G. Sakthivel

Application of fuzzy logic in internal combustion engines to predict the engine performance

This paper describes an application of fuzzy logic principle for predicting the internal combustion engine performance, emission and combustion characteristics using fish oil biodiesel. Experimental investigations on a single cylinder, constant speed, direct injection diesel engine were carried out under variable load conditions. The performance, emission and combustion characteristics such as brake thermal efficiency, hydrocarbon, exhaust gas temperature, oxides of nitrogen (NOx), carbon monoxide, smoke, carbon dioxide, ignition delay, combustion delay and maximum rate of pressure rise were considered. Engine performance was measured using an exhaust gas analyser, smoke metre, piezoelectric pressure transducer and crank angle encoder for different fuel blends and engine load conditions. The obtained data were recorded for each experiment and associated data used to develop a multiple inputs and multiple outputs fuzzy logic model. The developed model produced idealised results with the correlation coefficients of 0.988–0.999 and root mean square error, and was found to be useful for predicting the engine performance characteristics with limited number of available data.

Artificial neural network approach to predict the engine performance of fish oil biodiesel with diethyl ether using back propagation algorithm

An artificial neural network (ANN) model is developed to predict the engine performance of fish oil biodiesel blended with diethyl ether. Engine performance and emission characteristics such as brake thermal efficiency, hydrocarbon, exhaust gas temperature, oxides of nitrogen (NOx), carbon monoxide (CO), smoke and carbon dioxide (CO2) were considered. Experimental investigations on single-cylinder, constant speed, direct injection diesel engine are carried out under variable load conditions. The performance and emission characteristics are measured using an exhaust gas analyser, smoke metre, piezoelectric pressure transducer and crank angle encoder for different fuel blends and engine load conditions. In this model, a back propagation algorithm is used to predict the performance. Computational results clearly demonstrated that the developed ANN models produced less deviations and exhibited higher predictive accuracy with acceptable determination correlation coefficients of 0.97–1 and mean relative error of 0–3.061% with experimental values. The root mean square errors were found to be low. The developed model produces the idealised results and it has been found to be useful for predicting the engine performance and emission characteristics with limited number of available data.

Optimisation of compression ignition engine performance with fishoil biodiesel using Taguchi-Fuzzy approach

Due to the increase in demand of energy, there is a steep rise in petroleum product, which led to the depletion of conventional energy. This gave rise to the need of biodiesel as an alternate for diesel fuel. This paper deals with the study of biodiesel blends performance and different emission behaviour using the Taguchi and fuzzy logic method. Experimental investigations on a single cylinder constant speed direct injection diesel engine were carried out under two parameters: blend proportion and percentage load for six and five levels, respectively. As per this method, an L30 orthogonal array was used to collect data for 30 trials, which were experimented at different engine load and blend proportion. The optimisations are done on brake thermal efficiency, carbon monoxide (CO), carbon dioxide (CO2), hydrocarbon (HC), oxides of nitrogen (NOx), smoke, exhaust gas temperature, ignition delay, combustion delay and maximum rate of pressure rise. The signal-to-noise ratio was used for data analysis and the result is verified by the Fuzzy control system model with multi input multi output (MIMO) to predict the performance of engine. The developed model produced idealised results with the correlation coefficients of 0.897–0.998 and root mean square error and found to be useful for predicting the engine performance characteristics with limited number of available data.

A neural network model for the prediction of compression ignition engine performance at different injection timings

Rapid depletion of fossil fuel and continuous increase in gasoline prices have stimulated the search of alternative fuels. This paper deals with the prediction of engine performance, emission and combustion characteristics of compression ignition engine fuelled with fish oil biodiesel using artificial neural network (ANN). Experimental investigations are carried out in a single cylinder constant speed direct injection diesel engine under variable load conditions at different injection timings−210, 240 and 270 bTDC. The performance, combustion and emission characteristics are measured using an exhaust gas analyser, smoke meter, piezoelectric pressure transducer and crank angle encoder for different fuel blends and engine load conditions. For training the neural network, feed-forward back propagation algorithm is used. The developed ANN model predicts the performance, combustions and exhaust emissions with a correlation coefficients (R) of 0.97–0.99 and a mean relative error of 0.62–4.826%. The root mean square errors are found to be low. The developed model has found to predict accurately the engine performance, combustion and emission parameters at different injection timings.

UNSTEADY FREE CONVECTIVE BOUNDARY LAYER FLOW OF A NANOFLUID PAST A STRETCHING SURFACE USING SPECTRAL RELAXATION METHOD

ABSTRACT An analysis is presented to study the unsteady, two-dimensional nanofluid flow of heat and mass transfer with vanishing nanoparticles flux at the wall in the presence of heat generation or absorption with viscous dissipation. In this analysis, it is assumed as nanoparticle flux is zero on the boundaries. The highly nonlinear differential equations governing the boundary layer flow, heat and mass transfer are numerically solved by spectral relaxation method and validated with MATLAB solver bvp4c. The results are obtained by some values of the physical parameters, namely, the Brownian motion parameter, the thermophoresis parameter, unsteadiness parameter, Eckert number, heat generation or absorption parameter, Prandtl number and Lewis number. Physical features for all relevant parameters on the dimensionless velocity, temperature, nanoparticles volume fraction and heat and mass transfer rates are analysed and discussed. The thermal boundary layer thickness increases with an increase in the thermophoretic parameter. The nanoparticle volume fraction profile significantly descends from the surface with an increase in Brownian motion parameter.

