Empirical and ANN Optimization Study on Lemongrass Oil Blends in CI Engines
J. Environ. Nanotechnol., Volume 14, No 2 (June 2025) pp. 402-414
Abstract
This research investigates the efficiency and exhaust characteristics of a CI engine operating with a B20 lemongrass oil biodiesel mixture, systematically exploring the intricate interactions between compression ratios (17.5 and 18.5), injection pressures (220-260 bar), and injection timings (22°-26°bTDC. Leveraging an ANN optimization framework, the study aims to comprehensively analyze and define the experimental parameters. Experimental findings reveal that diesel (F0) outperforms lemongrass oil biodiesel (F1) in BTE and Brake specific fuel consumption (BSFC), with Brake Thermal Efficiency ranging from 27.46%–29.5% and BSFC of 0.29–0.32 kg/kWh, compared to biodiesel's 25.7%–28.4% and higher BSFC of 0.34–0.44 kg/kWh. Diesel also produces lower CO (0.4166%–0.4877%) and NOx (230.45–249.23 ppm), while biodiesel emits higher CO (0.45%–0.59%) and NOx (233.56–249.56 ppm). Biodiesel (F1) has lower HC emissions (47.8–51.9 ppm) but higher smoke opacity (53.9%–58.96%) compared to diesel's higher HC (51.9–63.5 ppm) and lower opacity (54.2%–56.23%). Using an ANN model with Bayesian optimization and activation functions (tanh, sigmoid, ReLU), the study found that predicted values closely align with actual values, with minimal deviations for BTE and HC emissions. However, larger deviations are observed for BSFC and NOx, especially at higher values. Improvements are recommended to enhance prediction accuracy for BSFC and NOx.
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