EXPLORING FUEL OCTANE NUMBERS: A COMPREHENSIVE ANALYSIS USING ACCELEROMETER-BASED ASSESSMENT AND STATISTICAL METRICS
Mohd Irman Hamzah , Department Of Mechanical Engineering Technology, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia Ahmad Habibah Ghani , Department Of Mechanical Engineering Technology, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, MalaysiaAbstract
This study presents a comprehensive analysis of fuel octane numbers using accelerometer-based assessment and statistical metrics. The performance of gasoline engines heavily relies on the octane number of the fuel used, which indicates its resistance to knocking. Traditional methods for measuring octane numbers are time-consuming and expensive. In this research, an innovative approach is proposed, utilizing an accelerometer to measure engine vibrations under controlled conditions. Correlation analysis and regression modeling were performed to establish the relationship between accelerometer readings and octane numbers. The results demonstrate a strong positive correlation and the development of a predictive model for estimating octane numbers based on accelerometer data. This study provides valuable insights for fuel development, engine optimization, and real-time octane number estimation.
Keywords
Fuel octane numbers, accelerometer-based assessment, statistical metrics
References
T. G. Leone, “The Effect of Compression Ration, Fuel Octane Rating and Ethanol Content on Spark-Ignition Engine Efficiency”, Environmental Science and Technology, 2015, 49 (18), pp. 10778-10789.
N. Rankovic and A. Bourhis, “Understanding Octane Number Evolution for Enabling Alternative Low RON Refinery Streams and Octane Boosters as Transportation Fuels”, Fuel, 2015, pp. 41-47.
Y. Shatnawi and M. Al-Khassaweneh “Fault Diagnosis in Internal Combustion Engines using Extension Neural Network”, IEEE Transaction on IndustryApplications, 2014, 61 (3), pp. 1434-1443.
J. Chen and R. B. Randall, “Improved Automated Diagnosis of Misfire in Internal Combustion Engines based on Simulation Models” Mechanical Systems and Signal Processing, 2015, 64-65, pp. 58-83.
J. Chen and R. B. Randall, “Intelligent Diagnosis of Bearing Knock Faults in Internal Combustion Engines using Vibration Simulation” Mechanism and Machine Theory, 2016, 104, pp. 161-176.
P. L. Mendonca, “Detection and Modelling of Incipient Failures in Internal Combustion Engine Driven Generators using Electrical Signature Analysis”, Electric Power Systems Research, 2017, 149, pp. 30-45.
M. I. Ramli, M. Z. Nuawi, S. Abdullah, M. R. M. Rasani, K.K. Seng and M. A. F. Ahmad, “Development on Simulation of Small Structure Modal Analysis Method using Piezoelectric Film Sensor”, 23rd. International Congress on Sound and Vibration, 2016, ICSV 2016, Athens, Greece.
M.Z. Nuawi, “A Study of Engine Monitoring System using Statistical Method”, Applied Mechanics and Materials, 2013, 471 (2), pp. 193-196.
A. Khadersab and S. Shivakumar, “Vibration Analysis Techniques for Rotating Machinery and its effect on Bearing Faults”, Procedia Manufacturing, 2018, 20, pp. 247-252.
S. S. Ziyad, et al. “Characterization of Polymer Material using I-KazTM Analysis Method under Impact Hammer Excitation Technique”, Journal of Applied Sciences, 2015, 15 (1), pp. 138-145.
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