Fuel Consumption Using OBD-II and Support Vector Machine Model

被引:19
作者
Abukhalil, Tamer [1 ]
AlMahafzah, Harbi [1 ]
Alksasbeh, Malek [1 ]
Alqaralleh, Bassam A. Y. [1 ]
机构
[1] Alhussien Bin Talal Univ Maan, Dept Comp Sci, Maan, Jordan
关键词
VEHICLE; OPTIMIZATION; BEHAVIOR; HYBRID; ENERGY;
D O I
10.1155/2020/9450178
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
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.
引用
收藏
页数:9
相关论文
共 23 条
[1]   Government policy and the development of electric vehicles in Japan [J].
Åhman, M .
ENERGY POLICY, 2006, 34 (04) :433-443
[2]   A new method for collecting vehicle behaviour in daily use for energy and environmental analysis [J].
Alessandrini, A. ;
Filippi, F. ;
Orecchini, F. ;
Ortenzi, F. .
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING, 2006, 220 (D11) :1527-1537
[3]   How does driving behavior change when following an eco-driving car? [J].
Ando, Ryosuke ;
Nishihori, Yasuhide .
STATE OF THE ART IN THE EUROPEAN QUANTITATIVE ORIENTED TRANSPORTATION AND LOGISTICS RESEARCH, 2011: 14TH EURO WORKING GROUP ON TRANSPORTATION & 26TH MINI EURO CONFERENCE & 1ST EUROPEAN SCIENTIFIC CONFERENCE ON AIR TRANSPORT, 2011, 20
[4]  
Araújo R, 2012, 2012 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV), P1005, DOI 10.1109/IVS.2012.6232304
[5]  
Cengel Y.A., 2002, SEA, V1000, P8862
[6]   The state of the art of electric, hybrid, and fuel cell vehicles [J].
Chan, C. C. .
PROCEEDINGS OF THE IEEE, 2007, 95 (04) :704-718
[7]  
Chen Shi-Huang., 2015, Proceedings ofthe InternationalMultiConference ofEngineers and Computer Scientists, V1, P18
[8]   SUPPORT-VECTOR NETWORKS [J].
CORTES, C ;
VAPNIK, V .
MACHINE LEARNING, 1995, 20 (03) :273-297
[9]   Independent driving pattern factors and their influence on fuel-use and exhaust emission factors [J].
Ericsson, E .
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT, 2001, 6 (05) :325-345
[10]   Optimizing route choice for lowest fuel consumption - Potential effects of a new driver support tool [J].
Ericsson, Eva ;
Larsson, Hanna ;
Brundell-Freij, Karin .
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2006, 14 (06) :369-383