• Journal of the Korean Society for Aviation and Aeronautics
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• v.22 no.4
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• pp.25-33
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• 2014

As global warming becoming an environmentally serious issue, more attention is drawn to fuel consumption which is the direct source of green house gas emission. The fuel consumption by aircraft operation is not an exception. Motivated by the societal and environmental context, this paper explains a method for estimation of aircraft fuel consumed during their flights as well as the computational process using real flight track data. Applying so-called 'Total Energy Model' along with aircraft specific parameters provided in EUROCONTROL's Base of Aircraft Data (BADA) to aircraft radar track data, we estimate fuel consumption of individual aircraft flown between Gimpo and Jeju airports. We then assess the estimation accuracy by comparing the estimated fuel consumption with the actual one collected from an airline. The computational results are quite encouraging in that the method is able to estimate the actual fuel consumption within ${\pm}6{\sim}11%$ of error margin. The limitations and possible enhancements of the method are also discussed.

• Journal of Information Processing Systems
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• v.13 no.2
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• pp.285-304
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• 2017

Big data information and pattern analysis have applications in many industrial sectors. To reduce energy consumption effectively, the eco-driving method that reduces the fuel consumption of vehicles has recently come under scrutiny. Using big data on commercial vehicles obtained from digital tachographs (DTGs), it is possible not only to aid traffic safety but also improve eco-driving. In this study, we estimate fuel consumption efficiency by processing and analyzing DTG big data for commercial vehicles using parallel processing with the MapReduce mechanism. Compared to the conventional measurement of fuel consumption using the On-Board Diagnostics II (OBD-II) device, in this paper, we use actual DTG data and OBD-II fuel consumption data to identify meaningful relationships to calculate fuel efficiency rates. Based on the driving pattern extracted from DTG data, estimating fuel consumption is possible by analyzing driving patterns obtained only from DTG big data.

• Journal of the Korean Data and Information Science Society
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• v.23 no.2
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• pp.247-256
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• 2012

Recently, estimation of greenhouse gas (GHG) emission has continuously emerged as an important global issue. This study compares various statistical methods for estimation of fuel consumption, which is necessary for calculation of GHG emission in road transportation sector. Existing methods have focused on using merely transportation fuel supply or distance traveled for calculation of fuel consumption. Estimates of GHG emission based on fuel supply, however, cannot reflect various vehicle types or model year. This study suggests and compares, from statistical point of view, several methods, which can be applied to estimate fuel consumption of each vehicle, by combining distance traveled and fuel efficiency (mileage), and total fuel consumption of all vehicles. It also suggests practical measures that can reflect vehicle types and model year to suggested methods for future research.

• Korean Journal of Computational Design and Engineering
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• v.17 no.2
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• pp.71-78
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• 2012

Recently, the ratio of fuel cost to the operational cost of a ship is increasing according to the increase of the international oil price. Thus, many studies are being made to reduce the cost; for example, a method for acquiring the sea state information, a method for estimating fuel consumption, a method for determining the ship's optimal route, and so on. However, these studies were not incorporated together and being independently made in different fields. In this study, by improving and incorporating such studies, a method for determining a ship economic route based on the acquisition of the sea state and estimation of fuel consumption was proposed. To evaluate the applicability of the proposed method, it was applied to an optimal routing problem of the ocean area including many islands. The result shows that the proposed method can yield the economic route minimizing fuel consumption.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.1
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• pp.153-161
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• 2004

A vehicle fuel economy is one of the most important issues in view of environmental regulation and customer's needs. In order to improve the vehicle fuel economy, great efforts has been carried out on the components bases. However, systematic analysis of vehicle fuel consumption is necessary for the further improvement of vehicle fuel economy. In this paper, a methodology for the breakdown of vehicle fuel consumption was studied and proposed for systematic analysis of the vehicle fuel economy. The energy equation for the vehicle power train was set up for the analysis of the vehicle fuel economy and simplified to be calculated or estimated using the measured data in a vehicle. The amount of fuel that was used in vehicle components under arbitrary driving conditions was quantified.

