Investigating Fuel Adulteration Using Arduino as an Engine Protection Device (EPD)
Abstract
This study explores the potential application of an Arduino-based engine protection device (EPD) for detecting tainted gasoline and engine protection. Fuel that has been tampered with can seriously harm engines, raising maintenance costs and lowering fuel efficiency. To look for any irregularities that would indicate fuel adulteration, an Arduino-based EPD can be programed to monitor metrics, including fuel flow rate, temperature, pressure, and quality. However, the precision and sensitivity of the employed sensors, the dependability and toughness of the Arduino platform, and the caliber of the device's programing and calibration will all affect how well an Arduino-based EPD detects gasoline adulteration. In conclusion, with an average mean detection time of 35 s and the ability to find adulteration levels of adulterants in fuel in less than a minute, the use of an Arduino-based EPD to detect fuel adulteration shows promise as a potentially effective and cost-effective solution for protecting engines from damage caused by contaminated fuel. The efficacy of an Arduino-based EPD for detecting gasoline adulteration under various operating circumstances and with various types of fuel needs to be further investigated and tested.
Keywords: Arduino, fuel adulteration, engine protection device, sensor, fuel flow rate.
Full Text:
PDFReferences
BULBUL A. A.-M., RASHED A. N. Z., EL-HAGEEN H. M., and ALATWI A. M. Design and numerical analysis of an extremely sensitive PCF-based sensor for detecting kerosene adulteration in petrol and diesel. Alexandria Engineering Journal, 2021, 60(6): 5419–5430. https://doi.org/10.1016/j.aej.2021.04.041
VEMPATAPU B. P., & KANAUJIA P. K. Monitoring petroleum fuel adulteration: A review of analytical method. TrAC Trends in Analytical Chemistry, 2017, 92: 1-11. https://doi.org/10.1016/j.trac.2017.04.011
RAWAT V., NADKARNI V., and KALE S. N. Highly sensitive electrical metamaterial sensor for fuel adulteration detection. Defence Science Journal, 2016, 66(4): 421-424. https://doi.org/10.14429/dsj.66.10217
YADAV G. C., PRAKASH S., SHARMA G., KUMAR S., and SINGH V. Detection of kerosene adulteration in automobile fuel with a novel metal clad planar waveguide. Optics & Laser Technology, 2019, 119: 105589. https://doi.org/10.1016/j.optlastec.2019.105589
EJOFODOMI O., & OFUALAGBA G. Automated Volume Measurement, Adulteration Detection, and Tracking of Petroleum Products. Proceedings of the SPE Nigeria Annual International Conference and Exhibition, Virtual, 2020. https://doi.org/10.2118/203694-MS
CHIKWE T. N., & ONOJAKE M. C. Adulterating the quality of automotive gas oil using dual purpose kerosene: Effects on compression ignition engines, humans and environment. Chemistry International, 2020, 6(2): 75-82. https://doi.org/10.5281/zenodo.3361114
OSUEKE C. O., & OFONDU I. O. Fuel adulteration in Nigeria and its consequences. International Journal of Mechanical & Mechatronics Engineering IJMME-IJENS, 2011, 11(4): 34–40.
YADAV, Sh. R., MURTHY V. K., MISHRA D., and BARAL B. Estimation of petrol and diesel adulteration with kerosene and assessment of usefulness of selected automobile fuel quality test parameters. International Journal of Environmental Science & Technology, 2005, 1: 253–255. https://doi.org/10.1007/BF03325839
BOADU K. O. Effects of Adulteration on Diesel Oil with Kerosene Fuel in Ghana. Journal of Applied Sciences and Environmental Management, 2019, 23(7): 1195-1200. https://doi.org/10.4314/jasem.v23i7.1
VEMPATAPU B. P., TRIPATHI D., KUMAR J., and KANAUJIA P. K. Determination of kerosene as an adulterant in diesel through chromatography and high-resolution mass spectrometry. SN Applied Sciences, 2019, 1: 614. https://doi.org/10.1007/s42452-019-0637-7
JIN Y.-S., KIM G.-J., SHON C.-H., JEON S.-G., and KIM J.-Il. Analysis of Petroleum Products and Their Mixtures by Using Terahertz Time Domain Spectroscopy. Journal of the Korean Physical Society, 2008, 53(4): 1879-1885. https://doi.org/10.3938/jkps.53.1879
YAKASAI I. K., ABAS P. E., and BEGUM F. Proposal of novel photonic crystal fibre for sensing adulterated petrol and diesel with kerosene in terahertz frequencies. IET Optoelectronics, 2020, 14(5): 319-326. https://doi.org/10.1049/iet-opt.2019.0141
