• 한국전자통신학회논문지
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• 제13권3호
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• pp.555-560
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• 2018

본 논문에서는 실차기반의 전기자동차 진단시스템을 활용한 교육용 콘텐츠에 관한 연구를 대상으로 한다. 먼저, 최근 늘어나고 있는 전기자동차의 이해를 돕기 위해 전기자동차를 구성하고 있는 핵심 부품과 전기자동차의 주행모드와 동작원리에 대해서 기술한다. 또한 전기자동차 시험 장치와 특성분석을 위한 진단시스템을 구현하였으며 실차기반의 실험 수행을 통해 주행모드에 따라 나타나는 특성을 분석하였다.

• 대한교통학회지
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• 제26권6호
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• pp.39-47
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• 2008

최근 IT 기술의 비약적인 발전으로 위성 및 지상파 DMB 서비스가 본격적으로 시작되면서 운전 중 DMB를 시청하거나 문자나 동영상으로 제공되는 교통정보를 시청하기 위해 차량 내 DMB를 설치하는 사례가 급속하게 증가하고 있다. 그러나 운전중 DMB 시청은 운전중 음식섭취, 라디오 조작, 휴대폰 사용 등과 유사하게 운전자의 시지 각 및 인지적 주의를 분산시켜 안전운전에 방해를 초래할 것이다. 하지만 이와 관련한 국내외의 실증적인 연구가 부족할 뿐만 아니라 운전행동에 있어서 구체적으로 어떻게 영향을 주는지도 밝혀지지 않았다. 따라서 본 연구에서는 국내 운전자들을 대상으로 운전 중 DMB 시청이 운전행동에 미치는 영향을 살펴보기 위하여 차량시뮬레이터를 이용한 실험연구를 실시하였다. 실험설계는 피험자내 실험설계를 하였으며 실험참여자들은 두 조건(즉, 운전 중 DMB를 시청하지 않는 조건과 DMB를 시청하는 조건) 모두에서 주행실험을 수행하였다. 연구결과, 운전 중 DMB를 시청하는 조건이 시청하지 않는 조건에 비해서 목적지에 도달하는 소요시간이 더 걸렸으며 가속 및 감속 페달을 급하게 조작하였을 뿐만 아니라 조향휠 편차가 크게 나타나 주행안전성을 떨어뜨리는 것으로 나타났다. 부가적으로, DMB 조작 조건(즉, 키패드 조건, 터치패드 조건, 리모컨 조건)에 따른 운전행동 차이도 살펴보았다. 마지막으로 본 연구의 제한점 및 함의에 대하여 논의하였다.

• 전력전자학회논문지
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• 제25권2호
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• pp.79-86
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• 2020

This study examines the power generation characteristics of a vehicle rooftop photovoltaic module with urban driving conditions. Actual test data with an illuminometer and a thermometer were used to analyze the power generation characteristics of the vehicle rooftop photovoltaic module. In addition, the power generation characteristics were analyzed in terms of urban driving conditions, irradiance, ambient temperature, and photovoltaic module temperature. This study also analyzes the power generation characteristics of the vehicle rooftop photovoltaic module with urban driving conditions through a wavelet transform filtering method. The power generation characteristics of the vehicle rooftop photovoltaic module with urban driving conditions depend on the change in irradiance rather than that in photovoltaic module temperature.

• 한국분무공학회지
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• 제19권1호
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• pp.40-46
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• 2014

Recently rise in oil prices feet the burden on not only diesel vehicle driver but also LPG vehicle driver, and get interested in various way to reduce fuel costs. In this study discuss on exhaust emissions characteristics on driving cycle mode and ignition advance condition change of CNG/LPLI Bi-Fuel vehicle. Experimental test was performed by changing the conditions of fuel (LPG/CNG), spark advance (Base, $10^{\circ}CA$, $15^{\circ}CA$), and driving mode (FTP-75, HWFET, and NEDC). In case of CO emission, in the order of CNG Base, CNG S/A10, S/A15 condition are average reduced -21%, -35%, -29% respectively compared to LPG fuel. The active emission reduction from the initial engine start, spark retard is likely to be beneficial in catalyst warm-up and improve combustion stability rather than spark advance.

• 한국자동차공학회논문집
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• 제21권6호
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• pp.123-134
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• 2013

Strengthening vehicle emission regulation is one of important policies to improve air quality in urban area. Due to the limitation of specified driving cycles for certification test to reflect real driving conditions, additional off-cycle emission regulations have been adopted in US and being developed in Europe. The driving cycles of US or Europe have been used in emission certification for Korean light-duty vehicles, but it has not been known how well the driving cycles reflect various real driving patterns in Korea. In that point of view, it is required to estimate vehicle emission based on real road driving conditions to raise the effectiveness of vehicle emission regulation in Korea. In this study, real driving emission measurements have been conducted for three Korean light-duty vehicles with PEMS. The driving routes consisted of urban, rural and motorway in Seoul and Incheon. The data have been analyzed with various averaging methods including moving averaging windows method and compared to emission limits set with emission certification modes applied to tested vehicles. The results have shown that the real driving pollutant emissions of a gasoline and a LPG vehicles have been ranged quite lower than those of emission limits on CVS-75 driving cycle. But real driving NOx of a light duty diesel vehicle has been considerably higher than emission limit of NEDC driving cycle. The higher than expected NOx emission of a diesel vehicle might be caused by different strategy to control EGR in real driving condition from NEDC driving.