• International Journal of Naval Architecture and Ocean Engineering
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• v.5 no.2
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• pp.246-262
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• 2013

With increases in international oil prices, the proportion of fuel cost to the operational costs of a ship is currently increasing. To reduce fuel cost, a method for determining an economical route for a ship based on the acquisition of the sea state and the estimation of fuel consumption is proposed. The proposed method consists of three items. The first item is to acquire the sea state information in real time. The second item is to estimate the fuel consumption of a ship according to the sea state. The last item is to find an economical route for minimal fuel consumption based on the previous two items. To evaluate the applicability of the proposed method, it was applied to routing problems in various ocean areas. The result shows that the proposed method can yield economical ship routes that minimize fuel consumption. The results of this study can contribute to energy savings for environmentally friendly ships.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.3
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• pp.65-76
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• 2000

To measure the fuel consumption rate of a vehicle, a car is tested on chassis dynamometer following given driving mode. But the fuel consumption rate measured by this method may be somewhat different from that measured in on-road driving conditions. It may be due to not considering road grade in driving modes. In this study, new driving modes which include road grade are proposed, and the simulation program to estimate the real driving fuel consumption rate of a vehicle is developed. On-road car tests to verify the simulation program are carried out and the results of the simulation are analysed and compared with those of the experiments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.12
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• pp.2582-2589
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• 2011

This Paper proposed the prediction method of fuel consumption from vehicle diagnosis informations through OBD-II Interface. We assumed mass air flow (MAF), shor-term fuel trim (STFT), and long-term fuel trim (LTFT) had a relationship with fuel consumption. We got the output as fuel-consumption from MAF, STFT, and LTFT as input variables. We had modelling as combustion reaction equation with OBD-II data and fuel consumption data supported by automotive company in real. In order to verify the effectiveness of proposed method, 5 km real road-test was performed. The results showed that the proposed method can estimate precisely the fuel consumption from vehicle data.

• International Journal of Highway Engineering
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• v.13 no.4
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• pp.167-175
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• 2011

Evaluation of fuel consumption for the various road condition and vehicle type is necessary to perform the economic analysis of road construction which is important for the efficient design and management of road. Economic analysis of road should consider the social cost which can be divided into agency cost including initial construction expense, maintenance cost, and so on, and user cost consisting of vehicle operating cost, congestion cost, etc. Since vehicle operating cost depends on the traffic volume, fuel consumption that is a major part of vehicle operating cost will change by traffic volume as well. Fuel consumption is significantly affected by vehicle speed and road condition, especially the roughness. Thus, fuel consumption should be evaluated in terms of road condition, which is not currently considered. In this study, the estimation model of fuel consumption for the passenger cars in Korea has been developed by considering the road condition. First, the relationship between vehicle speed and fuel consumption that is used to calculate the vehicle operating cost for investment evaluation of transportation facility and the initial feasibility study of road construction was investigated. Second, with the consideration of road roughness, fuel consumption of the passenger car was measured. From the measurement, it was found that fuel consumption increased by $80m{\ell}$ per 100km driving as the roughness increased by 1m/km. Therefore, it is recommended that for the economic analysis of road design and management, the fuel consumption should be a function of road roughness.

• Journal of Advanced Navigation Technology
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• v.27 no.5
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• pp.649-657
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• 2023

ICAO adopted the Carbon Offsetting and Reduction Scheme for International Aviation (CORSIA) at the 39th General Assembly in 2016, and 115 countries, including South Korea, expressed their intention to participate in CORSIA as of January 1, 2023. Since carbon generated in the aviation industry is mainly caused by greenhouse gases emitted from aircraft engines, fuel consumption must be reduced to reduce carbon emissions. Prior research, such as simulation, is essential to predict the effectiveness of each plan and to make decisions about its implementation. High-quality data is needed to derive accurate results, but it has been difficult to secure actual fuel consumption data, as they are considered to be classified airline data. Therefore, in this paper, after establishing a model that estimates fuel consumption based on actual fuel consumption data, the model is to be advanced to improve its accuracy.