(523d) Iot Based Fuel Adulteration Detection Using Dispersion Model and Tail Pipe Emissions
AIChE Annual Meeting
2020
2020 Virtual AIChE Annual Meeting
Topical Conference: Sensors
Applications in Chemical Sensors
Wednesday, November 18, 2020 - 8:45am to 9:00am
Over the years up-gradation to cleaner fuel aims to reduce the rising environmental pollution. Evidence
from the past states that adulteration of fuel exacerbates the problem. To cut the cost of highly taxed
improved hydrocarbon, it is usually blended up to 80% with cheaper hydrocarbon. The detection of
adulteration is to be achieved by implanting sensors within the fuel tank and the exhaust tailpipe. This
whole process will be brained by the Engine Control Unit (ECU) and the data will be transmitted to the
pollution monitoring agencies via Internet of Things (IoT) over an interval of time. The data received
from the vehicle will be modeled and analyzed on the basis of the dispersion model. The molecular
diffusion of the adulterate in the quality hydrocarbon will result in the intermixing of molecules, by
extending this study to reverse engineering, we will determine the amount of adulterate injected. The data
will be assimilated with the fuel and emission standards that will estimate the quantity and the injection
time period of the adulterate. Looking closer to the data, it can be easily estimated the adulteration cases
over a zone by analyzing the chronicle of refueling. This ensures the environmental agencies to keep track
of the adulterate hotspots. Presently various testing parameter are available such as ASTM D6730 (Gas
Chromatography), ASTM D2425(Mass Spectroscopy), ASTM D2425 (Distillation). The common
limitation of the tests available is that analysis must be performed outside the vehicle body, that will no
longer provide the chronology behind the addition of adulterant. It is estimated that when this model will
be implemented to the vehicles, it will uplift the aspect of the cleaner fuel to deliver better engine
performance with reduced emission levels. This will empower every citizen to monitor the quality of fuel
easily by accessing the data from the vehicle.
from the past states that adulteration of fuel exacerbates the problem. To cut the cost of highly taxed
improved hydrocarbon, it is usually blended up to 80% with cheaper hydrocarbon. The detection of
adulteration is to be achieved by implanting sensors within the fuel tank and the exhaust tailpipe. This
whole process will be brained by the Engine Control Unit (ECU) and the data will be transmitted to the
pollution monitoring agencies via Internet of Things (IoT) over an interval of time. The data received
from the vehicle will be modeled and analyzed on the basis of the dispersion model. The molecular
diffusion of the adulterate in the quality hydrocarbon will result in the intermixing of molecules, by
extending this study to reverse engineering, we will determine the amount of adulterate injected. The data
will be assimilated with the fuel and emission standards that will estimate the quantity and the injection
time period of the adulterate. Looking closer to the data, it can be easily estimated the adulteration cases
over a zone by analyzing the chronicle of refueling. This ensures the environmental agencies to keep track
of the adulterate hotspots. Presently various testing parameter are available such as ASTM D6730 (Gas
Chromatography), ASTM D2425(Mass Spectroscopy), ASTM D2425 (Distillation). The common
limitation of the tests available is that analysis must be performed outside the vehicle body, that will no
longer provide the chronology behind the addition of adulterant. It is estimated that when this model will
be implemented to the vehicles, it will uplift the aspect of the cleaner fuel to deliver better engine
performance with reduced emission levels. This will empower every citizen to monitor the quality of fuel
easily by accessing the data from the vehicle.