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All Journal Automotive Experiences
Ray Adhan Brieghtera
Universitas Muhammadiyah Magelang, Indonesia
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Control & Systems Engineering Electrical & Electronics Engineering Energy Materials Science & Nanotechnology Mechanical Engineering

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Fuel Control System on CNG Fueled Vehicles using Machine Learning: A Case Study on the Downhill Suroto Munahar; Muji Setiyo; Ray Adhan Brieghtera; Madihah Mohd Saudi; Azuan Ahmad; Dori Yuvenda
Automotive Experiences Vol 6 No 1 (2023)
Publisher : Automotive Laboratory of Universitas Muhammadiyah Magelang in collaboration with Association of Indonesian Vocational Educators (AIVE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/ae.8107

Abstract

Compressed Natural Gas (CNG) is an affordable fuel with a higher octane number. However, older CNG kits without electronic controls have the potential to supply more fuel when driving downhill due to the vacuum in the intake manifold. Therefore, this article presents a development of a CNG control system that accommodates road inclination angles to improve fuel efficiency. Machine learning is involved in this work to process engine speed, throttle valve position, and road slope angle. The control system is designed to ensure reduced fuel consumption when the vehicle is operating downhill. The results showed that the control system increases fuel consumption by 25.7% when driving downhill which an inclination of 5ᵒ. The AFR increased from 17.5 to 22 and the CNG flow rate decreased from 17.7 liters/min to 13.8 liters/min which is promising for applying to CNG vehicles.
Co-Authors Azuan Ahmad Dori Yuvenda Madihah Mohd Saudi Muji Setiyo Suroto Munahar