4.6 Article Proceedings Paper

Modeling, polynomial regression, and artificial bee colony optimization of SI engine performance improvement powered by acetone-gasoline fuel blends

Journal

ENERGY REPORTS
Volume 9, Issue -, Pages 55-64

Publisher

ELSEVIER
DOI: 10.1016/j.egyr.2022.12.102

Keywords

SI engine performance; Optimization; Acetone-gasoline; Polynomial regression; Alternative fuel; Artificial bees colony algorithm

Categories

Ask authors/readers for more resources

This study aims to enhance the performance of SI engines by using acetone-gasoline mixtures and applying the Artificial Bees Colony Algorithm (ABC) to determine the optimal blends and engine speed. Experimental results show that adding acetone improves the overall performance of the gasoline engine, with the AC10 blend and engine speeds of 2889 rpm and 2769 rpm achieving the best results in terms of engine torque and thermal efficiency.
The current study attempts to improve the performance of SI engines by employing two alternative acetone-gasoline mixtures. This investigation applies the Artificial Bees Colony Algorithm (ABC) to determine the optimum acetone-gasoline blends and engine speed to increase engine performance further and minimize fuel consumption. The SI engine performance of one-cylinder, four-stroke powered by neat gasoline fuel (AC0), 5% of acetone by volume (AC5), and 10 % of acetone by volume (AC10) has been investigated experimentally. Tests were carried out at speed rates from 1,000 to 3,600 rpm. The gasoline engine was integrated into an eddy-current dynamometer to evaluate the performance indexes. It was revealed that the overall performance of the gasoline engine is enhanced when acetone is blended with gasoline. The AC10 exhibited better engine brake torque (BT) and brake thermal efficiency (BTE) than pure gasoline, with 4.39 % and 6.9 %, respectively. According to the optimization findings, a 10% acetone concentration and engine speeds of 2889 rpm and 2769 rpm produced the best results in terms of BT and BTE, which were 7.776 N.m and 29.992%, respectively. However, at 2401 rpm of engine speed, a minimum BSFC of 0.2986 was reached without acetone. This result demonstrates that the ABC algorithm can precisely forecast the optimal position in terms of engine effectiveness and fuel consumption. (c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available