Engine Exhaust Gas Temperature Research Articles

A comparative study of combustion, emission, and performance characteristics of rice-bran-, neem-, and cottonseed-oil biodiesels with varying degree of unsaturation

In this study, we compared three different blended (20/80 by vol.) biodiesels of rice bran, neem, and cottonseed oils with varying degree of unsaturation. All three biodiesel blends decreased the brake thermal efficiency and increased the exhaust gas temperature of a single-cylinder diesel engine. They decreased CO, hydrocarbon, and smoke emissions, but increased NOx emissions. The biodiesels provided better combustion characteristics than diesel. Of all the tested biodiesel blends, rice bran oil biodiesel decreased CO and hydrocarbon emissions the most, albeit at the cost of increasing NOx emissions. CO, HC, and smoke emissions decreased with the increase in degree of unsaturation, whereas NOx emissions increased with the increase in degree of unsaturation.

Simulation of Aldehyde Emissions from an Ethanol Fueled Spark Ignition Engine and Comparison with FTIR Measurements

This paper presents a mathematical model that calculates aldehyde emissions in the exhaust of a spark ignition engine fueled with ethanol. The numerical model for aldehyde emissions was developed using FORTRAN software, with the input data obtained from a dedicated engine cycle simulation software, AVL BOOST. The model calculates formaldehyde and acetaldehyde emissions, formed from the partial oxidation of methane, ethane and unburned ethanol. The calculated values were compared with experimental data obtained by Fourier Transform Infrared Spectroscopy (FTIR). The experiments were performed with a mid-size sedan powered by a 1.4-liter spark ignition engine on a chassis dynamometer. In general, the results demonstrate that the concentrations of aldehydes and the source elements increased with engine speed and exhaust gas temperature. A reasonable agreement between simulated and measured values was achieved.

Study And Evaluation of Injection Timing of CIDI Engine Injection Pump Using Alternate Fuel i.e Biodiesel Fuel

In this investigation an experimental study of the effects of FIP injection timing on Specific Fuel Consumption(SFC), Brake Thermal Efficiency(BTE), Engine Exhaust Gas Temperature(EEGT), CO, HC, NOX and Smoke of “Kirloskar- 6R1080TA, 6-CylinderInline, Direct Injection, Turbocharged Intercooled, 191 hp Diesel Engine” has been conducted. Injection Timing retardation method has been utilised to reduce SFC, EEGT, CO, HC, NOX, Smoke and increase BTE of Kirloskar-6R1080TA Diesel Engine. The Kirloskar 6R1080TA engine has been tested for six different injection timings (23°, 21°, 20°, 19°, 18° and 17° CA BTC) at same engine speeds and load conditions. The SFC,EEGT, CO, HC, NOX and Smoke of engine are approximately higher and BTE lower for injection timings at 23°, 21°, 20°, 18° and 17° CA BTC than 19° CA BTC at same speed and load. The results are showing that SFC,EEGT,CO,HC,NOX and Smoke are approximately reduces and BTE increases by reducing injection timing from 23° CA BTC to 19° CA BTC. Optimum FIP injection timing for Kirloskar 6R1080TA engine has been achieved at 19° CA BTC.

Characterization of carbonaceous particulate matter emitted from marine diesel engine

In an effort to aid the Korean ship-building industry to effectively respond to the upcoming environmental regulations, a series of experimental campaigns to characterize carbonaceous Particulate matters (PMs) emitted from a cruising marine ship have been carried out. To this end, the carbonaceous PMs emitted from two-stroke marine-diesel engines burning Bunker B (Low residual fuel oil, LRFO 3%) were sampled on-board at various locations: 1) After the turbo charger (TC), 2) before the economizer (ECO), 3) after the economizer, and 4) in the funnel of the chimney. Sampled carbonaceous PM particles were then analyzed using a High-resolution transmission electron microscopy (HRTEM) and Raman spectroscopy. Results obtained from the analysis of HRTEM images and Raman spectra indicate that carbonaceous PMs are mainly fractionated into Black carbon (BC) and Organic carbon (OC), respectively and the each fraction of sampled carbonaceous PMs varies with engine operation conditions and exhaust gas temperatures at the sampling location. The present work is anticipated to provide a useful set of information for characterizing carbonaceous PMs emitted from marine diesel engines.

