• Journal of Biosystems Engineering
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• v.35 no.2
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• pp.69-76
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• 2010

This study was conducted to develop an index of fuel consumption to rate agricultural tractors by their fuel efficiencies. The fuel consumption index consisted of two components: basic and operational indexes. The basic index is to consider an average amount of fuel consumed by engine when it transmits 20 and 100% of the rated power. The operational index is to consider the fuel consumed by tractor for typical field operations: plowing, rotavating, and the remains. The equations and procedures to obtain these indexes were proposed. The method and fuel consumption rate to classify tractors into 5 grades were also proposed. The best 15% of the tractor models were rated as the first grade, 20% as the second grade, 30% as the third grade, 20% as the fourth grade, and 15% as the fifth grade in order of fuel efficiency. Using the fuel consumption index, the classification was conducted on 143 tractor models tested at the National Institute of Agricultural Engineering from 2000 to 2007. The proposed 5-grade system of classification using the fuel consumption index could be used to rate the fuel efficiency of 20-100 kW tractor models produced over past 10 years in Korea.

• 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 Society of Mechanical Technology
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• v.13 no.4
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• pp.157-164
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• 2011

Hybrid car can improve fuel efficiency using a power of motor that is generated during constant-speed or deceleration driving. The motor is located between engine and transmission. But, when voltage of main battery is low, fuel efficiency is low because the voltage can't run the motor. In this situation, this study observed fuel efficiency when using solar cell for assistance power. In order to verify a fuel consumption of hybrid car equipped solar cell for assistance power, the car was tested downtown driving. As hybrid car was equipped solar cell for assistance, fuel consumption was reduced 8.35 % at running air conditioner. And, at air conditioner doesn't work, fuel consumption was reduced 6.88 %. This point of view, CO2 is expected to reduce in similar proportion.

• Journal of Institute of Convergence Technology
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• v.3 no.2
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• pp.57-60
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• 2013

The purpose of this study is to analysis of how to calculate fuel efficiency in major development countries (U.S. and Europe) and energy consumption formular derivation of domestic CNG fuel and prove by vehicle test. The formula of fuel consumption is different in mpg(mile per gallon), l/100km, and km/l each countries. CNG fuel has a significant impact on fuel density, composition, and Hydro-Carbon ratio. So, this study how to measurement and calculation procedures of CNG gaseous fueled vehicle energy consumption rate.

• Journal of the Korean Institute of Gas
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• v.13 no.5
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• pp.1-6
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• 2009

This paper presents the fuel consumption effects of LPG vehicle depending on the atmospheric temperature, LP gas leakage of vaporizer, viscosity of engine oil and engine load conditions. The fuel consumption test results show that when the temperature of engine temperature rises, the fuel consumption efficiency increases in general. The fuel consumption efficiency for an atmosphere temperature of $24.2^{\circ}C$ is 13.6% high compared to that of $1^{\circ}C$. No leak vaporizer on fuel consumption efficiency is 5.3% high compared to that of the LP gas leak vaporizer. The fuel economy of new engine oils is just 1.1% high compared to that of used oils with a LPG vehicle mileage of 9,500km. This is not an influential factor compared with an atmospheric temperature and a LP gas leakage. The more important factors on the fuel consumption efficiency are driving conditions such as a rapid braking, abrupt start and fast acceleration. The test results indicate that the normal start is 32.3% high compared to that of an abrupt start and the fast acceleration is 10.8% high compared with that of an abrupt start. And the fuel consumption efficiency for a rapid braking is 18.3% higher than that of an abrupt start. These indicate that the driving condition is very important to reduce the fuel consumption rate.

• Journal of Climate Change Research
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• v.7 no.2
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• pp.177-184
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• 2016

Recently, the need for technology development of commercial vehicle fuel consumption has emerged. Fuel economy improvement of transport equipment and transportation efficiency, and increasing attention to the logistics cost reduction measures. Increasing attention to the logistics cost reduction measures by fuel economy improvement of transport equipment and transportation efficiency. In this study, we have installed aerodynamic reduction device (side skirt, boat tail) to 14.5 ton cargo trucks and 45 ft tractor-trailers. And the fuel consumption was compared installed before and after. Fuel economy assessment for the aerodynamic reduction value device was tested by modifying the SAE J1321 Joint TMC/SAE Fuel Consumption Test Procedure - Type II test in according domestic situation. Greenhouse gas reductions were calculated in accordance with the scenario, including fuel consumption test results. When the 14.5 ton cargo trucks has been equipped with side skirts and boat tail, it confirmed the improvement in fuel efficiency of 4.72%. One Heavy-duty truck's the annual greenhouse gas reductions value are $6.86ton\;CO_2\;eq$. And if applying the technology to more than 50% of registered 15 ton trucks, greenhouse gas reductions are calculated as $686,826ton\;CO_2\;eq./yr$.

