Fuel Consumption Using OBD-II and Support Vector Machine Model
This paper presents a method to estimate gasoline fuel consumption using the onboard vehicle information system OBD-II (Onboard Diagnoses-II). Multiple vehicles were used on a test route so that their consumption can be compared. The relationships between fuel consumption and both of the engine spee...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Journal of Robotics |
| Online Access: | http://dx.doi.org/10.1155/2020/9450178 |
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| _version_ | 1832556835438067712 |
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| author | Tamer Abukhalil Harbi AlMahafzah Malek Alksasbeh Bassam A. Y. Alqaralleh |
| author_facet | Tamer Abukhalil Harbi AlMahafzah Malek Alksasbeh Bassam A. Y. Alqaralleh |
| author_sort | Tamer Abukhalil |
| collection | DOAJ |
| description | This paper presents a method to estimate gasoline fuel consumption using the onboard vehicle information system OBD-II (Onboard Diagnoses-II). Multiple vehicles were used on a test route so that their consumption can be compared. The relationships between fuel consumption and both of the engine speed are measured in RPM (revolutions per minute), and the throttle position sensor (TPS). The relationships are expressed as polynomial equations. The method which is composed of an SVM (support vector machine) classifier combined with Lagrange interpolation, is used to define the relationship between the two engine parameters and the overall fuel consumption. The relationship model is plotted using a surface fitting tool. In the experimental section, the proposed method is tested using the vehicles on a major highway between two cities in Jordan. The proposed model gets its sample data from the engine’s RPM, TPS, and fuel consumption. The method successfully has given precise fuel consumption with square root mean difference of 2.43, and the figures are compared with the values calculated by the conventional method. |
| format | Article |
| id | doaj-art-95f174f0d99449e28ac9cfa89b53fea3 |
| institution | Kabale University |
| issn | 1687-9600 1687-9619 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Robotics |
| spelling | doaj-art-95f174f0d99449e28ac9cfa89b53fea32025-02-03T05:44:15ZengWileyJournal of Robotics1687-96001687-96192020-01-01202010.1155/2020/94501789450178Fuel Consumption Using OBD-II and Support Vector Machine ModelTamer Abukhalil0Harbi AlMahafzah1Malek Alksasbeh2Bassam A. Y. Alqaralleh3Department of Computer Science, Alhussien Bin Talal University Ma’an, Ma’an, JordanDepartment of Computer Science, Alhussien Bin Talal University Ma’an, Ma’an, JordanDepartment of Computer Science, Alhussien Bin Talal University Ma’an, Ma’an, JordanDepartment of Computer Science, Alhussien Bin Talal University Ma’an, Ma’an, JordanThis paper presents a method to estimate gasoline fuel consumption using the onboard vehicle information system OBD-II (Onboard Diagnoses-II). Multiple vehicles were used on a test route so that their consumption can be compared. The relationships between fuel consumption and both of the engine speed are measured in RPM (revolutions per minute), and the throttle position sensor (TPS). The relationships are expressed as polynomial equations. The method which is composed of an SVM (support vector machine) classifier combined with Lagrange interpolation, is used to define the relationship between the two engine parameters and the overall fuel consumption. The relationship model is plotted using a surface fitting tool. In the experimental section, the proposed method is tested using the vehicles on a major highway between two cities in Jordan. The proposed model gets its sample data from the engine’s RPM, TPS, and fuel consumption. The method successfully has given precise fuel consumption with square root mean difference of 2.43, and the figures are compared with the values calculated by the conventional method.http://dx.doi.org/10.1155/2020/9450178 |
| spellingShingle | Tamer Abukhalil Harbi AlMahafzah Malek Alksasbeh Bassam A. Y. Alqaralleh Fuel Consumption Using OBD-II and Support Vector Machine Model Journal of Robotics |
| title | Fuel Consumption Using OBD-II and Support Vector Machine Model |
| title_full | Fuel Consumption Using OBD-II and Support Vector Machine Model |
| title_fullStr | Fuel Consumption Using OBD-II and Support Vector Machine Model |
| title_full_unstemmed | Fuel Consumption Using OBD-II and Support Vector Machine Model |
| title_short | Fuel Consumption Using OBD-II and Support Vector Machine Model |
| title_sort | fuel consumption using obd ii and support vector machine model |
| url | http://dx.doi.org/10.1155/2020/9450178 |
| work_keys_str_mv | AT tamerabukhalil fuelconsumptionusingobdiiandsupportvectormachinemodel AT harbialmahafzah fuelconsumptionusingobdiiandsupportvectormachinemodel AT malekalksasbeh fuelconsumptionusingobdiiandsupportvectormachinemodel AT bassamayalqaralleh fuelconsumptionusingobdiiandsupportvectormachinemodel |