Experimental analysis of diesel engine exhaust gas coupled with water desalination for improved potable water production

Exhaust gas temperature of diesel engine is higher compared with a petrol engine and also creates higher pollution in the environment. Exhaust gas recirculation system and many other systems have used for reuse of exhaust gas to improve the performance of diesel engine, but the use of diesel engine for production of potable water production is still unattended by the researchers. The main aim of this research work is to use the waste heat of exhaust gas for potable water production from the low-capacity desalination system integrated with a evaporator and condenser unit. In this work, single pass evaporator and water-cooled condenser used for evaporation and condensation of saline water were designed and fabricated by locally available materials. The experiments were performed on a 10 HP diesel engine with varying the load to get potable water. It has found that 4.2 L/hr of potable water is obtained from the exhaust gas without varying the performance of the engine. Also, it has found that, temperature of saline water is heated more than 70°C in the condenser unit.

ディーゼル機関排出ガス加熱用再生加熱蒸発方式バーナの開発

A lab-scale two-stage light-oil burner has been developed to obtain the fundamental data required for designing burners to heat a diesel particulate filter when exhaust gas temperature of the main engine is low. Regenerative-heating and pre-evaporation premixing combustion were adopted to this burner for downsizing and reducing cost. Two-stage combustion was realized in the burner to reduce the heat-load of the combustion chamber for the first stage combustion. The combustion chamber volume is about 66 mL. Observations of flame-holding condition and temperature measurements of the burner and combustion gas were performed with varying the fuel flow rate and air flow rate. Three types of secondary air nozzle and three secondary air nozzle positions were tested to understand the effect of the secondary nozzle on combustion gas temperature and combustion gas compositions. It was found that the burner in the single-stage combustion mode was able to stabilize a flame in the range of 2 to 14 mL/min in fuel flow rate at adequate equivalence ratio in the range of 1.4 to 1.8. Combustion gas temperature of the burner in the two-stage combustion mode is determined by the total equivalence ration and is independent on the equivalence ratio of the first stage combustion. It is possible to suppress CO and NOx emissions when the burner is operated at 0.8 in the total equivalence ratio.

Thermodynamic analysis of a twin cylinder diesel engine in dual fuel mode with producer gas

There is a need for thermodynamic analysis of the compression ignition (CI) engine to evaluate its energy utilization efficiency, which will locate and quantify the amount of quality energy lost from the engine at different heads. In this paper, the analysis of energy, exergy, maximum combustion temperature and exhaust gas temperature of a CI engine in normal mode using diesel and in dual fuel mode with producer gas is performed. The results indicate that brake thermal efficiency, exergy efficiency and maximum combustion temperature increases with increase in load. At the same time destruction of exergy also increases with engine load. Compared to normal diesel mode, dual fuel mode shows a diminishing performance that may be due to the poor burning qualities of producer gas.

Artificial neural network-based prediction of performance and emission characteristics of CI engine using polanga as a biodiesel

The present work predicts the performance parameters, namely brake specific fuel consumption (BSFC), brake thermal efficiency (BTE), peak pressure, exhaust gas temperature and exhaust emissions of a single cylinder four-stroke diesel engine at different injection timings and engine load using blended mixture of polanga biodiesel by artificial neural network (ANN). The properties of biodiesel produced from polanga were measured based on ASTM standards. Using some of the experimental data for training, an ANN model was developed based on standard back-propagation algorithm for the engine. Multi-layer perception network was used for non-linear mapping between input and output parameters. Different activation functions and several rules were used to assess the percentage error between the desired and the predicted values. It was observed that the developed ANN model can predict the engine performance and exhaust emissions quite well with correlation coefficient (R) 0.99946, 0.99968, 0.99988, 0.99967, 0.99899, 0.99941 and 0.99991 for the BSFC, BTE, peak pressure, exhaust gas temperature, NOx, smoke and unburned hydrocarbon emissions, respectively. The experimental results revealed that the blended fuel provides better engine performance and improved emission characteristics.

