Artificial neural network approach to study the effect of injection pressure and timing on diesel engine performance fueled with biodiesel

This study intends to predict the influence of injection pressure and injection timing on performance, emission and combustion characteristics of a diesel engine fuelled with waste cooking palm oil based biodiesel using the artificial neural network (ANN) model. To acquire data for training and testing in the proposed ANN, experiments were carried out in a single cylinder, four stroke direct injection diesel engine at a constant speed of 1500 rpm and at full load (100%) condition. From the experimental results, it was observed that waste cooking palm oil methyl ester provided better engine performance and improved emission and combustion characteristics at injection pressure of 280 bar and timing of 25.5° bTDC. An ANN model was developed using the data acquired from the experiments. Training of ANN was performed based on back propagation learning algorithm. Multilayer perceptron (MLP) network was used for non-linear mapping of the input and output parameters. Among the various networks tested the network with two hidden layers and 11 neurons gave better correlation coefficient for the prediction of engine performance, emission and combustion characteristics. The ANN model was validated with the test data which was not used for training and was found to be very well correlated.     

Vibration reduction of H/Shaft using an electromagnetic damper with mode change

The objective of this study is to develop a damper that can reduce the amplitude of vibration in various frequency ranges. Previous H/Shaft vibration reduction methods work in a passive way. A dynamic damper reduces the amplitude of vibration at its first mode, but vibration still appears at the second mode. A mass damper or hollow shaft can shift the natural frequency to a lower or higher region. The fixed operating frequency prevents vibration from being reduced outside the operating frequency range. The proposed damper uses electromagnets as either masses or actuators to change the damper mode between dynamic damper mode and mass damper mode. The electromagnetic damper (EMD) can change its mode to respond to the vibration excitation at both low and high frequencies. The vibration reduction performance was evaluated by FRF tests in laboratory and vehicle conditions. The results were compared with those of a dynamic damper and indicate that the amplitude of vibration is reduced by 95.6 % when the EMD is implemented on an H/Shaft, whereas only 61.9 % vibration reduction is achieved by the dynamic damper.     

Application of a modified thermostatic control strategy to parallel mild HEV for improving fuel economy in urban driving conditions

A modified thermostatic control strategy is applied to the powertrain control of a parallel mild hybrid electric vehicle (HEV) to improve fuel economy. This strategy can improve the fuel economy of a parallel mild HEV by operating internal combustion engine (ICE) in a high-efficiency region. Thus, in this study, experiments of a parallel mild HEV were conducted to analyze the characteristics of the hybrid electric powertrain and a numerical model is developed for the vehicle. Based on the results, the thermostatic control strategy was modified and applied to the vehicle model. Also, battery protection logic by using electrochemical battery model is applied because the active usage of battery by thermostatic control strategy can damage the battery. The simulation results of the vehicle under urban driving conditions show that the thermostatic control strategy can improve the vehicle’s fuel economy by 3.7 % compared with that of the conventional strategy. The results also suggest that the trade-off between the fuel economy improvement by efficient ICE operation and the battery life reduction by active battery usage should be carefully investigated when a thermostatic control strategy is applied to a parallel mild HEV.     

Real-time empirical NO<Subscript>x</Subscript> model based on In-cylinder pressure measurements for light-duty diesel engines

This paper proposes a real-time empirical model of NO_x emissions for diesel engines. The proposed model predicts the level of NO_x emissions using an empirical model developed based on the thermal NO formation mechanism, the extended Zeldovich mechanism. Since it is difficult to consider the exact physical NO formation phenomena in real-time applications, the proposed algorithm adapts the key factors of the NO formation mechanism from the extended Zeldovich mechanism: temperature of the burned gas, concentration of the gas species, and combustion duration where NO is generated. These factors are considered in a prediction model as four parameters: exhaust gas recirculation rate (EGR rate), crank angle location of 50 % of mass fraction burned (MFB50), exhaust lambda value, and combustion acceleration. The proposed prediction model is validated with various steady engine experiments that showed a high linear correlation with the NO_x emission measured by a NO_x sensor. Furthermore, it is also validated for transient experiments.     

Flamelet combustion model for stratified EGR distribution in a diesel engine

Numerous research has been devoted to finding a method to simultaneously reduce NOx and soot emissions from diesel engines. In-cylinder EGR stratification is a technique that simultaneously reduces NOx and soot using a nonuniform EGR distribution in the combustion chamber. To study the potential of in-cylinder EGR stratification, a new combustion model is required that considers the non-uniform EGR distribution and the chemical kinetics. In this study, a new combustion model, the Flamelet for Stratified EGR (FSE) model, was developed to consider the non-uniform in-cylinder gas distribution based on chemical kinetics. The concept of the FSE model is based on using multiple flamelets with the multizone concept. To describe the non-uniform gas distribution, the combustion chamber is divided into several zones by oxygen concentration at the start of injection. Then, the flamelet equations are solved at the boundary of each zone. The final species mass fraction of each cell is calculated using linear interpolation between two results from the boundaries. In this paper, the FSE model was validated under in-cylinder EGR stratification conditions, and then, the potential of in-cylinder EGR stratification was studied by using the FSE model. The effect of in-cylinder EGR stratification was verified under various injection timing, engine speed, and road conditions with optimized engine geometries. The results shows simultaneous NOx and soot reductions under the stratified EGR condition.     

Stress sensitivity analysis and optimization of automobile body frame consisting of rectangular tubes

At conceptual design stage, beam element is extensively used to create the frame structure of automobile body, which can not only archive the accurate stiffness but also reduce much computational cost. However, the stress definition of beam element is very complex so that the stress sensitivity and optimization are difficult to analytically derive and numerically program. This paper presents an solution to this problem and an application in the lightweight optimization design of automobile frame. Firstly, maximal Von Mises stress of rectangular tube is calculated by using the superposition of stress, which is together induced by the axial force, bending moments, torsional moment and shear force. Secondly, the sensitivity of Von Mises Stress with respect to size design variables: breadth, height and thickness are derived, respectively. Thirdly, an optimal criterion is constructed by Lagrangian multiplier method to solve the frame optimization with stress constraints. Lastly, numerical example of car frame proves that the proposed method can guarantee the stress of each beam element almost fully reaches at the yielding stress.     

A Novel Image Encryption Technique Based on Inter Block Difference

Data security plays a vital role in the current scenario due to the advanced and sophisticated data access techniques.Present development in data access is alwa...     

Dynamic Performance of a Bulkhead Flat Car

The dynamic performance of a flat car is studied herein. The performance indices include roll angles, lateral accelerations, center plate loads, side bearing loads, wheel loads and spring deflections. These variables are maximum when the car is running at its critical speed, corresponding to either the rock and roll, or the bounce mode. The Association of American Railroads' (AAR) Flexible Carbody Model was used. The input for vertical track irregularities used in the simulation was generated from published spectra for U.S. Federal Railroad Administration (FRA) Class 4 track. After studying the car's performance with various column loads and spring suspensions, it was found that the most commonly used column load of 4,000 lbs. (17.8 kN) should be used. The spring suspension used in the original car design should also be adopted, in order to avoid spring bottoming.     

Computer-Simulation of the Dynamical Curving Behaviour of a Railway-Bogie

This paper describes the modelling of a two axle railway-bogie with variable design configurations and its application in the investigation of the behaviour in transitional and circular curves. Several results indicate possibilities to improve the curving properties and recommend the usage of forced-steering bogies, which show better performance in narrow curves without unbearable sacrifices to high-speed-behaviour on straight track.