Optimization of engine operating parameters suitable for punnai oil application in CI engine using Grey relational method. Issue 4 (June 2019)

• Record Type: Journal Article
• Authors: Narendranathan, S K; Sudhagar, K; Karthikeyan, R
• Is Part Of: Energy & environment. Volume 30:Issue 4(2019)
• Page Start: 732
• Page End: 751
• Publication Date: 2019-06
• Subjects: Punnai oil -- Taguchi -- Grey relational analysis -- analysis of variance -- regression equation -- performance -- combustion -- emission; Power resources -- Environmental aspects -- Periodicals; Power resources -- Periodicals; Renewable energy sources -- Periodicals; Energy policy -- Environmental aspects -- Periodicals; Ressources énergétiques; Politique énergétique; Energy policy -- Environmental aspects; Power resources; Power resources -- Environmental aspects; Renewable energy sources; Periodicals; 333.7
• DOI: 10.1177/0958305X18813603
• Languages: English
• ISSNs: 0958-305X

Abstract

This work is intended to apply neat form of punnai oil of higher proportion in the existing CI engines with modified operating parameters. It uses neat punnai oil of 50% by volume in compression ignition (CI) engine as diesel–punnai oil blend. The more influencing engine operating parameters such as injection pressure, injection timing, and intake air temperature, and the compression ratio were used for the optimization. A combined Taguchi and Grey relational analysis was used for designing the experiment and optimizing the operating parameters. Based on the methods used, 18 experimental trials were chosen, and their results were fed into the Grey relational analysis. Results of the Grey analysis show that the trial number 13 was performed well. The levels used in this trial such as injection pressure (250 bar), injection timing (25°bTDC), compression ratio (18.5), and intake air temperature (80°C) were identified as the optimum levels of operating parameters for admitting 50% of punnai oil in CI engine. This work had used MiniTab software for designing Taguchi and Grey relational analysis.