Effects of Spark Ignition Engine Operating Parameters on Its Cyclic Variation ——Modeling and Simulation

An engine cyclic variation model has been built by using the residual gas temperature for the n th cycle as the input of the model, through constant pressure intake process, adiabatic compression process, constant volume combustion process, adiabatic expansion process, adiabatic blow down process and constant pressure exhaust process to approximate the thermodynamic processes in the cylinder, finally the residual gas temperature for the ( n+1) th cycle can be estimated. Because of the adding of engine operating parameters such as engine speed, spark advance, equivalence ratio, intake air pressure, intake air temperature to the model, effects of these parameters on cyclic variation can be estimated quantitatively. Since residual gas temperature fluctuation between cycles reflects the circumstances of engine cyclic variation, parameters to which residual gas temperature is sensitive are most likely used as the means to control cyclic variation. Model simulation shows that for the nearly stiochiometric mixture, cyclic variation is not obvious or even quite stable, but for the lean mixture, under the circumstances of partial load and larger spark advances, engine cyclic variations occur chaotically or with bifurcation.

Intelligent prediction on air intake flow of spark ignition engine by a chaos radial basis function neural network

To ensure the control of the precision of air-fuel ratio(AFR)of port fuel injection(PFI)spark ignition(SI)engines,a chaos radial basis function(RBF)neural network is used to predict the air intake flow of the engine.The data of air intake flow is proved to be multidimensionally nonlinear and chaotic.The RBF neural network is used to train the reconstructed phase space of the data.The chaos algorithm is employed to optimize the weights of output layer connection and the radial basis center of Gaussian function in hidden layer.The simulation results obtained from Matlab/Simulink illustrate that the model has higher accuracy compared to the conventional RBF model.The mean absolute error and the mean relative error of the chaos RBF model can reach 0.0017 and 0.48,respectively.

Correlation of Performance, Exhaust Gas Temperature and Speed of a Spark Ignition Engine Using Kiva4

The objective of this study was to investigate performance characteristics of a spark ignition engine, particularly, the correlation between performance, exhaust gas temperature and speed, using Kiva4. Test data to validate kiva4 simulation results were conducted on a 3-cylinder, four-stroke Volkswagen (VW) Polo 6 TSI 1.2 gasoline engine. Three different tests were, therefore, carried out. In one set, variations in exhaust gas temperature were studied by varying the engine load, while keeping the engine speed constant. In another test, exhaust gas temperature variations were studied by keeping the engine at idling whilst varying the speeds. A third test involved studying variations in exhaust gas temperature under a constant load with variable engine speeds. To study variations in exhaust gas temperatures under test conditions, a basic grid/mesh generator, K3PREP, was employed to write an itape17 file comprising of a 45° asymmetrical mesh. This was based on the symmetry of the combustion chamber of the engine used in carrying out experimental tests. Simulations were therefore performed based on the input parameters established in the conducted tests. Simulations with the kiva4 code showed a significant predictability of the performance characteristics of the engine. This was evident in the appreciable agreement obtained in the simulation results when compared with the test data, under the considered test conditions. A percentage error, between experimental results and results from simulations with the kiva4 code of only between 2% to 3% was observed.

Influence of Combustion Chamber Design Parameters and Intake Environments on Spark Ignition Engine Performance and Exhaust Gas Emission

In the present paper, the effect of the combustion chamber design parameters on the improvement of combustion efficiency (the heat generated inside the combustion chamber) and the enhancement in the pollution rates (heat emissions) from a four-stroke, spark-ignition engine has been studied experimentally and theoretically. Two different programs, Gaseq and Ansys, were used to simulate the effect of the combustion chamber shape, turbulent kinetic energy, intake temperature, intake pressure, parity ratio, compression ratio, and engine speed on reducing specific fuel consumption in the engine, reducing carbon dioxide emissions, and increasing overall engine efficiency. The results showed increasing the intake temperature increased the amount of heat produced in the combustion chamber. This leads to increases in the overall efficiency of the engine, but leads to increasing the carbon dioxide and nitrogen oxide emissions. Increasing the intake pressure has a positive effect on the combustion temperature and pressure, but it has a negative effect on carbon dioxide and nitrogen oxides. Raising the pressure ratio improved the overall efficiency of the engine by increasing the combustion heat, but increasing specific fuel consumption and emissions. Also, increasing the engine speed above the permissible limit has an adverse effect on the spraying speed due to the piston speed being higher than the flame speed, which leads to a reduction in the engine brake torque. An increase in the compression ratio leads to higher fluid pressure and output capacity, but combustion methods occur. An increase in the kinetic energy of the turbulence leads to good combustion. A bowl in a piston has the highest rate of rotation and rotation compared to flat and hemispherical pistons. That is, the design of the cylinder head of this type leads to an improvement in the combustion efficiency and thus the efficiency of the engine.

