• Advances in aircraft and spacecraft science
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• 제1권3호
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• pp.311-330
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• 2014

Environmental impact of aircraft emissions can be addressed in two ways. Air quality impact occurs during landings and takeoffs while in-flight impact during climbs and cruises influences climate change, ozone and UV-radiation. The aim of this paper is to investigate airports related local emissions and fuel consumption (FC). It gives flight path optimization model linked to a dispersion model as well as numerical methods. Operational factors are considered and the cost function integrates objectives taking into account FC and induced pollutant concentrations. We have compared pollutants emitted and their reduction during LTO cycles, optimized flight path and with analysis by Dopelheuer. Pollutants appearing from incomplete and complete combustion processes have been discussed. Because of calculation difficulties, no assessment has been made for the soot, $H_2O$ and $PM_{2.5}$. In addition, because of the low reliability of models quantifying pollutant emissions of the APU, an empirical evaluation has been done. This is based on Benson's fuel flow method. A new model, giving FC and predicting the in-flight emissions, has been developed. It fits with the Boeing FC model. We confirm that FC can be reduced by 3% for takeoffs and 27% for landings. This contributes to analyze the intelligent fuel gauge computing the in-flight fuel flow. Further research is needed to define the role of $NO_x$ which is emitted during the combustion process derived from the ambient air, not the fuel. Models are needed for analyzing the effects of fleet composition and engine combinations on emission factors and fuel flow assessment.

• 한국컴퓨터정보학회논문지
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• 제27권9호
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• pp.13-20
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• 2022

본 연구에서는 주행 차량의 실시간 연료소모량을 예측할 수 있는 머신러닝 기법을 제안하고 그 특성을 분석하였다. 머신러닝 학습을 위해 실도로 주행을 실시하여 주행 속도, 가속도, 도로 구배와 함께 연료소모량을 측정하였다. 특성 데이터로 속도, 가속도, 도로구배를, 타깃으로 연료소모량을 지정하여 다양한 머신러닝 모델을 학습시켰다. 회귀법에 해당하는 K-최근접이웃회귀 및 선형회귀와 함께, 분류법에 해당하는 K-최근접이웃분류, 로지스틱회귀, 결정트리, 랜덤포레스트, 그래디언부스팅을 사용하였다. 실시간 연료소모량에 대한 예측 정확도는 0.5 ~ 0.6 수준으로 전반적으로 낮았고, 회귀법의 경우 분류법보다 정확도가 떨어졌다. 총연료소모량에 대한 예측 오차는 0.2 ~ 2.0% 수준으로 상당히 정확했고, 분류법보다 회귀법의 오차가 더 낮았다. 이는 예측 정확도의 기준으로 결정계수(R²)를 사용했기 때문인데, 이 값이 작을수록 타깃의 평균 부근에 예측치가 좁게 분포하기 때문이다. 따라서 실시간 연료소모량 예측에는 분류법이, 총연료소모량 예측에는 회귀법이 적합하다고 할 수 있다.

• 설비공학논문집
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• 제26권5호
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• pp.199-205
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• 2014

The integration of FC (Fuel Cell) and GSHP (Ground Source Heat Pump) hybrid system could produce a synergistic advantage in thermal and electric way. This study intends to analyse the economical aspect of a FC integrated GSHP hybrid system compared to the conventional system which is consisted with a boiler and a chiller. Based on the hourly simulation, the study indicated that GSHP system and FC+GSHP hybrid system could reduce the energy consumption on a building. The method of the economic assessment has been based on IEA ECBCS Annex 54 Subtask C SPB(Simple Payback) method. The SPB was calculated using the economic balanced year of the alternative system over the conventional (reference) system. The SPB of the alternative systems (GSHP and FC+GSHP) with 50% initial incentive was 4.06 and 26.73 year respectively while the SPB without initial incentive of systems was 10.71 and 57.76 year.

• 한국자동차공학회논문집
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• 제23권5호
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• pp.537-544
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• 2015

The effects of the modification of hybrid vehicle components on diesel exhaust emissions were investigated in this study. We examined the changes in exhaust emissions and the fuel consumption (FC) caused by the modification of generator (alternator) and motors. Exhaust emissions such as black carbon (BC), HC, $NO_X$ and $CO_2$ were measured not only in idle state but also on an actual urban road as well as on a chassis dynamometer. BC, $NO_X$ and HC emissions increased by 95%, 27% and 34% respectively when the generator charged the battery in the idle condition. BC and FC decreased in hybrid mode on the actual urban road partly because the motors were used to assist the diesel engine. In addition, the decreases in exhaust emissions and FC were also evident in the hybrid mode when the vehicle was tested on the chassis dynamometer.

