Using response surface methodology approach for optimizing performance and emission parameters of diesel engine powered with ternary blend of Solketal-biodiesel-diesel. (August 2022)

• Record Type: Journal Article
• Authors: Sharma, Prabhakar; Le, Minh Phung; Chhillar, Ajay; Said, Zafar; Deepanraj, Balakrishnan; Cao, Dao Nam; Bandh, Suhaib A.; Hoang, Anh Tuan
• Is Part Of: Sustainable energy technologies and assessments. Volume 52:Part D(2022)
• Publication Date: 2022-08
• Subjects: Solketal -- Ternary blend -- Engine behaviors -- Optimization -- Response surface methodology; Renewable energy sources -- Periodicals; Energy development -- Technological innovations -- Periodicals; Electric power production -- Periodicals; Energy storage -- Periodicals; 333.79
• DOI: 10.1016/j.seta.2022.102343
• Languages: English
• ISSNs: 2213-1388

Abstract

Graphical abstract: Highlights: Ternary blend of Solketal-biodiesel-diesel are employed to power the diesel engine. Effects of compression ratio, injection parameters, and blending ratio are analyzed. Box-Behnken design is used for robust model prediction and optimization. High R (09695–0.9858) and R 2 (0.9401–0.9717) are achieved for optimized values. Abstract: This study focused on optimizing operation parameters of a diesel engine powered with ternary blends of oxygenated additive (Solketal)-biodiesel (originated from waste cooking oil)-diesel. Different ratios of the ternary blend were used to fuel the test engine at various compression ratios, fuel injection pressures and injection timings. The experimental data were used for RSM-based model prediction, establishing the relation function, and optimization. The RSM-based prognostic model was evaluated with statistical regression indices such as Pearson's coefficient (0.9695 – 0.9858) and coefficient of determination (0.9401 – 0.9717), showing highly robust predictive models. Besides, root mean square error (0.002 – 1.74) and mean absolute percentage deviation (0.3–0.9%) of the predictive model were low. The optimized values of CR, FIP, FIT, and Solketal content in the ternary blend was 17.8, 270 bar, 27 o bTDC, and 9.5%, respectively. The model predicted and observed outputs were within 8%, indicating that the used model in this study is robust to predict output at this optimized condition with 29.4% of brake thermal efficiency, 0.396 kg/kWh brake-specific fuel consumption, 0.39% of carbon monoxide, 228 ppm of nitrogen oxides, and 52 ppm of unburnt hydrocarbon. Generally, using the Solketal oxygenated additive could improve engine performance and reduce harmful emissions.