A hybrid calibration scheme for developing hydrogen enrichment ratio control map using RSM and ANN technique to enhance the characteristics of an ammonia biodiesel RCCI combustion engine

• Published in: Case studies in thermal engineering Vol. 49; p. 103257
• Main Authors: Elumalai, R., Ravi, K.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01-09-2023; Elsevier
• Subjects: Algal biodiesel: RCCI combustion; Ammonia energy premixing; Hydrogen enrichment energy share; RSM and ANN based hybrid calibration scheme; Hydrogen enrichment energy share; Algal biodiesel: RCCI combustion; RSM and ANN based hybrid calibration scheme; Ammonia energy premixing
• ISSN: 2214-157X; 2214-157X
• DOI: 10.1016/j.csite.2023.103257

This investigation aims to optimally attune hydrogen enrichment ratio for an ammonia biodiesel powered RCCI engine using RSM and ANN techniques. Conventionally, optimal mapping is accomplished through trial-and-error experimentation. In this study, an innovative model-based calibration method for developing an optimal hydrogen ratio map is suggested. The LRF energy share of ammonia in premixing is set at 40%, the hydrogen enrichment is varied from 5 to 20%, and the rest of the energy is biodiesel as HRF. Based on the experimental inputs, the RSM-based optimization has established an ideal hydrogen enrichment ratio of 14.77%, 18.75%, 18.93%, 17.94%, 16.43%, 14.42%, 15.58%, 13.23%, and 17.12% for intermittent load conditions of 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, and 100%. A simultaneous decrease in smoke and BSEC is obtained, with a little penalty in NOx emissions at optimal conditions. RSM optimization with a desirability level of 97.9% was conducted over three trials for authentication using ANN. Based on the results, ANN predicts all the replies with R > 0.96. The experimental corroboration of the predicted variables of the optimized map for 50% load has an error between 1.40% and 4.95%, which are within the acceptable range.