Prediction of Ship Main Engine Exhaust Gas Temperature Using AR Model

In order to forecast the malfunctional state of main power plant on ships through predicting the trend of unsteadily changed thermal performance parameters in main power plant system, this paper established AR model for thermal performance parameters using time series analysis method, by which to predict the change trend analysis of thermal performance parameters, and comparing the predicted values and the measured values. The actual application case of predicting a main engine’s exhaust temperature has been validated by using of the AR model, and results showed that: AR model can accurately predict the change trend of smoke temperature, and the prediction precision is higher, the average relative error was 0.25%.

Biogas upgrading for on-board hydrogen production: Reforming process CFD modelling

Hydrogen production through fuel reforming can be used to improve IC (internal combustion) engines combustion characteristics and to lower vehicle emissions. In this study, a computational fluid dynamics (CFD) model based on a detailed kinetic mechanism was developed for exhaust gas reforming of biogas to synthetic gas (H2 and CO). In agreement with experimental data, the reactor's physical and chemical performance was investigated at various O2/CH4 ratios and gas hourly space velocities (GHSV). The numerical results imply that methane reforming reactions are strongly sensitive to O2/CH4 ratio and engine exhaust gas temperature. It was also found that increasing GHSV results in lower hydrogen yield; since dry and steam reforming reactions are relatively slow and are both dependent on the flow residence time. Furthermore, the hot spot effect, which is associated to oxidation reforming reactions, was investigated for catalyst activity and durability.

Heat Transfer Research of Gas-solid-liquid Three Phase Coupling of EGR Cooler

The main aim of the study is to get the temperature and backpressure of a car engine exhaust gas which goes through the EGR-cooler. So the internal fluid flow and heat transfer process of the EGR cooler must be studied more clearly, numerical simulations are applied. Based on the strong coupling method, gas-solid-liquid three phases coupling model of the typical heat transfer unit is established. According to the coupling result, the heat flux of the tube’s outside surface is gained and then mapped to the inner surface of the cooler’s water. The water model is set up based on the separation coupling method. According to the analysis of the calculation, the detailed pressure and temperature distribution of the gas, water and solid are obtained. From the distribution cloud, we know the changes of the parameters along the fluid flows streamline.

Sulfur Driven Nucleation Mode Formation in Diesel Exhaust under Transient Driving Conditions

Sulfur driven diesel exhaust nucleation particle formation processes were studied in an aerosol laboratory, on engine dynamometers, and on the road. All test engines were equipped with a combination of a diesel oxidation catalyst (DOC) and a partial diesel particulate filter (pDPF). At steady operating conditions, the formation of semivolatile nucleation particles directly depended on SO2 conversion in the catalyst. The nucleation particle emission was most significant after a rapid increase in engine load and exhaust gas temperature. Results indicate that the nucleation particle formation at transient driving conditions does not require compounds such as hydrocarbons or sulfated hydrocarbons, however, it cannot be explained only by the nucleation of sulfuric acid. A real-world exhaust study with a heavy duty diesel truck showed that the nucleation particle formation occurs even with ultralow sulfur diesel fuel, even at downhill driving conditions, and that nucleation particles can contribute 60% of total particle number emissions. In general, due to sulfur storage and release within the exhaust aftertreatment systems and transients in driving, emissions of nucleation particles can even be the dominant part of modern diesel vehicle exhaust particulate number emissions.

Performance of Diesel Engine Operating with Waste Plastic Disposal Fuel

Nowadays, many researches are conducted to produce alternative fuel. In order to overcome increasing price of fossil fuel and environmental issues, fuel from natural sources such as palm, rapeseed and jathropa are increasingly being utilized to produce bio-fuel. Similar as natural source, waste product such as plastics and tires also can be processed to produce alternative fuel. In this paper, engine performance of diesel engine operating with 100% waste plastic disposal fuel (WPDF) is analyzed and compared to diesel fuel. The experiment is conducted using single cylinder YANMAR TF120M diesel engine which is operating at variable speed and constant load. The performance parameters that analyzed in the experiment are engine power, torque, combustion pressure and exhaust gas temperature. Results of the experiment shows that waste plastic disposal fuel (WPDF) potentially can be use as alternative fuel in diesel engine. However, based on the data obtained, performance of diesel engine operating with WPDF is lower compared to diesel fuel.