• International Journal of Computer Science & Network Security
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• 제22권3호
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• pp.37-44
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• 2022

Plug-in Hybrid electric vehicles (PHEV) show great potential to reduce gas emission, improve fuel efficiency and offer more driving range flexibility. Moreover, PHEV help to preserve the eco-system, climate changes and reduce the high demand for fossil fuels. To address this; some basic components and energy resources have been used, such as batteries and proton exchange membrane (PEM) fuel cells (FCs). However, the FC remains unsatisfactory in terms of power density and response. In light of the above, an electric storage system (ESS) seems to be a promising solution to resolve this issue, especially when it comes to the transient phase. In addition to the FC, a storage system made-up of an ultra-battery UB is proposed within this paper. The association of the FC and the UB lead to the so-called Fuel Cell Battery Electric Vehicle (FCBEV). The energy consumption model of a FCBEV has been built considering the power losses of the fuel cell, electric motor, the state of charge (SOC) of the battery, and brakes. To do so, the implementing a reinforcement-learning energy management strategy (EMS) has been carried out and the fuel cell efficiency has been optimized while minimizing the hydrogen fuel consummation per 100km. Within this paper the adopted approach over numerous driving cycles of the FCBEV has shown promising results.

• 한국산학기술학회논문지
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• 제20권2호
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• pp.1-6
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• 2019

본 연구의 목적은 100kW급 연료전지 시스템의 열관리 성능을 실도로 운전조건에서 분석하여, 성능 해석 모델링을 개발하는 것이다. 개발된 모델을 적용하여, 열관리 시스템의 운전조건 변화에 따른 성능 변화를 고찰하고자 한다. 해석 모델링은 핵심부품들에 대한 성능 평가 데이터를 바탕으로, 성능에 영향을 주는 변수들로 개발하였다. 개발된 연료전지 열관리 시스템 해석 모델링으로 다양한 실차 운전조건에서의 최적 열관리 시스템에 대한 전력소비량을 분석하였다. 주요하게, 연료전지 열관리시스템 핵심부품(워터펌프, 냉각 팬, 3 Way Valve, 라디에이터)에 대한 성능 특성 분석 후 모델링을 진행하였다. 개발된 모델링으로 운전조건에 따른 유량 예측을 하였고, 실험값과 예측값과의 비교분석을 통하여서, 해석 모델링에 대한 검증을 진행하였다. 과도해석을 통하여서, 냉시동시 냉각수 온도가 특정온도까지의 소요시간을 예측하였다. 스택 운전조건에서 스택 입출구 온도가 적정 수준에서 움직이기 위한 열관리 시스템 운전조건에 대한 예측을 진행하였다. 그 결과를 바탕으로, 소모전력과 열방출량과의 비교분석을 하였다. 개발된 해석 모델링은 핵심부품들의 성능 변화시 연료전지 시스템 운전에 대한 영향도를 분석할 수 있도록 활용할 예정이다.

• 한국자동차공학회논문집
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• 제20권4호
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• pp.60-67
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• 2012

Most of a driving cycle is used to measure fuel consumption (FC) and emissions for a specified vehicle. A driving cycle was reflected geography and traffic characteristics for each country, also, driving pattern is affected these parameters such as vehicle dynamics, FC and emissions. Therefore, this study is an attempt to develop a driving cycle for military operational area. The proposed methodology the driving cycle using micro-trips extracted from real-world data. The methodology is that the driving cycle is constructed considering important parameters to be affected FC. Therefore, this approach is expected to be a better representation of heterogeneous traffic behavior. The driving cycle for the military operational area is constructed using the proposed methodology and is compared with real-world driving data. The running time and total distance of the final cycle is 1461 s, 13.10 km. The average velocity is 32.25 km/h and average grade is 0.43%. The Fuel economy in the final cycle is 5.93 km/l, as opposed to 6.10 km/l for real-world driving. There were about 3% differences in driving pattern between the final driving cycle and real-world driving.

