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주입 전압파형의 형상에 따른 고조파 주입 센서리스 기법의 제어 성능 비교
문경록,이동명 한국전기전자학회 2022 전기전자학회논문지 Vol.26 No.1
This paper compares the sensorless control performance according to the applied voltage waveform by injectingsinusoidal, triangular, and square waveform in the harmonic injection sensorless control method. By injectingvarious voltage shape waveform with a frequency of 1kHz, the error amount of the estimated angle for eachwaveform is compared and analyzed. For the experiment, the HILS(hardware in the loop simulation) system wasused. The hardware is the control board, and the inverter and motor models implemented in Simulik are locatedin the real-time simulator. The control algorithm is implemented by the FPGA control board, which includes aPWM interrupt service routine with a frequency of 10 kHz, harmonic injection and position detection sensorlessalgorithm. 본 논문은 전동기의 저속 영역 운전의 센서리스 기법으로 적합한 고조파 주입 센서리스 제어기법에서 사인파, 삼각파 및 사각파를주입하여 인가 전압 파형에 따른 센서리스 성능을 비교한다. 본 연구는 영구자석 전동기의 센서리스 기법에 관한 것이다. 1kHz 주파수를 갖는 여러 모양의 파형을 주입하여, 각 파형에 대한 추정된 각도의 오차량을 비교 분석한다. 실험은 HILS(hardware in theloop simulation) 시스템을 이용하였으며, Hardware는 제어보드이며 실시간 시뮬레이터에는 Simulik로 구현된 인버터와 전동기의 모델이 위치한다. 제어 알고리즘은 FPGA 제어보드로 구현하였으며, 이는 10kHz 주파수의 PWM 인터럽트 서비스 루틴, 고조파주입 및 위치 검출 센서리스 알고리즘 등을 포함한다. HILS 실험을 통해 사인파, 삼각파 및 사각파 고조파 주입시 센서리스 제어성능을 비교한다.
문경록,김태한,송택렬 한국우주과학회 2012 Journal of Astronomy and Space Sciences Vol.29 No.4
This paper studies the problem of tracking a re-entry vehicle (RV) in order to predict its impact point on the ground. Re-entry target dynamics combined with super-high speed has a complex non-linearity due to ballistic coefficient variations. However, it is difficult to construct a database for the ballistic coefficient of a unknown vehicle for a wide range of variations, thus the reliability of target tracking performance cannot be guaranteed if accurate ballistic coefficient estimation is not achieved. Various techniques for ballistic coefficient estimation have been previously proposed, but limitations exist for the estimation of non-linear parts accurately without obtaining prior information. In this paper we propose the ballistic coefficient β model-based interacting multiple model-extended Kalman filter (β-IMM-EKF) for precise tracking of an RV. To evaluate the performance, other ballistic coefficient model based filters, which are gamma augmented filter, gamma bootstrapped filter were compared and assessed with the proposed β-IMM-EKF for precise tracking of an RV.
증기 분리식 예냉 증기압축 냉동 사이클의 성능 특성 연구
문경록,윤상국 한국마린엔지니어링학회 2019 한국마린엔지니어링학회지 Vol.43 No.3
The purpose of this study is to improve the performance of the current vapor compression refrigeration cycle composed of a compressor, a condenser, an expansion device, and an evaporator. In the refrigeration cycle, a certain portion of the liquid refrigerant evaporates after the expansion process, and the evaporated vapor refrigerant does not play a role in the refrigeration effect in the evaporator. Therefore, a new two-stage expansion refrigeration cycle, in which the vapor is separated from the mixture after the middle expansion process, was introduced and analyzed. It was found that the new vapor-separated cycle significantly improves the coefficient of performance by ~30% compared with that of the current existing refrigeration cycle, when a middle expansion pressure of 5 bars is applied in a typical R-134a domestic freezer cycle working in the high-pressure condition of 10.166 bars, a condensation temperature of 35 °C having 5 °C of pre-cooling, and a low-pressure condition of 1.064 bars and −25°C. In addition, because the mass flow rate of the liquid phase in the evaporator decreases by ~15%–20% compared with that of the current cycle, the evaporator size can be significantly reduced. 증기 압축식 냉동 사이클은 압축기, 응축기, 팽창장치, 증발기 등으로 구성되며, 냉동기 용량에 따라 많은 전기 에너지가 소비되므로 지속적인 에너지 절약의 노력을 필요로 한다. 증기 압축식 냉동 사이클에서 팽창과정 중 발생하는냉매 기체는 증발기 내부에서 냉동효과를 제공하지 못하며, 액체만이 기체로 상태가 바뀌면서 냉동 역할을 수행한다. 그러므로 본 연구에서는 증발기 유입 전에 기체 냉매를 분리하는 새로운 2단 팽창 사이클을 고안하여 성능계수 향상 효과를 분석하였다. 분석 결과, 증기 분리식 예냉 냉동 사이클은 중간 팽창 압력 5 bar에서 현재 사이클 대비 약 30 % 이상의 성능 향상을 보였다. 비교 기준 사이클은 가정용 R-134a 냉장고 냉동 공간으로 고압은 10.166 bar, 예냉이 5℃된 응축온도 35℃, 그리고 저압은 1.064 bar, -25℃를 기준하였다. 또한, 증기 분리 2단 팽창 사이클 경우 증발기 내부에 흐르는냉매 질량유량흐름이 15 ~ 20 %가 감소하게 되어 증발기의 규격이 크게 감소하게 되었다.
기계학습 기간에 따른 장기간 전력계통한계가격의 추세 예측
문경록(Mun Kyeong-Rok),이건우(Lee Keon-Woo),고경남(Ko Kyung-Nam) 한국태양에너지학회 2021 한국태양에너지학회 논문집 Vol.41 No.5
The yearly system marginal prices (SMPs) in mainland Korea, from 2020 to 2030, were predicted using significant amounts of machine learning training data. The factors for deciding SMP were collected from public data portal sites. The factors included supply capacity, maximum power, supply reserve, liquefied natural gas (LNG), West Texas intermediate crude oil (WTI), and FOB Kalimatan. The best two factors for forecasting SMP, LNG, and WTI were selected through correlation analysis. The training data were divided into cases, A for 10 years and B for 5 years. The models, K-nearest neighbor (KNN), light gradient boost machine (LGBM), random forest (RF), and support vector regression (SVR) models were used for machine learning, and their accuracy was evaluated. Finally, long-term mainland SMPs were forecasted using Japanese LNG and WTI prices. The resultant model for the most accurate machine learning was LGBM which was used to forecast long-term SMPs. The mainland SMP was predicted to decrease from 2020 to 2022 and then maintain 72 KRW/kWh for Case A and 69 KRW/kWh for Case B until 2030.