Investigation on VCR engine performance using (Hevea brasiliensis) biodiesel using response surface method. (2021)

• Record Type: Journal Article
• Authors: Murugapoopathi, S.; Vasudevan, D.; Rajaganapathy, C.
• Is Part Of: Materials today. Volume 37(2021)Supplement Part 2
• Page Start: 1096
• Page End: 1102
• Publication Date: 2021
• Subjects: IP Injection pressure -- CR Compression ratio -- VCR Variable Compression ratio -- NOx Oxides of nitrogen -- B20 20% biodiesel + 80% diesel -- B40 40% biodiesel + 60% diesel -- B60 60% biodiesel + 40% diesel -- B80 80% biodiesel + 20% diesel -- IT Ignition timing -- HC Hydrocarbon -- CO Carbon monoxide -- RSM Response surface methodology -- CO2 Carbon dioxide -- PC Personal computer -- BTE Brake thermal efficiency -- BSFC Brake specific fuel consumption -- ANOVA Analysis of variance -- CI Compression ignition; VCR engine -- Response surface methodology -- Emission -- Biodiesel -- NOx emission; Materials science -- Congresses -- Periodicals; 620.1
• DOI: 10.1016/j.matpr.2020.06.339
• Languages: English
• ISSNs: 2214-7853

Abstract

Highlights: RSM modelling was effectively analyzed with experimental observations with RSO biodiesel of blends and diesel. RSM models are effectively used to develop performance and emission models. Robust designed models will be used for future scope using this RSM models. Abstract: Many studies revealed in the direction of improving the performance and reduce the emission of a diesel engine. Design of experiment is one of the methods to analyse different factors which influence the responses of the engine. The factors were compression ratio, load, fuel blend and injection pressure and responses of BTE, SFC and CO, HC and NOx emissions were taken. Design matrix with 31 runs central composite design is chosen to analyse the effect of confidence level of factors. The model was evaluated using response surface methodology for fitting the numerical model through tested values. The regression equations were formed to evaluate the different responses of a numerical model and error was found to be less than 10% with experimental runs. D-optimality test was used to optimize more than one solution in the ANOVA table. The optimum factors such as 21 CR with 8 kg of load blend 20 and injection pressure of 150 bar gives an error of less than 10% with all responses with composite desirability of 0.995867. It is found that the emission NOx, CO decreases with less than 5% of experimental value with increase in compression ratio for lower blends.