• 한국자동차공학회논문집
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• 제20권6호
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• pp.61-66
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• 2012

Conventional method to transform vehicle driving condition to engine operation mode is to use vehicle road load under neutral gear and mechanical efficiency of drivetrain. But this method requires additional measurement of efficiency of drivetrain on a test rig. And this measurement is normally done at fixed speed and thus estimated accuracy of engine operation mode is not considered to be high enough. This study suggests new method to calculate engine operation mode for prescribed driving mode such as NEDC using vehicle coastdown test under gear engaged condition without measurement of mechanical efficiency of drivetrain. Coastdown test was done under neutral and gear engaged condition for comparison and also trial to extract mechanical loss of drivetrain was carried out. Calculated engine torque by conventional and newly suggested method was compared with actually measured torque of a vehicle on a chassis dynamometer during NEDC. Newly suggested method showed slightly higher accuracy of accumulated brake work during NEDC.

• 한국항만학회지
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• 제14권3호
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• pp.303-312
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• 2000

In this paper, we describe an image processing algorithm which is able to recognize the road lane. This algorithm performs to recognize the interrelation between AGV and the other vehicle. We experimented on AGV driving test with color CCD camera which is setup on the top of vehicle and acquires the digital signal. This paper is composed of two parts. One is image preprocessing part to measure the condition of the condition of the lane and vehicle. This finds the information of lines using RGB ratio cutting algorithm, the edge detection and Hough transform. The other obtains the situation of other vehicles using the image processing and viewport. At first, 2 dimension image information derived from vision sensor is interpreted to the 3 dimension information by the angle and position of the CCD camera. Through these processes, if vehicle knows the driving conditions which are lane angle, distance error and real position of other vehicles, we should calculate the reference steering angle.

• 한국자동차공학회논문집
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• 제7권7호
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• pp.136-148
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• 1999

Detailed mathematical models of hybrid drivertrain components are presented and numerical simulations are carried out to analyze the shift characteristics and to improve the driving comfortability when the hybrid drivetrain is applied at the vehicle . Theoretical results are compared with experimental ones from the dynamometer as same condition in order to prove the appropriateness of modeling . Adding the vehicle body modeling, included in the suspension and the engine mount, it is possible to predict the dynamic behavior and shift characteristics more actually when shifts are occurred by automated manual transmission(AMT). these additional results are also compared with the same simulation ones of internal combustion engined vehicle equipped conventional manual transmission. Hence, it can be expected that the hybrid vehicle with AMT has a good shift quality.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2016년도 춘계학술대회
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• pp.577-578
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• 2016

본 논문에서는 차량운행 시 일어날 수 있는 졸음운전 사고를 예방하기 위해 맥박 센서를 이용하여 차량 안전시스템 구성을 제안하였다. 제안한 차량 안전시스템은 운전자의 졸음운전 상태를 판단하여 경보를 알리고, 이를 이용하여 운전자는 돌발적인 상황이나 위험상황을 미리 인지하여 직접적인 사고 및 2차 사고를 예방 할 수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권12호
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• pp.5842-5861
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• 2019

A current autonomous vehicle determines its driving strategy by considering only external factors (Pedestrians, road conditions, etc.) without considering the interior condition of the vehicle. To solve the problem, this paper proposes "An Optimal Driving Support Strategy(ODSS) based on an Genetic Algorithm for Autonomous Vehicles" which determines the optimal strategy of an autonomous vehicle by analyzing not only the external factors, but also the internal factors of the vehicle(consumable conditions, RPM levels etc.). The proposed ODSS consists of 4 modules. The first module is a Data Communication Module (DCM) which converts CAN, FlexRay, and HSCAN messages of vehicles into WAVE messages and sends the converted messages to the Cloud and receives the analyzed result from the Cloud using V2X. The second module is a Data Management Module (DMM) that classifies the converted WAVE messages and stores the classified messages in a road state table, a sensor message table, and a vehicle state table. The third module is a Data Analysis Module (DAM) which learns a genetic algorithm using sensor data from vehicles stored in the cloud and determines the optimal driving strategy of an autonomous vehicle. The fourth module is a Data Visualization Module (DVM) which displays the optimal driving strategy and the current driving conditions on a vehicle monitor. This paper compared the DCM with existing vehicle gateways and the DAM with the MLP and RF neural network models to validate the ODSS. In the experiment, the DCM improved a loss rate approximately by 5%, compared with existing vehicle gateways. In addition, because the DAM improved computation time by 40% and 20% separately, compared with the MLP and RF, it determined RPM, speed, steering angle and lane changes faster than them.