144
Views
16
CrossRef citations to date
0
Altmetric
Articles

Application of fuzzy-assisted grey Taguchi approach for engine parameters optimization on performance-emission of a CI engine

ORCID Icon, &
Received 26 Mar 2019, Accepted 07 Sep 2019, Published online: 28 Nov 2019
 

ABSTRACT

With the prevalent interest in diesel engine performance and emission, it is necessary to define optimum engine operating condition with less number of experiments for the efficient and effective outcome. In this article, the combined effect of input parameters viz. engine load and types of fuel blend in controlling BSFC, NOx, UHC, and CO output variables in a diesel engine are investigated. In this study, a fuzzy-assisted grey Taguchi method has been proposed to optimize the engine load and types of fuel used. The main purpose of using fuzzy inference system is to convert the multi-response into an equivalent single objective optimization. Optimum input factor corresponding to estimated values of output response has been obtained by employing fuzzy grey reasoning grade. The computed factor combination based on the highest ranking of fuzzy grey grade is validated through a confirmation experiment. Based on grey-fuzzy approach optimum engine parameter is found D85B10E5 at 100% load. ANOVA analysis of Grey Fuzzy Grade reveals engine load is the most significant input factor influencing engine output. Based on the results it is concluded that grey-fuzzy-Taguchi approach can be a more useful tool to ameliorate performance and emission of an engine compared to simple grey relational grade.Abbreviations: CI: compression ignition; BSEC: break specific energy consumption; NOx: nitrogen oxides; UHC: unburned hydrocarbon; CO: carbon monoxide; GRA: grey relational analysis; GRC: grey relational coefficient; GRG: grey relational grade; ANOVA: analysis of variance; DAQ: data acquisition; S/N: signal to noise ratio; FIS: fuzzy interface system; GFG: grey fuzzy grade

Nomenclature

D100=

100% Diesel

D90B5E5=

90% Diesel, 5% Palm biodiesel, 5% Ethanol

D85B10E5=

85% Diesel, 10% Palm biodiesel, 5% Ethanol

D80B15E5=

80% Diesel,15% Palm biodiesel,5% Ethanol

D75B20E5=

75% Diesel, 20% Palm biodiesel, 5% Ethanol

Acknowledgments

We gratefully acknowledge with warm appreciation to Department of Mechanical Engineering, National Institute of Technology Agartala, West Tripura, India for supporting us to complete this research work.

Additional information

Notes on contributors

Suman Dey

Suman Dey, Ph.D. scholar in Mechanical engineering Department, NIT Agartala. His field of research including alternative fuels, fuel additives, engine parameters optimization. He is also working with the effect of fuel additives for engine emission reduction.

Madhujit Deb

Madhujit Deb, Assistant professor in the Mechanical Engineering Department, NIT Agartala. His field of research includes alternative fuels and IC engine.

Pankaj Kumar Das

Pankaj Kumar Das, Assistant professor in the Mechanical Engineering Department, NIT Agartala. His interested working areas are machine design, workshop process, tribology, strength of material and finite element methods.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.