Nonlinear and adaptive control of NO/NO2 ratio for improving selective catalytic reduction system performance

Reducing the NOx emissions from Diesel engines remains as a challenging issue as the emission standards for Diesel engine powered vehicles have become more stringent than ever before. Urea-based selective catalytic reduction (SCR) systems have emerged as a promising technique in addressing this issue. However, the SCR performance in terms of NOx reduction and ammonia slip continues as an ongoing challenge due to the engine exhaust gas temperature variations, Diesel emission characteristics (especially high NO/NO2 ratio), and immature SCR controls. The purpose of this study is to improve the SCR performance by feeding the SCR system with exhaust gas having the desired NO/NO2 ratio. The proposed complete active NO/NO2 ratio control consists of a low-level adaptive NO/NO2 ratio controller and a high-level nonlinear soot mass controller. The low-level controller utilizes the pre-SCR catalysts such as Diesel oxidation catalyst (DOC) to convert part of NO into NO2, while the high-level controller was designed and coordinated with the low-level controller to avoid NO2 reduction through the Diesel particulate filter (DPF). Simulation and experimental results show that the proposed active NO/NO2 ratio control has the potentials of regulating the NO/NO2 ratio to the desired value and thus considerably improving the SCR performance. Simulation results also illustrate that the active NO/NO2 ratio control can enable the SCR system size reduction by a half without a significant sacrifice on the overall tailpipe emission control performance. Such an integrated aftertreatment system control can be instrumental in reducing the cost and improving the performance of SCR systems, especially in low-temperature operations.

Liquid-Phase Catalytic Decomposition of Novel Ammonia Precursor Solutions for the Selective Catalytic Reduction of NOx

Aqueous solutions of NH3-precursor compounds (i.e. urea and methanamide) were catalytically hydrolyzed in the liquid phase by applying a pressure of 50 bar during contact with the catalyst in a heated tube. Methanamide could be hydrolyzed on an Au/TiO2 catalyst to yield not only NH3, but also H2. Decomposition of urea under high pressure in the liquid phase could even be achieved without the addition of a catalyst. Due to the large excess of water present during decomposition, side products could be avoided. As the reactor tube is electrically heated, the presented method provides a possibility to reliably transform NH3-precursor compounds into gaseous NH3 independent of the engine exhaust gas temperature. The NH3-flow can be added to the main exhaust duct to enable the selective catalytic reduction of NOx at the light-off of the SCR catalyst.

Effects of exhaust gas recycle in a downsized gasoline engine

Lately, the exhaust gas recycle usage, widely diffused in Diesel engines, has been adopted in SI engines as well. It is a cheap technique which allows a sound control of NO formation meanwhile it can improve engine thermodynamics.In this paper, the influence of EGR on the operation of a turbocharged spark ignition engine has been evaluated by using both experimental and numerical techniques. In particular, since knock occurrence is a crucial point in the optimization of a turbocharged SI engine, the improvement in knock resistance, at high load operation, has been assessed. First, a method for knock detection and quantification has been illustrated. Then, the influence of EGR on engine performance, octane requirement and exhaust gas temperature was measured at two different rotational speed values and WOT operation.Since EGR has produced a drop in engine performance (between 10% and 13%) and an increase in knock resistance, a new set of main control variables has been determined in order to restore the original torque level while achieving a significant decrease in specific fuel consumption (between 6% and 11%).At the end, numerical analyses of engine combustion, aimed to explain the results of experimental investigations, have been carried out and a summary is reported in the paper.

