Innovative conceptional approach to quantify the potential benefits of gasoline-methanol blends and their conceptualization on fuzzy modeling

Restricted fossil-based petroleum fuel resources and a raising fuel utilization direction have produced significant economic and ecological issues. The current article exhibits a robust model of using the innovative conceptional approach to quantify the potential benefits from gasoline-methanol blends utilizing a Fuzzy model based on real experimental data. Methanol has several merits to be an appealing gasoline fuel surrogate. The compositions of gasoline utilized in the current study were gasoline Fisher-Tropsh samples (GFT), including GFT-100, GFT-95, GFT-90, GFT-85, GFT-80, GFT-75, GFT-70, GFT-65, and GFT-60 with a methanol mass fraction of 0%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, and 40% by weight. Additionally, antiknock combustion characteristics of gasoline-methanol blends, involving research octane number (RON) and motor octane number (MON) at different percentages were investigated. The results showed that the established Fuzzy logic model is well matching the real experimental results to a great grade, presenting the trustworthiness of the Fuzzy logic model. Finally, the results reported that a low per-centage of methanol blends is preferable to maximize the efficiency and exhaust emissions of motor gasoline engines without altering the material structure.(c) 2022 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

Automated summary

This article presents a fuzzy logic model based on experimental data to quantify the potential benefits of gasoline-methanol blends. The study finds that a low percentage of methanol blends can maximize the efficiency and exhaust emissions of gasoline engines without altering the material structure.