• 한국자동차공학회논문집
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• 제25권3호
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• pp.297-308
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• 2017

One of the major engine thermal management system(TMS) strategies for improving fuel economy is to operate the engine in high temperatures. Therefore, this work performed a numerical and experimental study to examine the effect of several different STOs(Starting Temperature of Opening) of wax-thermostat, ranging from $85^{\circ}C$ to $105^{\circ}C$, of gasoline engine on fuel economy and emission characteristics. In this study, a gasoline car equipped with waxthermostat was tested and simulated under FTP-75 and HWFET mode. CRUISE $M^{TM}$ was used to simulate vehicle dynamics, transient engine performance and TMS. The test results showed fuel savings for both drive cycles due to higher STO of $100^{\circ}C$, which is slightly worse than that of $90^{\circ}C$ and amounts between 0.34 and 0.475 %. These controversial results are attributed to experimental errors and uncertainty. The computational results for three STOs, $85^{\circ}C$, $95^{\circ}C$ and $105^{\circ}C$, showed that fuel savings attributed to the application of higher STOs of $95^{\circ}C$ and $105^{\circ}C$ are relatively small and range from 0.306 to 0.363 %. It is also found that the amount of HC and CO emissions from the tailpipe tends to decrease with higher engine coolant temperature because of faster catalyst light-off and improved combustion.

• Advances in Energy Research
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• 제7권1호
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• pp.35-52
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• 2020

The paper proposes a hybrid approach of artificial bee colony (ABC) and grey wolf optimizer (GWO) algorithm for multi-objective and multidimensional engine optimization of a converted plug-in hybrid electric vehicle. The proposed strategy is used to optimize all emissions along with brake specific fuel consumption (FC) for converted parallel operated diesel plug-in hybrid electric vehicle (PHEV). All emissions particulate matter (PM), nitrogen oxide (NOx), carbon monoxide (CO) and hydrocarbon (HC) are considered as optimization parameters with weighted factors. 70 hp engine data of NOx, PM, HC, CO and FC obtained from Oak Ridge National Laboratory is used for the study. The algorithm is initialized with feasible solutions followed by the employee bee phase of artificial bee colony algorithm to provide exploitation. Onlooker and scout bee phase is replaced by GWO algorithm to provide exploration. MATLAB program is used for simulation. Hybrid ABC-GWO algorithm developed is tested extensively for various values of speeds and torque. The optimization performance and its environmental impact are discussed in detail. The optimization results obtained are verified by real data engine maps. It is also compared with modified ABC and GWO algorithm for checking the effectiveness of proposed algorithm. Hybrid ABC-GWO offers combine benefits of ABC and GWO by reducing computational load and complexity with less computation time providing a balance of exploitation and exploration and passes repeatability towards use for real-time optimization.

• 한국가스학회지
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• 제27권3호
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• pp.52-58
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• 2023

지구 기상이변에 대해 탄소중립의 중요성이 대두됨에 따라 무탄소 연료인 수소의 에너지원으로서의 활용도 역시 증대되고 있다. 일반적으로 수소는 연료전지(FC, Fuel Cell)에 활용되고 있으나, 이는 연소를 기반으로 하는 내연기관(ICE, Internal Combustion Engine)에도 활용될 수 있다. 특히 연료전지만으로 수소 활용 및 인프라 확장이 어려운 때에 이미 생산 측면이나 공급 측면에서 인프라가 기 구축되어 있는 내연기관은 수소 에너지 저변 확대에 큰 도움을 줄 수 있다. 다만 수소를 연소기반으로 활용할 경우 고온에서 공기 중 질소가 산소와 반응하여 유해배기물질인 질소산화물(NOx, Nitrogen Oxides)이 생성될 수 있는 단점은 존재한다. 특히 냉간 (Cold Start) 운전 영역시 포함될 EURO-7 배기규제의 경우 워밍업(Warm-up) 과정에서 발생하는 배기배출물의 저감을 위한 노력도 필요하다. 따라서 본 연구에서는 2 L급 수소 직접분사방식 전기점화 (SI, Spark Ignition) 엔진을 활용하여 냉각수를 상온에서 88 ℃로 워밍업하는 과정에서 질소산화물 및 연료소모율의 변화 특성을 살펴보았다. 특히 수소는 기존의 가솔린, 천연가스, 액화석유가스(LPG, Liquified Petroleum Gas)와 달리 가연범위(Flammable range)가 넓기 때문에 공기과잉률(Excessive air ratio)을 희박하게 조절할 수 있다는 장점이 있다. 이에 본 연구에서는 워밍업하는 과정에 있어서 공기과잉률을 1.6/1.8/2.0으로 변화하여 그 결과를 분석하였다. 본 실험의 결과는 워밍업 시 공기과잉률이 희박해질수록 시간당 질소산화물의 배출이 적고, 열효율도 상대적으로 높으나 최종 온도까지 도달 시간이 길어짐에 따라 누적 배출량 및 연료소모율은 악화될 수도 있음을 시사한다.