• Plant Journal
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• v.12 no.3
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• pp.39-45
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• 2016

Each of fuel consumption per hour was measured at the 320 MW and 380 MW generator output while changing mixing ratio of bio fuel oil to 50%, 80% and 100%. Fuel consumption per hour was increased from 11.0% to 20.4% as mixing ratio of bio fuel oil was changed from 50% to 100% at the 320 MW generator output comparing with fuel consumption per hour in case of bunker-C oil single firing. Fuel consumption per hour was also increased from 12.0% to 21.1% as mixing ratio of bio fuel oil was changed from 50% to 100% at the generator output 380 MW. Furthermore, it was confirmed that plant efficiency was decreased as mixing ratio of bio fuel oil was increased from 50% to 100% as a result that plant efficiency was calculated using the measured fuel consumption per hour, the generator output and the gross heating value.

• Journal of Ocean Engineering and Technology
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• v.37 no.5
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• pp.181-189
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• 2023

The fuel consumption of marine diesel engines holds paramount importance in contemporary maritime transportation and shapes energy efficiency strategies of ocean-going vessels. Nonetheless, a noticeable gap in knowledge prevails concerning the influence of ship hull conditions and propeller roughness on fuel consumption. This study bridges this gap by utilizing artificial intelligence techniques in Matlab, particularly convolutional neural networks (CNNs) to comprehensively investigate these factors. We propose a time-series prediction model that was built on numerical simulations and aimed at forecasting ship hull and propeller conditions. The model's accuracy was validated through a meticulous comparison of predictions with actual ship-hull and propeller conditions. Furthermore, we executed a comparative analysis juxtaposing predictive outcomes with navigational environmental factors encompassing wind speed, wave height, and ship loading conditions by the fuzzy clustering method. This research's significance lies in its pivotal role as a foundation for fostering a more intricate understanding of energy consumption within the realm of maritime transport.

• Journal of the Korean Applied Science and Technology
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• v.35 no.3
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• pp.667-675
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• 2018

Increasing emissions regulations and demand of high-efficiency cars that travels a lot of distance with less fuel, there is growing interest in Energy Consumption Efficiency. Korean energy consumption efficiency compute combined Fuel Economy by driven city & highway driving mode and present final Energy Consumption Efficiency as using 5-cycle correction formula. Energy consumption efficiency is computed Carbon-balance-method, when used burning fuel play a key role in vehicle performance & Energy Consumption Efficiency. In Korea, vehicle fuel is circulate by Petroleum and Petroleum Alternative Business Act, there is property difference in quality standard because petroleum sector's refine method or type of crude oil. It does not appear a big difference according to fuel, because it sets steady quality standard, it may affect the performance of automobile. Thus, in research We purchase a few diesel fuel which circulated in the market in summer season though directly-managed-gas station by petroleum sector, resolve property each of fuel, we compute Fuel Economy each of them. We analyze into change depend on applying for property as nowadays utilizing Energy Consumption Efficiency calculating formula of gasoline and diesel fuel. As result, Density each of sample fuel has a maximum difference roughly 0.9%, net heat value each of sample fuel has difference 1.6%, result of current Energy Consumption Efficiency each of sample fuel has a difference roughly 1% at city drive mode, 1.4% at highway drive mode. Result of use gasoline calculator formula shows less 6% result than nowadays utilizing Energy Consumption Efficiency calculating formula, each of sample's Energy Consumption Efficiency shows maximum roughly 1.4% result in city & highway drive mode.

• Journal of Biosystems Engineering
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• v.9 no.2
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• pp.65-73
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• 1984

While most of researches on the performance of high temperature grain dryer have dealt mainly with improving dryer capacity and drying speed during the last twenty years, energy efficiency, in fact, has not been emphasized. Current fuel supplies and energy cost have shifted the emphasis to reducing the energy consumption for grain drying while maintaining dryer capacity and grain quality. Since the energy input for drying is relatively large, the recovery and reuse of at least part of the exhaust energy can significantly reduce the total energy consumption in existing drying systems. Unilization of exhaust heat in grain dryer either through direct recycling or by a thermal coupling in heat exchanger have been subject of a number of investigators. However, very seldom research in Korea has been done in this area. Three drying tests(non-recycling, 0.22 recycle ratio, and 0.76 recycle ratio)were performed to investigate the thermal efficiency and heat loss factors of continuous flow type dryer, and to analyze the effect of recycle ratio (weight of exhaust air recycled/total weight of input air) on the energy requriements for rough rice drying. The test results showed that when the exhaust air was not recycled, the energy lost from furnace was 15.3 percent of input fuel energy, and latent and sensible heat of exhaust air were 61.4 percent and 11.2 percent respectively. The heat which was required in raising grain temperature and stored in dryer was relatively small. As the recycle ratio of exhaust air was increased, the drying rate was suddenly decreased, and thermal efficiency of the kerosene burner was also decreased. Drying test with 0.76 recycle ratio resulted in 12.4% increase in fuel consumption, and 38.4% increase in electric power consumption as compared to the non-recycled drying test. Drying test of 0.22 recycle ratio resulted in 6.8% saving in total energy consumption, 8.0% reduction in fuel consumption, and 2.5% increase in electric power consumption as compared to the non-recycled drying test.