Development of artificial neural network to predict the performance of spark ignition engine fuelled with waste pomegranate ethanol blends

In this study,an artificial neural network(ANN)is developed to predict the performance of a spark-ignition engine using waste pomegranate ethanol blends.A series of experiments on a single-cylinder,four-stroke spark-ignition engine yielded the data needed for neural network training and validation.70 percent of the experimental data was used to train the network using the feed-forward back propagation(FFBP)algorithm.The developed network model’s performance was evaluated by contrasting its output with experimental results.Input parameters included engine speed,ethanol blends,and output parameters included indicated and brake power,thermal,volumetric,and mechanical efficiencies.Training and testing data had regression coefficients that were almost identical to one.The research revealed that the ANN model can be a better option for predicting engine performance with a higher level of accuracy.

Measuring Fuel Stratification in Cylinder of a Spark Ignition Engine by a Two-Tracer PLIF System

A two-tracer PLIF system was developed to measure fuel stratification in cylinder of a spark ignition engine which is achieved by producing a strong tumbling flow and introducing two fuels through two separate intake ports.Two tracers,3-pentanone and N,N-dimethylaniline(DMA),were doped in two fuels,hexane and iso-octane,respectively.A spectroscopic test result showed that when subject to irradiation by a XeCl Excimer laser(308 nm),3-pentanone and DMA emit fluorescence within different wavelength regions.Their fluorescence can be separated by two band-pass optical filters and recorded into a single intensified CCD camera through a specially designed image doubling system.The advantage of the measurement method is that both fuel distributions in cylinder can be visualized by one shot.Measurement results showed that two fuels were well stratified in the cylinder.

Evaporate prediction and compensation of intake port wall-wetting fuel film for spark ignition engines fueled with ethanol-gasoline blends

The fuel dynamic transfer process,including fuel injection,fuel film deposition and evaporation in the intake port,was analyzed for spark ignition(SI) engines with port fuel injection(PFI).The influence of wall-wetting fuel film,especially its evaporation rate,upon the air-fuel ratio of in-cylinder mixtures was also discussed.According to the similarity principle,Fick's law,the ideal gas equation and the Gilliland correlation,an evaporate prediction model of wall-wetting fuel film was set up and an evaporate prediction based dynamic fuel film compensator was designed.Through engine cold start tests,the wall-wetting temperature,which is the key input of the fuel film evaporate prediction model,was also modeled and predicted.Combined with the experimental data of the evaporation characteristics of ethanol-gasoline blends and engine calibration tests,all the parameters of the wall-wetting fuel film evaporate prediction model used in the fuel film compensator were identified.Square-wave disturbance tests of fuel injection showed that with the help of the fuel film compensator the response of the in-cylinder air-fuel ratio was significantly improved and the real air-fuel ratio always closely matched the expected ratio.The fuel film compensator was then integrated into the final air-fuel ratio controller,and the engine tests showed that the air-fuel ratio control error was less than 2% in steady-state conditions,and less than 4% in transient conditions.The fuel film compensator also showed good adaptability to different ethanol-gasoline blends.

Evaluation and Control of Cyclic Variation in Spark Ignited Engines by a Thermodynamic Model

An evaluation method of engine cyclic variation is proposed based on fuzzy mathematics concept. The degree of engine cyclic variation is divided into 4 levels: stable, slight variation, moderate variation and serious variation based on the statistic standard deviation of residual gas temperatures within the specified simulation cycles and the function of cyclic variation is also inducted for the cyclic variation control. Because the degree of engine cyclic variation can be estimated qualitatively, the effective control means can be applied to appease the undesired cyclic variation. Simulation result shows that for a very serious cyclic variation through the proper adjustment of the spark angle and the cyclic variation will disappear.

Semi-empirical modeling of volumetric efficiency in engines equipped with variable valve timing system

Volumetric efficiency and air charge estimation is one of the most demanding tasks in control of today's internal combustion engines.Specifically,using three-way catalytic converter involves strict control of the air/fuel ratio around the stoichiometric point and hence requires an accurate model for air charge estimation.However,high degrees of complexity and nonlinearity of the gas flow in the internal combustion engine make air charge estimation a challenging task.This is more obvious in engines with variable valve timing systems in which gas flow is more complex and depends on more functional variables.This results in models that are either quite empirical(such as look-up tables),not having interpretability and extrapolation capability,or physically based models which are not appropriate for onboard applications.Solving these problems,a novel semi-empirical model was proposed in this work which only needed engine speed,load,and valves timings for volumetric efficiency prediction.The accuracy and generalizability of the model is shown by its test on numerical and experimental data from three distinct engines.Normalized test errors are 0.0316,0.0152 and 0.24 for the three engines,respectively.Also the performance and complexity of the model were compared with neural networks as typical black box models.While the complexity of the model is less than half of the complexity of neural networks,and its computational cost is approximately 0.12 of that of neural networks and its prediction capability in the considered case studies is usually more.These results show the superiority of the proposed model over conventional black box models such as neural networks in terms of accuracy,generalizability and computational cost.

