In general, diesel engines get better fuel mileage when compared with gasoline engines. However, only very recently, modern technologies have significantly improved such engines. Įarlier, non-spark-ignition engines (diesel) were known for their weakness in terms of emissions and reliability. Fuel cell electric vehicles (FCVs) such as hydrogen cells is one more types that is either used to generate power using hydrogen combustion engine which moves the vehicle or indirectly generating electricity to power up an electric motor. For the past decade, the Japanese government has been urging Japan’s automotive manufacturers to increase the development work spent on battery-powered electric vehicles (EVs) and hybrid electric vehicles (HEVs). Worldwide, governments are imploring for more efficient vehicles therefore, there have been outstanding advancements in the use of alternative and low emission fuels such as hydrogen combustion cells. Moreover, the high costs of oil, together with the rising worries about environmental and atmospheric pollution, has forced automotive manufacturers to the development and marketing of energy efficient vehicles, by adopting strategies such as (i) designing more efficient small displacement engines, (ii) reducing weight and coefficient of drag of the vehicle, (iii) usage of low profile tires to minimize rolling resistance, (iv) adding an electric powertrain along with the conventional fuel engine, etc. This evolving problem has urged government agencies and decision-makers to set regulations and standards on efficiency and low emissions. Over the past few years, automotive manufactures have been concerned about reducing emissions and the overall utilization of fuel resources that is associated with the transportation industry. 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. The proposed model gets its sample data from the engine’s RPM, TPS, and fuel consumption. In the experimental section, the proposed method is tested using the vehicles on a major highway between two cities in Jordan. The relationship model is plotted using a surface fitting tool. 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 relationships are expressed as polynomial equations. The relationships between fuel consumption and both of the engine speed are measured in RPM (revolutions per minute), and the throttle position sensor (TPS).
Multiple vehicles were used on a test route so that their consumption can be compared. This paper presents a method to estimate gasoline fuel consumption using the onboard vehicle information system OBD-II (Onboard Diagnoses-II).