Parametric optimization of engine performance and emission for various n-butanol blends at different operating parameter condition

Patil, Amit R.; Desai, Avinash D.

doi:10.1016/j.aej.2020.02.006

Cited by 15 publications

(8 citation statements)

References 16 publications

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“…The best parameter results for the highest BTE were found at a blending ratio of 0%, a CR of 18:1, a fuel injection pressure of 160 bar, and a load intensity of 9 kg. 36 …”

Section: Methodsmentioning

confidence: 99%

“…The best parameter results for the highest BTE were found at a blending ratio of 0%, a CR of 18:1, a fuel injection pressure of 160 bar, and a load intensity of 9 kg. 36 According to the analysis, in a diesel engine fueled by a blend of C. inophyllum diesel, diesel, and n-butanol, greater performance was reported when 15% n-butanol was used. To predict the performance at full load, a study was done by taking input factors such as the blend ratio, injection, and pressure.…”

Section: Taguchi Methodmentioning

confidence: 99%

“…The factors for optimization in the experiment were the fuel mixing ratio, CR, fuel injection pressure, and intensity of load. The best parameter results for the highest BTE were found at a blending ratio of 0%, a CR of 18:1, a fuel injection pressure of 160 bar, and a load intensity of 9 kg …”

Section: Methodsmentioning

confidence: 99%

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Overall Performance Investigation and Optimization of a Multi-fuel Operated Compression Ignition Engine Using Coupled Taguchi and Grey Relational Analysis

Mishra¹,

Mohapatra

Sahoo³

et al. 2022

ACS Omega

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Biofuels are regarded as the best diesel fuel substitute due to their low sulfur concentration, reduced aromatic hydrocarbon content, renewable nature, and higher oxygen content. In this research article, the impact of producer gas, Calophyllum inophyllum oil, diesel, and a blend of C. inophyllum–producer gas fuel on a variable compression ratio (VCR) compression ignition (CI) engine, and the performance and emission parameters are evaluated. Several test runs are undertaken at a constant speed of 1500 rpm to predict the performance and emission characteristics of the test engine by changing input parameters such as engine load, CR, and fuel mode of operation. The brake thermal efficiency, BTE, is considered the performance characteristic, and CO, HC, NO X , and opacity are considered the emission characteristics for the present study. The biofuel, or producer gas, employed in this study is prepared from waste biomasses, such as leaves, small tree branches, vegetable waste, and cow dung, aiding waste management for a sustainable environment. In addition, a coupled Taguchi–Grey relational analysis technique is used to predict the best possible combination of control factors for optimizing the overall output responses. 12 kg load, a CR of 18, and diesel fuel are found to be the optimum input parameters of an engine toward optimum performance. A confirmation test is performed at the end to validate the outcome of the experiment. An enhancement in performance of 22.75% is observed with the considered Grey relational grade model.

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“…The best parameter results for the highest BTE were found at a blending ratio of 0%, a CR of 18:1, a fuel injection pressure of 160 bar, and a load intensity of 9 kg. 36 …”

Section: Methodsmentioning

confidence: 99%

Section: Taguchi Methodmentioning

confidence: 99%

See 1 more Smart Citation

Overall Performance Investigation and Optimization of a Multi-fuel Operated Compression Ignition Engine Using Coupled Taguchi and Grey Relational Analysis

Mishra¹,

Mohapatra

Sahoo³

et al. 2022

ACS Omega

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“…The RNPP has two solution sets: possibly and surely feasible optimal solution sets in the 1 st class. Parametric optimization [6] is a helpful universal tool that has recently got many applications in process engineering systems [1,7,14,20]. Given a constrained optimization problem, including a set of variables and bounded parameters, it provides the optimal value of the variables as an explicit function of the parameters without completely enumerating the entire space of the parameters.…”

Section: Introductionmentioning

confidence: 99%

Min-Max Solutions for Parametric Continuous Static Game Under Roughness (Parameters in the Cost Function and Feasible Region Is a Rough Set)

Aboelnaga¹,

Zidan²

2020

UMJ

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Any simple perturbation in a part of the game whether in the cost function and/or conditions is a big problem because it will require a game re-solution to obtain the perturbed optimal solution. This is a waste of time because there are methods required several steps to obtain the optimal solution, then at the end we may find that there is no solution. Therefore, it was necessary to find a method to ensure that the game optimal solution exists in the case of a change in the game data. This is the aim of this paper. We first provided a continuous static game rough treatment with Min-Max solutions, then a parametric study for the processing game and called a parametric rough continuous static game (PRCSG). In a Parametric study, a solution approach is provided based on the parameter existence in the cost function that reflects the perturbation that may occur to it to determine the parameter range in which the optimal solution point keeps in the surely region that is called the stability set of the \(1^{st}\) kind. Also the sets of possible upper and lower stability to which the optimal solution belongs are characterized. Finally, numerical examples are given to clarify the solution algorithm.

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“…They reviewed artificial neural network (ANN) and RSM optimization methods in their manuscript, but combined analysis has not been covered. Patil and Desai 34 used various blends of n -butanol and diesel in a single-cylinder VCR diesel engine for experiments at various engine settings of FIT, compression ratio (CR), and FIP. The Taguchi DoE method was executed for optimization.…”

Section: Introductionmentioning

confidence: 99%

Application of Taguchi and response surface methodology approach to a sustainable model developed for a compression-ignition engine using polanga biodiesel/diesel blends

Sharma¹,

Singh

Tyagi³

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part I:

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The exhaustive and irresponsible use of fossil fuels has created numerous public and environmental health issues in the past few decades. To address this issue, this work has investigated the use of polanga ( Calophyllum inophyllum) biodiesel/diesel blends in a diesel engine. This study focuses primarily on the optimization of performance and emission characteristics of a diesel engine fuelled with polanga-based biodiesel blends. The engine input factors were also investigated for desired optimal thermal performance. In this study, four input parameters, namely, engine loads, blends of polanga-based biodiesel, fuel injection pressure, and fuel injection timing were chosen for analysis. The corresponding engine output responses, namely, brake thermal efficiency, CO, NOx, and smoke emissions, are selected for their optimization by Taguchi method and response surface methodology. The results show that the best setting of above-mentioned input factors is reported at 44% engine load, 13% mixing of polanga biodiesel with diesel, 180 bar injection pressure of fuel, and 21.5 °bTDC injection timing of fuel. The comparison between results obtained by the optimization process and experimental results showed that the deviations were always found to be within the acceptable range of errors.

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Parametric optimization of engine performance and emission for various n-butanol blends at different operating parameter condition

Cited by 15 publications

References 16 publications

Overall Performance Investigation and Optimization of a Multi-fuel Operated Compression Ignition Engine Using Coupled Taguchi and Grey Relational Analysis

Overall Performance Investigation and Optimization of a Multi-fuel Operated Compression Ignition Engine Using Coupled Taguchi and Grey Relational Analysis

Min-Max Solutions for Parametric Continuous Static Game Under Roughness (Parameters in the Cost Function and Feasible Region Is a Rough Set)

Application of Taguchi and response surface methodology approach to a sustainable model developed for a compression-ignition engine using polanga biodiesel/diesel blends

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