The Advantages of Non-Thermal Plasma for Detonation Initiation Compared with Spark Plug

In this paper,the characteristics of detonation combustion ignited by AC-driven non-thermal plasma and spark plug in air/acetylene mixture have been compared in a doubletube experiment system.The two tubes had the same structure,and their closed ends were installed with a plasma generator and a spark plug,respectively.The propagation characteristics of the flame were measured by pressure sensors and ion probes.The experiment results show that,compared with a spark plug,the non-thermal plasma obviously broadened the range of equivalence ratio when the detonation wave could develop successfully,it also heightened the pressure value of detonation wave.Meanwhile,the detonation wave development time and the entire flame propagation time were reduced by half.All of these advantages benefited from the larger ignition volume when a non-thermal plasma was applied.

Thermodynamic Analysis of Turbo-Charged Power Generating System

Turbochargers have been known in compression ignition engines for power generation.Recent trends in power generation through gas cycles have recorded successes via turbochargers application in spark ignition engines as well.When power cycles are turbocharged,there is a general expectation of a higher power and performance output from the cycle as compared to when they are naturally aspirated.This research was conducted to estimate the thermodynamic properties of a spark ignition engine power generating system when it is both naturally aspirated and when the same system is turbocharged to 2.5 times the amount of air in natural aspiration.Octane fuel was employed for petrol approximation during this study.The system process was broken down into stages of charging between natural aspiration and turbocharged;thus MATLAB program was applied to model the system for the case of natural aspiration and turbocharging with no increase in fuel supply.The results were used for both analyses and comparison which showed that the system generates slightly more power with turbocharging at 0%increase in fuel consumption.The natural aspiration achieved values are 2.8232 kJ/mol and 55.26%for output and efficiency respectively,while the turbocharged engine produced optimal values of 2.8833 kJ/mol and 56.51%for output and efficiency.The air fuel ratio by mole for the turbocharged engine was 145.18:1,which shows a greater fuel economy of 59%as compared to the 59.5:1 A/F(air/fuel)ratio of the naturally aspirated engine.

SI Engine Fueled with Gasoline, CNG and CNG-HHO Blend: Comparative Evaluation of Performance, Emission and Lubrication Oil Deterioration

Hydroxy gas (HHO) is one of the potential alternative fuels for spark ignition (SI) engine,notably due to simultaneous increase in engine performance and reduction in exhaust emissions.However,impact of HHO gas on lubrication oil for longer periods of engine operation has not yet been studied.Current study focuses on investigation of the effect of gasoline,CNG and CNG-HHO blend on lubrication oil deterioration along with engine performance and emissions in SI engine.HHO unit produces HHO gas at 4.72 L/min by using 6 g/L of KOH in the aqueous solution.CNG was supplied to the test engine at a pressure of 0.11 MPa using an electronically controlled solenoid valve.Engine tests were carried out at different speeds at 80%open throttle condition and various performance parameters such as brake power (BP),brake specific fuel consumption(BSFC),brake thermal efficiency (BTE),exhaust gas temperature and exhaust emissions (HC,CO_(2),CO and NO_(x))were investigated.In addition,various lubrication oil samples were extracted over 120 h of engine running while topping for drain out volume and samples were analyzed as per ASTM standards.CNG-HHO blend exhibited better performance i.e.,15.4%increase in average BP in comparison to CNG,however,15.1%decrease was observed when compared to gasoline.CNG-HHO outperformed gasoline and CNG in the case of HC,CO_(2),CO and brake specific fuel consumption (31.1%decrease in comparison to gasoline).On the other hand,CNG-HHO produced higher average NO_(x) (12.9%) when compared to CNG only.Furthermore,lubrication oil condition(kinematic viscosity,water contents,flash point and total base number (TBN)),wear debris (Iron (Fe),Aluminum(Al),Copper (Cu),Chromium (Cr)) and additives depletion (Zinc (Zn),Calcium (Ca)) presented a significant degradation in the case of CNG-HHO blend as compared to gasoline and CNG.Lubrication oil analyses illustrated 19.6%,12.8%and 14.2%decrease in average viscosity,flash point and TBN for CNG-HHO blend respectively.However,average water contents,Fe,Al and Cu mass concentration appeared 2.7%,25×10^(-6),19×10^(-6),and 22×10^(-6) in lubrication oil for CNG-HHO respectively.

Simple adaptive air-fuel ratio control of a port injection SI engine with a cylinder pressure sensor

The problem of air-fuel ratio(AFR) control of the port injection spark ignition(SI) engine is still of considerable importance because of stringent demands on emission control. In this paper, the static AFR calculation model based on in-cylinder pressure data and on the adaptive AFR control strategy is presented. The model utilises the intake manifold pressure, engine speed, total heat release, and the rapid burn angle, as input variables for the AFR computation. The combustion parameters, total heat release,and rapid burn angle, are calculated from in-cylinder pressure data. This proposed AFR model can be applied to the virtual lambda sensor for the feedback control system. In practical applications, simple adaptive control(SAC) is applied in conjunction with the AFR model for port-injected fuel control. The experimental results show that the proposed model can estimate the AFR, and the accuracy of the estimated value is applicable to the feedback control system. Additionally, the adaptive controller with the AFR model can be applied to regulate the AFR of the port injection SI engine.