injected fuel.

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Nowadays, due to increasing the complexity of IC engines, calibration task becomes more severe and the need to use surrogate models for investigating of the engine behavior arises. Accordingly, many black box modeling approaches have been used in this context among which network based models are of the most powerful approaches thanks to their flexible structures. In this paper four network based modeling methods are used and compared to model the behavior of an IC engine: neural networks model (NN), group method of data handling model (GMDH), a hybrid NN and GMDH model (NN-GMDH), and a GMDH model whose structure is determined by genetic algorithm (Genetic-GMDH). The inputs are engine speed, throttle angle, and intake valve opening and closing timing, and the output is the engine brake torque. Results show that NN has the best prediction capability and Genetic-GMDH model has the most flexible and simplest structure and relatively good prediction ability.

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In this paper we aim to develop a predictive combustion model for a turbocharged engine in GT-Power software to better simulate engine characteristics and study its behavior under variety of conditions. Experimental data from combustion was initially being used for modelling combustion in software and these data were used for model calibration and result validation. EF7-TC engine was chosen for this research which is the first turbocharged engine designed and developed by IKCO and IPCO in Iran. After analyzing necessary theories for predictive combustion model and required steps for calibration of CombSITurb model in software, one final set of multipliers were calculated based on different sets derived for each engine speed and engine operation was simulated with this combustion model. In addition to improved predictability of engine model, comparing results of predictive model with non-predictive model shows better accuracy especially at lower engine speeds and less tolerance of results for each engine speed.

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In this research, a high-temperature Rankin cycle (HTRC) with two-stage pumping is presented and investigated. In this cycle, two different pressures and mass flow rates in the HTRC result in two advantages. First, the possibility of direct recovery from the engine block by working fluid of water, which is a low quality waste heat source, is created in a HTRC. Secondly, by doing this, the mean effective temperature of heat addition increases, and hence the efficiency of the Rankin cycle also improves.
The proposed cycle was examined with the thermodynamic model. The results showed that in a HTRC with a two-stage pumping with an increase of 8% in the mean effective temperature of heat addition, the cycle efficiency is slightly improved. Although the operational work obtained from the waste heat recovery from the engine cooling system was insignificant, the effect of the innovation on the recovery from the exhaust was significant. The innovation seems not economical for this low produced energy. However, it should be said that although the effect of the innovation on the increase of the recovery cycle efficiency is low, the changes that must be implemented in the system are also low. 

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In this study, modeling of a fuel jet which has been injected by high pressure into a low-pressure tank are investigated. Due to the initial conditions and the geometry of this case and similar cases (like CNG injectors in internal combustion engines (ICE)), the barrel shocks and Mach disk are observed. Hence a turbulence and transient flow will be expected with lots of shocks and waves. According to the increasing usage of this type of injectors in ICE, more studies should be conducted to find the most accurate and beneficial models for modeling this phenomenon.

In order to find an accurate and beneficial turbulence model ,in this study, three Reynolds-averaged Navier–Stokes (RANS) turbulence models (SST k-ω, RNG and standard k ) and large eddy simulation (LES) turbulence model were compared by the fuel jet characteristics in three regions (outlet of the nozzle, at Mach disk and at the downstream of the flow). Although the LES model needs more time for each test, the results are more reliable and accurate. On the other hand, RANS turbulence models have lots of errors (more than 10 percent) especially for predicting the characteristics of fuel jet at Mach disk.

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Intake and exhaust manifolds are among the most important parts in engine in which pressure loss phenomena has direct impact on with changing volumetric efficiency. In typical 1D simulation codes, the quantity of pressure loss is proportional to the fluid’s mean velocity by Pressure Loss Coefficient (K_p) value. This important coefficient which has substantial rule in engine simulation is usually determined using constant available values, extracted from complicated experiments (like Miller’s tests) in a specified situation. But these values are credible only in situations according to those tests. Coupling 3D simulations with 1D codes is a common method to gain accurate values of these coefficients but this deals with drastic high simulation costs. To address this problem, a more efficient way is replacing an algebraic relation, extracted from 3D calculations, instead of a constant value in 1D code. It’s obvious that in order to reach accurate coefficients in arbitrary conditions (geometric and flow specifications) determining the best numerical method is mandatory.  In present research, after investigating all 3D simulation aspects, six different selected numerical solutions have been implemented on four different bends in ANSYS Fluent.Results have been validated by comparing loss coefficient values of incompressible fluid (water) with Miller loss coefficient values and method with the most accurate and stable results has been discovered. It was found that all these methods are suitable in general (with less than 5% error in coefficient values) but solutions with structured grid and SST k-ω turbulence modeling represented better stability and accuracy.

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Surface texturing modifications improve the tribological performance parameters. In parallel slider bearings with a micro-grooved textured surface, the effects of the Reynolds number and the texture aspect ratio at constant texture density have been studied; however, the texture density variation's effects on the tribological performance have not been investigated yet. The focus of this study is on the texture density variation in micro-grooved parallel slider bearings. The numerical analysis approach was utilized to perform a more in-depth understanding of texture density variation on the two-dimensional pressure distribution, skin friction coefficient, and recirculation zones in micro-grooves and the objective of flow functions such as load-carrying capacity and friction coefficient. In order to validate using the current CFD model for analyzing hydrodynamic bearings, a comparison with the published theoretical paper results was presented. The results were in good agreement with the published theoretical predictions. In a variety of aspect ratios, the texture densities led to an upgrade tribological performance. Results showed remarkable improvements in frictional response with texture density, and an optimal texture density exists. Finally, it was observed that the optimal micro-grooves texture density depends on the texture aspect ratio, while it is independent of the sliding velocity.