• 상하수도학회지
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• 제26권6호
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• pp.851-860
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• 2012

In this study, to evaluate the abatement of runoff pollution loads by the road sweeping(cleaning), various investigations are implemented at the sample area of the highway. As the results of evaluating the removal efficiency of pollutants along road cleaning, TSS showed about 78 % of the removal efficiency and COD showed 49 % of removal efficiency through the operation of cleaning vehicle of vacuum suction method. In case of TN and TP, they showed the relatively-lower removal efficiency by 30~35 %. TSS removal efficiency along the number of cleaning appeared about 60 % in case of one time of cleaning and the additional removal effect did not appear though the number of cleaning increased to two times. With running speed of cleaning vehicle, TSS removal ratio is lessened from 60 % to 20 % when cleaning vehicle speed up to 20 km/hr from 6 km/hr. It seems that the reasons why the removal efficiencies are inversely proportional to its speed are related to the lower vacuum efficiencies and the disturbed particles on the road. In the pollutant build-up analysis, it is showed that it takes more time to the critical pollutant build-up in the shoulder than the center of the road. It is also showed that the proper cleaning cycle is recommended as 4~6 dry weather days without rainfall events.

• 융복합기술연구소 논문집
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• 제8권1호
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• pp.5-8
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• 2018

Emissions of diesel vehicles have been regulated by NEDC mode for a long time. However, the NEDC mode has been known the control of emission reduction is not reflected properly on actual road conditions. For these reasons, diesel vehicle emissions are regulated in both NEDC mode and WLTC mode from 2017 to 2020, from 2020 onwards, the emissions of diesel vehicles will measure in WLTC mode only and will not be able to exceed 1.5 times the regulated value. The purpose of this study is to analyze the development trend of diesel vehicle after-treatment system in order to comply with the future regulations on diesel vehicle. As a result, it is essential to reduce the NOx emissions of diesel vehicles for Euro 6, the NOx emissions of the test vehicle equipped with SCR were 30% to 50% loss than the test vehicle equipped with LNT despite the higher curb weight and engine displacement.

• Journal of Positioning, Navigation, and Timing
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• 제6권4호
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• pp.135-140
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• 2017

This paper proposes a signal merging algorithm to increase the signal-to-noise ratio (SNR) of a GPS correlator output to estimate the roll angle of a rotating vehicle in a weak GPS signal environment. Rotation Locked Loop (RLL) algorithm is used to estimate a roll angle using the characteristics that the power of the GPS signal measured at the receiver of a rotating vehicle varies periodically. First, delay times are calculated to synchronize GPS signals using satellites' and receiver's positions and the rotation frequency of a vehicle, and then correlator outputs are delayed in time and merged with each other, resulting in the increase of an SNR in a correlator output. Finally, simulations are conducted and the performance of the proposed algorithm is validated.

• 제어로봇시스템학회논문지
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• 제16권7호
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• pp.632-638
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• 2010

This paper presents an optimum tire force distribution method for 6WD/6WS(6-Wheel-Drive and 6-Wheel-Steering) electric vehicles. Using an independent steering and driving system, the performance of 6WD/6WS vehicles can be improved, as, for example, with respect to their maneuverability under low speed and their stability at high speed. Therefore, there should be a control strategy for finding the optimum tire forces that satisfy the driver's command and minimize energy consumption. From the driver's commands (steering angle and accelerator/brake pedal stroke), the desired yaw moment, the desired lateral force, and the desired longitudinal force were obtained. These three values were distributed to each wheel as the torque and the steering angle, based on the optimum tire force distribution method. The optimum tire force distribution method finds the longitudinal/lateral tire forces of each wheel that minimize the cost function, which is the sum of the normalized tire forces. Next, the longitudinal/lateral tire forces of each wheel are converted into the reference torque inputs and the steering wheel angle inputs. The proposed method was tested through a simulation, and its effectiveness was verified.

• 한국자동차공학회논문집
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• 제15권3호
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• pp.153-159
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• 2007

Nano-Particles are influenced on the environmental protection and human health. The relationships between transient vehicle operation and nano-particle emissions are not well-known, especially for diesel passenger vehicles with DPF. In this study, a diesel passenger vehicle was measured on condition of DPF regeneration and no regeneration on a chassis dynamometer test bench. The particulate matter (PM) emission from this vehicle was measured by its number, size and mass measurement. The mass of the total PM was evaluated with the standard gravimetric measurement method while the total number and size concentrations were measured on a NEDC driving cycle using Condensation Particle Counter (CPC) and EEPS. Total number concentration by CPC was $1.5{\times}10^{1l}N/km$, which was 20% of result by EEPS. This means about 80% of total particle emission is consist of volatile and small-sized particles(<22nm). During regeneration, particle emission was $6.2{\times}10^{12}N/km$, was emitted 400 times compared with the emission before regeneration. As for the particle size of $22{\sim}100nm$ was emitted mainly, showing peak value of near 40nm in size. This means regeneration decreased the mean size of particles. Regarding regeneration, PM showed no change while the particle number showed about 6 times difference between before and after regeneration. It seems that the regeneration influences on particle number emissions are related to DPF-fill state and filtration efficiency.

