Optimizing CI Engine Ethanol Fuel Induction Techniques Using the AHP-PROMETHEE II Hybrid Decision Model

Abstract

Ethanol along with nanoparticles stands out as a promising alternative in the pursuit of environmentally sustainable fuel options, offering a potential solution to the dual challenge of curbing NOx and PM/soot emissions while optimizing engine performance in compliance with stringent pollution regulations for compression ignition (CI) engines. The research study aims to optimize ethanol fuel induction techniques for CI engines. It utilizes a hybrid decision-making approach that integrates the analytic hierarchy process- AHP- for problem structuring and the derivation of preference weights. Subsequently, the preference ranking organization method for enrichment evaluations-PROMETHEE II is applied to assess and rank the existing alternatives. The study entails a methodical assessment of diverse ethanol induction methods across varying engine load ranges, considering multiple criteria including engine performance, emissions, combustion behavior, and exhaust after-treatment efficiency. Hybrid AHP-PROMETHEE II model provides criteria weights and ranks ethanol induction techniques and fuel blends across low, medium, and high engine loads for decision-making. It ensures that the method chosen aligns with goals, such as reducing NOx and soot emissions, optimizing engine performance, enhancing combustion, and minimizing exhaust after-treatment costs for CI engines. According to the research findings, the hybrid AHP-PROMETHEE II model identifies the CI engine operating at medium load with ethanol blending (DE10) and without the use of nanoparticles as the preferred choice. Additionally, AHP-PROMETHEE II (AHP derived criteria weights) and PROMETHEE II (direct rating derived criteria weights) models, suggested DE10 with nanoparticle (DE10_NP) using blending technique at low load and combined blending-fumigation technique with nanoparticles at high load. However, at medium load, PROMETHEE II recommends DE10_NP, while AHP-PROMETHEE II recommends DE10 blending technique. To assess the performance and reliability of this model, the consistency ratio and Spearman's rank correlation coefficient indices were computed, yielding values of 0.05 and 0.59, respectively. Both indices fall below the predetermined threshold limits, indicating a high level of consistency of the model.