• Journal of Auto-vehicle Safety Association
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• v.10 no.3
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• pp.45-54
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• 2018

Greenhouse gas is the big issue of the whole world. So foreign countries, EU, USA, Japan, China and Korea made the policy for reducing greenhouse gas. For calculation of reduction, it is necessary to know the quantity of current greenhouse emission per year in Korea. It is not reflected real driving condition for measuring the Fuel economy and greenhouse gas. The subject of this study is to figure out the characteristics which influence on greenhouse gas in real driving condition. And final goal is applying the policy greenhouse emission reduction.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.457-467
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• 2020

Increasing environmental concerns have prompted countries around the world to tighten regulations on greenhouse gases and fuel efficiency. Research is being done using advanced driver assistance systems to improve fuel economy and for the convenience of drivers. Research on systems such as adaptive cruise control (ACC), LKAS, and AEB is active. The purpose of ACC is to control the longitudinal speed and distance of the vehicle and minimize the driver's load, which is considered useful for accident prevention. From this point of view, research has used a mathematical method of safety evaluation as a function of distances and scenarios while considering domestic road environments. A vehicle is tested with a simulation in a proposed scenario. The purpose of the analysis is to verify the functional safety of ACC by comparing the theoretical calculations using theoretical equations, the relative distances in the simulation, and an actual vehicle test. These methods are expected to enable many companies to use scenarios, formulas, and simulations as safety verification methods in the development of ACC.

• Journal of Institute of Convergence Technology
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• v.4 no.2
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• pp.67-70
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• 2014

Recently EU has been recognized that there is a difference of emission quantity between emission certification test mode and real-road driving test. Accordingly the European Commission is currently preparing to require real-road testing as part of the passenger car type-approval process in the EU. vehicle manufacturers from 2017 are expected to test new vehicles not only under laboratory conditions but also on the real-road, using PEMS equipment. Therefore the purpose of this study is to analyze the emission and Fuel Economy of CVS-75 mode test using chassis dynamometer and RDE test using PEMS equipment by PHEV passenger car.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.2
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• pp.38-46
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• 2012

This paper discusses the energy consumption for a mid-size electric vehicle(EV) under various conditions. In order to analyze which driving style is more efficient in terms of the system of the EV, we develop the electric vehicle model and apply several types of speed profiles such as different steady speeds, acceleration/deceleration, and a real world driving cycle including the elevation profile obtained from a GPS device. The results show that the energy consumption of the EV is affected by the operating efficiency of components when driving at low speed, while it depends on required power at wheels when driving at high speed. Also this paper investigates the effect of the elevation of a road and the rate of electrical braking on the energy consumption as well as the fuel economy of a conventional vehicle model under the same conditions.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.9
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• pp.133-140
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• 2016

The Ministry of Land, Infrastructure and Transport has introduced low-floor buses, which are convenient for passengers getting on and off the bus and for the handicapped. The standard bus model is 11 m long and uses compressed natural gas (CNG). However, this model has drawbacks in narrow rural road conditions such as those in farming and fishing villages and mountainous areas, as well as difficulty in refueling since CNG facilities are not readily available. In this study, running resistance values were obtained by coasting performance tests on actual roads using a Tata Daewoo LF-40 model with three different weight conditions: curb vehicle weight (CVW), half vehicle weight (HVW), and gross vehicle weight (GVW).The test methods include WHVC, NIER-06, and constant-speed driving at 60 km/h. These tests were used to measure the fuel economy of vehicles other than the target vehicles to obtain the combined fuel economy. The energy efficiency was highest in the case of CVW. In the WHVC mode, the fuel consumption rates of HVW and GVW were typically 3.5% and 12% higher than that of CVW, respectively. In constant-speed driving, the fuel efficiency of HVW was higher than that of CVW. Further research is required to analyze the exhaust gas data.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.13-20
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• 2022

It's proposed and analyzed ML(Machine Learning) models to predict vehicle FC(Fuel Consumption) in real-time. The test driving was done for a car to measure vehicle speed, acceleration, road gradient and FC for training dataset. The various ML models were trained with feature data of speed, acceleration and road-gradient for target FC. There are two kind of ML models and one is regression type of linear regression and k-nearest neighbors regression and the other is classification type of k-nearest neighbors classifier, logistic regression, decision tree, random forest and gradient boosting in the study. The prediction accuracy is low in range of 0.5 ~ 0.6 for real-time FC and the classification type is more accurate than the regression ones. The prediction error for total FC has very low value of about 0.2 ~ 2.0% and regression models are more accurate than classification ones. It's for the coefficient of determination (R²) of accuracy score distributing predicted values along mean of targets as the coefficient decreases. Therefore regression models are good for total FC and classification ones are proper for real-time FC prediction.

• Journal of Digital Convergence
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• v.17 no.11
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• pp.207-213
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• 2019

The fuel-cut coast-down driving mode is activated when the acceleration pedal is released with transmission gear engaged, and it's a default function for electronic-controlled engine of vehicles. The fuel economy becomes better because fuel injection stops during fuel-cut driving mode. A fuel-cut detection method is suggested in the study and it's based on the speed, acceleration and road gradient data from GPS sensor. It detects fuel-cut driving mode by comparing calculated acceleration and realtime acceleration value. The one is estimated with driving resistance in the condition of fuel-cut driving and the other is from GPS sensor. The detection accuracy is about 80% when the method is verified with road driving data. The result is estimated with 9,600 data set of vehicle speed, acceleration, fuel consumption and road gradient from test driving on the road of 12km during 16 minutes, and the road slope is rather high. It's easy to detect fuel-cut without injector signal obtained by connecting wire. The detection error is from the fact that the variation range of speed, acceleration and road gradient data, used for road resistance force, is larger than the value of fuel consumption data.