• Journal of Electrical Engineering and Technology
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• 제13권6호
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• pp.2468-2478
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• 2018

We propose the Sparse Feature Convolutional Neural Network (SFCNN) to reduce the volume of convolutional neural networks (CNNs). Despite the superior classification performance of CNNs, their enormous network volume requires high computational cost and long processing time, making real-time applications such as online-training difficult. We propose an advanced network that reduces the volume of conventional CNNs by producing a region-based sparse feature map. To produce the sparse feature map, two complementary region-based value extraction methods, cluster max extraction and local value extraction, are proposed. Cluster max is selected as the main function based on experimental results. To evaluate SFCNN, we conduct an experiment with two conventional CNNs. The network trains 59 times faster and tests 81 times faster than the VGG network, with a 1.2% loss of accuracy in multi-class classification using the Caltech101 dataset. In vehicle classification using the GTI Vehicle Image Database, the network trains 88 times faster and tests 94 times faster than the conventional CNNs, with a 0.1% loss of accuracy.

• 한국자동차공학회논문집
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• 제17권1호
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• pp.130-136
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• 2009

A lumped parameter model of Li-ion battery in hybrid electric vehicle(HEV) is constructed and system parameters are identified by using recursive least square estimation for different C-rates, SOCs and temperatures. The system characteristics of pole and zero in frequency domain are analyzed with the parameters obtained from different conditions. The parameterized model of Li-ion battery indicates highly dependant of temperatures. The system pole and internal resistance changes 6.6 and 18 times at $-20^{\circ}C$, comparing with those at $25^{\circ}C$, respectively. These results will be utilized on constructing model-based state observer or an on-line identification and an adaptation of the model parameters in battery management systems for hybrid electric vehicle applications.

• 한국군사과학기술학회지
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• 제11권4호
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• pp.141-148
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• 2008

In this paper, we develop a detailed full dynamic model which includes various rough terrains for 6-wheel skid-steering mobile robot based on the real experimental autonomous vehicle called Dog-Horse Robot. We also design a co-simulation for performance comparison of path tracking algorithms. The control architecture in the co-simulation can be divided into two levels. The high level control is the closed-loop control of path tracking to follow a given path, and the low level is concerned about torque control of wheel motion. The simulation using the mechanical data of the Dog-Horse Robot is performed under the Matlab/Simulink environment. We also simulate and evaluate the performance of the model based adaptive controller.

• 한국산학기술학회논문지
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• 제16권12호
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• pp.8700-8706
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• 2015

고속철도차량 동력대차의 1차 구동장치는 모터 감속기와 견인전동기로 구성한다. 모터 감속기와 견인전동기는 기계적으로 일체형 결합 구조이지만, 상이한 기술 요구사항으로 인하여 이들의 완전 분해정비 주기는 서로 다르다(모터 감속기의 완전 분해정비 주기: $1.8{\times}10^6km$, 견인전동기의 완전 분해정비 주기: $2.5{\times}10^6km$). 따라서 불필요한 정비 횟수를 감소하기 위하여 신뢰성 중심 유지보수 관점에서 최적의 완전 분해정비 주기의 산정이 중요하다. 본 연구에서는 실제 유지보수 정비이력으로부터 두 구성품들에 대한 고장 결함나무 분석을 수행하고 각 하부부품들의 치명도를 고려한 고장률을 각각 평가하였다. 두 구성품에 대한 최적의 동일한 완전분해 정비주기는 기존의 총 예방정비 비용을 감소하기 위하여 유전자 알고리즘으로 부터 얻었다. 이 알고리즘에서 각 개체를 구성하는 유전자는 최소 예방 정비주기이며, 이의 조합으로 구성된 세대별 개체의 적합도함수는 총 정비비용의 역수로 공식화하여 얻는다. 최소공배수에 의한 방법은 기존 대비 4%만 감소하지만, 유전자 알고리즘에 의한 최적의 동일 완전분해 정비주기는 225만km로서 기존 방법의 총비용과 비교하여 약 14% 감소하였다.

• 한국융합학회논문지
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• 제7권6호
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• pp.1-6
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• 2016

본 논문에서는 영상을 분할하고, 분할된 영상의 로컬 히스토그램을 이용하여 저조도 환경의 블랙박스 영상 향상 방법을 제안한다. 기존 블랙박스 영상은 저조도 환경에서 촬영되기 때문에 향상 기법을 적용 시 과도한 향상 효과가 발생하는 단점이 있다. 제안 알고리즘은 3단계 과정으로 구성된다. 1단계는 입력 영상을 ($N{\times}M$)개 조각으로 분할하고, 분할된 부분 영상과 인접한 부분 영상을 그룹 영상으로 묶어 구분한다. 2단계는 구분된 그룹 영상을 각각의 로컬 히스토그램을 이용하여 명암 향상 처리를 수행한다. 3단계는 명암 향상 처리된 각각의 그룹 영상의 특성을 반영한 전달 함수를 이용하여 전체 영상을 재구성한다. 알고리즘 검증을 위하여 지하 주차장과 야간 운행 영상을 저조도 환경 영상으로 사용하였다. 제안 알고리즘은 다양한 저조도 환경의 블랙박스 영상을 향상시켜 차량 운행 환경 정보 획득에 유리한 영상을 제공할 수 있다.