Fault Diagnosis of Gas Turbine Engine LRUs Using the Startup Characteristics

This paper introduces a feature-extraction method to characterize gas turbine engine dynamics. The extracted features are used to develop a fault diagnosis and prognosis method for startup related sub-systems in gas turbine engines - the starter system, the ignition system and the fuel delivery system. The startup of a gas turbine engine from ignition to idle speed is very critical not only for achieving a fast and efficient startup without incurring stall, but also for health monitoring of many subsystems involved. During startup, an engine goes through a number of phases during which various components become dominant. The proposed approach physically monitors the relevant phases of a startup by detecting distinct changes in engine behavior as it manifests in such critical variables as the core speed and the gas temperature. The startup process includes several known milestones, such as starter-on, light-off, peak gas temperature, and idle. As each of these is achieved, different engine components come into play and the dynamic response of the engine changes. Monitoring engine speed and exhaust gas temperature and their derivatives provides valuable insights into engine behavior. The approach of the fault diagnosis system is as follows. The engine startup profiles of the core speed (N2) and the gas temperature are obtained and processed into a compact data set by identifying critical-to-characterization instances. The principal component analysis is applied to a number of parameters, and the fault is detected and mapped into three engine component failures which are the starter system failure, the ignition system failure, and the fuel delivery system failure.

Prediction of engine performance for an alternative fuel using artificial neural network

This study deals with artificial neural network (ANN) modeling to predict the brake specific fuel consumption, effective power and average effective pressure and exhaust gas temperature of the methanol engine. To obtain training and testing data, a number of experiments were performed with a four-cylinder, four-stroke test engine operated at different engine speeds and torques. Using some of the experimental data for training, an ANN model based on standard back propagation algorithm was developed. Then, the performance of the ANN predictions was measured by comparing the predictions with the experimental results. Engine speed, engine torque, fuel flow, intake manifold mean temperature and cooling water entrance temperature have been used as the input layer, while brake specific fuel consumption, effective power, average effective pressure and exhaust gas temperature have also been used separately as the output layer. After training, it was found that the R2 values are close to 1 for both training and testing data. RMS values are smaller than 0.015 and mean errors are smaller than 3.8% for the testing data. This shows that the developed ANN model is a powerful one for predicting the brake specific fuel consumption, effective power and average effective pressure and exhaust gas temperature of internal combustion engines.

Engine performance and emission analysis of LPG-SI engine with the aid of artificial neural network

Artificial neural network (ANN) technique is used in this analysis to estimate the performance and emission concentration of liquefied petroleum gas (LPG) spark-ignition (SI) engine. The performance indicators include fuel consumption and brake thermal efficiency while the emission components are NO x, CO, CO2, O2, and unburned hydrocarbon (UHC). Data of engine body temperature and exhaust gas temperature are also simulated. The first part of this study involves experimental works where a single-cylinder four-stroke SI engine was modified to allow the intake of LPG and operated at variable loadings with constant speed. The experimental results show that LPG produces comparable performance at high loads while significant reduction takes place in NO x, CO, CO2, O2, and UHC concentrations. The second part of this study involves the use of back-propagation algorithm for the training of the ANN model. The result of the simulation reveals that ANN model is appropriate to estimate the engine performance and gas exhaust emissions with correlation coefficient ranging from 0.9 to 0.99 with low root mean-squared error and low mean relative error.

Coupling a Dynamic Linear Model with Random Forest Regression to Estimate Engine Wear


 
 
 
 Mechanical systems wear or change over time. Data collected over a system’s life can be input to statistical learning models to predict this wear/change. A research effort at The Boeing Company has modeled gas turbine engine exhaust gas temperature (EGT) as a function of other recorded parameters. Our investigation chose gas turbines, but these techniques could also be used for other systems that slowly change (degrade) over time. Previous work trained a flexible empirical regression model at a fixed point of wear, and then applied it independently at time points over the life of an engine to predict wear. However, wear typically occurs slowly and smoothly. This paper describes the benefit of relating wear predictions over time using a dynamic linear model, which is an example of a state space method. The combined model predicts wear with dramatically reduced variability over both our previous effort and a baseline method. The benefit of reduced variability is that engine wear is more evident, and it is possible to detect operational anomalies more quickly. In addition to tracking wear, we also use the model as the basis for a Bayesian approach to monitor for sudden changes and reject outliers, and adapt the model after these events. Experiments compare methods and give some guidance in applying the methodology.