Application of hybrid Taguchi L16 and desirability for model prediction and optimization in assessment of the performance of a novel Water Hyacinth biodiesel run diesel engine. (1st May 2023) - Jain, Akshay
Graphical abstract: Highlights: Novel biodiesel was produced from Water Hyacinth. The highest BTE of 26.79 % was obtained at IT of 20° bTDC for biodiesel mode. The lowest emission was measured at IT at 20° bTDC for biodiesel mode. Taguchi-based L 16 OA is employed for economic and scientific testing. Desirability approach revealed best output at 78% load and 20-degree injection timing. Abstract: The twin effect, fossil fuel crisis as well the rise of pollution, has activated continuous research for alternative, renewable, clean, and affordable energy. In this regard, biodiesel seems to be one of the promising potential solutions to the above-mentioned problems. Keeping this view in mind, the current study aims at the production of biodiesel from Water Hyacinth and testing the same biodiesel in a diesel engine. A single-cylinder, variable injection timing, and 3.5 kW research test diesel engine was selected for testing. To analyze the influence of injection timing and engine load on the performance of a Water Hyacinth biodiesel run diesel engine, four injection timings (20° bTDC, 23° bTDC, 25° bTDC, 28° bTDC) and five varying engine loading conditions (20 %, 40 %, 60 %, 80 %, 100 %) at fixed compression ratio (17.5) was considered. The results of the investigation indicated that the maximum brake thermal efficiency of 26.79 % was obtained at 80 % load, injection timing of 20° bTDC, and a compression ratio of 17.5. For the same settings, the carbon monoxide and hydrocarbon emissions were found to be the least considering all test cases. For efficient use of time and resources, the tests were carried out using a Taguchi L16 orthogonal array. S: N ratios were determined to investigate the underlying patterns in the test phase data, and ANOVA was used to analyze the data to create new correlations. The operational parameters were optimized using the RSM-based desirability technique. With an R 2 between 0.849 and 0.9985, a reliable predictive model in the form of a mathematical expression was created using ANOVA. For each response variable, new correlations were generated. The engine load showed greatest impact on BTE and exhaust emission, excluding peak cylinder pressure. S: N value curves showed how control parameters affected the data. The optimum output of 24.44 % BTE, 51.2 bar PCP, 29.6 ppm CO, 1.51 vol% CO2, 176 ppm NOx, and 23.66 ppm HC can be produced at 78 % load and 20° injection advance, according to parametric optimization using the desirability technique. The modeling residuals for all the parameters were less than 6 %, according to the validation test.