Failure mode and effect analysis using fuzzy analytic hierarchy process and GRA TOPSIS in manufacturing industry

In the manufacturing industry, system failures may cause to personnel and infrastructure damages to the organisation which leads to loss in production. FMEA is a widely used engineering technique to improve product quality, reliability and eliminate known and/or potential failures. The present study develops evaluation model based on FMEA and FAHP integrated with combination of TOPSIS and GRA to valuate greatest risk in the processes for production of automotive dust cap in manufacturing industry. FAHP is used to compute the weights whereas fuzzy TOPSIS is used to obtain the final ranking. Among the various failure, blanking of blank failure mode is ranked first in the priority order to make an attention followed by the drawing dimension failure > window cutting failure > final inspection of dimension failure > packing (short excess quantity) failure > hole size failure > packing (damage in pack) failure > dispatch failure > plating failure.

Selection of optimum fish oil fuel blend to reduce the greenhouse gas emissions in an IC engine—A hybrid multiple criteria decision aid approach

ABSTRACT The increasing demand on energy due to population growth and rising of living standards has led to considerable use of fossil fuels which has in turn, had an adverse impact on environmental pollution and depletion of fossil fuels in Internal Combustion (IC) engine sector. Alternative fuel blend evaluation in IC engine fuel technologies is a very important strategic decision involving decisions balancing within a number of criteria and opinions from different decision maker of IC engine experts. The selection of appropriate source of biodiesel and proper blending of biodiesel plays a major role in alternate energy production. This paper describes an application of hybrid Multi Criteria Decision Making (MCDM) technique for the selection of optimum biodiesel blend in the IC engine. The proposed model, Analytical Network Process (ANP) is integrated with Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) to evaluate the optimum blend. Here the ANP is used to determine the relative weights of the criteria, whereas TOPSIS is used for obtaining the final ranking of alternative blends. An efficient pair-wise comparison process and ranking of alternatives can be achieved for optimum blend selection through the integration of ANP and TOPSIS. The obtained preference order for the blends are as B20 > B40 > Diesel > B60 > B80 > B100. This paper highlights a new insight into MCDM techniques to evaluate the best fuel blend for the decision makers such as engine manufactures and R&D engineers to meet the fuel economy and emission norms to empower the green revolution.

Correlation of combustion noise with ignition-timing in an IC engine

ABSTRACT The need for development of a more efficient IC engine is always on the rise which can be related to oil being a non-renewable resource and its increasing carbon foot print causing global warming. In addition to the CO2, there are more toxic pollutants such as NOx, CO and HC due to improper combustion. These demands have paved way for development of alternative fuel engines such as bio-diesel, bio-ethanol and hybrids. Still these engines need to optimise their combustion to get the best of both worlds. And for the purpose of optimisation there must be a means to measure and estimate the combustion characteristics. Thus analysing the combustion noise gives some insight into the performance of the engine.

Boundary layer flow of nanofluids to analyse the heat absorption/generation over a stretching sheet with variable suction/injection in the presence of viscous dissipation

ABSTRACT In this investigation, the heat and mass transfer characteristics in boundary layer flow about a stretching sheet in a porous medium filled with TiO2 – water and Al2O3 – water-based nanofluids, in the presence of internal heat generation or absorption and viscous dissipation with variable suction or injection effects is numerically studied. The similarity transformations are used to transform the governing boundary layer equations for momentum, energy and species transfer into a set of non-linear ordinary differential equations which are solved numerically by Keller-box method. The obtained numerical results are validated against results computed by using MATLAB bvp4c routine, and excellent agreement is observed. The impact of various pertinent parameters on velocity, temperature and concentration as well as the friction factor coefficient, local heat and mass transfer rates are derived and discussed through graphs and tables for TiO2 and Al2O3 water-based nanofluids. The present study reveals that an increase in Eckert number (Ec) and heat generation/absorption parameter (Q) significantly decreases local heat transfer rate.

Design and Analysis to Analyse the Heat Transfer of Space Heater for Boat

ABSTRACT As fossil fuels are depleting gradually with the course of time there is a need for developing innovative products that can extract maximum potential that the system can deliver. One of the key areas that still make use of diesel fuels for experiencing thermal comfort is the boat heating system. Due to its user-friendly characteristics with low maintenance requirements, space heater has still be the benchmark for all other types of heaters. The boat cabin heater is an essential setup for all kinds of boats and ships not just for the warmth but also to eliminate the dampness that can spread throughout the boat in cold weather. The paper presents a detailed analysis of thermal behaviour inside a space heater using computational fluid dynamics technique to study the effect of fin numbers and fin location inside the heat exchanger. A total of 11 cases were simulated to study the effect of a fin on the heat transfer rate and pressure drop. An optimisation is done to have maximum heat transfer rate with minimum pressure drop and results showed that case number 9 has satisfied the above criteria to obtain an effectiveness of 90%.