Fuel Control System on CNG Fueled Vehicles using Machine Learning: A Case Study on the Downhill

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 when driving downhill due vacuum in intake manifold. Therefore, this article presents development of control system that accommodates road inclination angles improve efficiency. Machine learning involved work process engine speed, throttle valve position, and slope angle. The designed ensure reduced consumption vehicle operating downhill. results showed increases by 25.7% which 5ᵒ. AFR increased from 17.5 22 flow rate decreased 17.7 liters/min 13.8 promising for applying vehicles.