COHEN A. J., ANDERSON H. R., OSTRO B., PANDEY K. D., KRZYZANOWSKI M., KÜNZLI N., GUTSCHMIDT K., POPE III C. A., ROMIEU I., SAMET J. M., and SMITH K. R. (2004). Urban air pollution. In: EZZATI M., LOPEZ A. D., RODGERS A., and MURRAY C. J. L. (eds.) Comparative Quantification of Health Risks: Global and Regional Burden of Disease Attributable to Selected Major Risk Factors. World Health Organization, 2004: 1353-1433. https://www.jstor.org/stable/pdf/resrep27829.22.pdf
LAM N. L., SMITH K. R., GAUTHIER A., and BATES M. N. Kerosene: A Review of Household Uses and their Hazards in Low- and Middle-Income Countries. Journal of Toxicology and Environmental Health, Part B, 2012, 15(6): 396-432. https://doi.org/10.1080/10937404.2012.710134
BAHARI M. S., CRIDLLE W. J., and THOMAS J. D. R. Determination of the adulteration of petrol with kerosine using a rapid phase-titration procedure. Analyst, 1990, 115(4): 417-419. https://doi.org/10.1039/AN9901500417
GUPTA A., & SHARM R. K. A New Method for Estimation of Automobile Fuel Adulteration. In: VILLANYI V. (ed.) Air Pollution. IntechOpen Limited, London, 2010. https://doi.org/10.5772/10054
MISHRA V., JAIN S. C., SINGH N., PODDAR G. C., and KAPUR P. Fuel Adulteration Detection Using Long Period Fiber Grating Sensor Technology. Indian Journal of Pure & Applied Physics, 2008, 46: 106-110. http://csioir.csio.res.in/195/
VERMA R. K., SUWALKA P., and YADAV J. Detection of adulteration in diesel and petrol by kerosene using SPR based fiber optic technique. Optical Fiber Technology, 2018, 43: 95-100. http://dx.doi.org/10.1016/j.yofte.2018.04.011
PATHAK A. K., GANGWAR R. K., PRIYADARSHINI P., and SINGH V. K. A robust optical fiber sensor for the detection of petrol adulteration. Optik, 2017, 149: 43-48. https://doi.org/10.1016/j.ijleo.2017.09.036
YAKASAI I., ABAS P. E., KAIJAGE S. F., CAESARENDRA W., and BEGUM F. Proposal for a Quad-Elliptical Photonic Crystal Fiber for Terahertz Wave Guidance and Sensing Chemical Warfare Liquids. Photonics, 2019, 6(3): 78. https://doi.org/10.3390/photonics6030078
HABIB M. A., ANOWER M. S., ABDULRAZAK L. F., and REZA M. S. Hollow core photonic crystal fiber for chemical identification in terahertz regime. Optical Fiber Technology, 2019, 52: 101933. http://dx.doi.org/10.1016/j.yofte.2019.101933
RANA S., KANDADAI N., and SUBBARAMAN H. A Highly Sensitive, Polarization Maintaining Photonic Crystal Fiber Sensor Operating in the THz Regime. Photonics, 2018, 5(4): 40. https://doi.org/10.3390/photonics5040040
SULTANA J., ISLAM M. S., AHMED K., DINOVITSER A., NG B. W., and ABBOTT D. Terahertz detection of alcohol using a photonic crystal fiber sensor. Applied Optics, 2018, 57(10): 2426-2433. https://doi.org/10.1364/ao.57.002426
ISLAM M. S., SULTANA J., AHMED K., ISLAM M. R., DINOVITSER A., NG B. W.-H., and ABBOTT D. A Novel Approach for Spectroscopic Chemical Identification Using Photonic Crystal Fiber in the Terahertz Regime. IEEE Sensors Journal, 2018, 18(2): 575–582. https://doi.org/10.1109/jsen.2017.2775642
PUTRA A., NURSALIM J., ARIBOWO A., and TJAHYADI H. Arduino-based Vehicle Fuel Theft Detector System. Jurnal Teknologi Informasi dan Pendidikan, 2020, 13(2): 55-61. https://doi.org/10.24036/tip.v13i2.340
EJILAH I. R., OLORUNNISHOLA A. A. G., and ENYEJO L. A. A Comparative Analysis of the Combustion Behavior of Adulterated Kerosene Fuel Samples in a Pressurized Cooking Stove. Global Journal of Research in Engineering-A: Mechanical & Mechanics Engineering, 2013, 13(6): 34-44. https://globaljournals.org/GJRE_Volume13/4-A-Comparative-Analysis-of-the-Combustion.pdf
BAMIMORE I., & AJAGBE S. A. Design and implementation of smart home nodes for security using radio frequency modules. International Journal of Digital Signals and Smart Systems, 2020, 4(4): 286-303. https://dx.doi.org/10.1504/IJDSSS.2020.111009
AJAGBE S. A., ADIGUN M. O., AWOTUNDE J. B., OLADOSU J. B., and OGUNS Y. J. Internet of Things Enabled Convolutional Neural Networks: Applications, Techniques, Challenges, and Prospects. In: NAVED M., DEVI V. A., GAUR L., and ELNGAR A. A. (eds.) IoT-enabled Convolutional Neural Networks: Techniques and Applications. River Publishers, New York, 2023. https://doi.org/10.1201/9781003393030-2
Refbacks
- There are currently no refbacks.
