• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.4
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• pp.591-598
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• 2021

The digital phase-locked loops(DPLL) is a circuit used for phase synchronization and has been generally used in various fields such as communication and circuit fields. State estimators are used to design digital phase-locked loops, and infinite impulse response state estimators such as the well-known Kalman filter have been used. In general, the performance of the infinite impulse response state estimator-based digital phase-locked loop is excellent, but a sudden performance degradation may occur in unexpected situations such as inaccuracy of initial value, model error, and disturbance. In this paper, we propose a minimum variance finite impulse response filter with optimal horizon for designing a new digital phase-locked loop. A numerical method is introduced to obtain the measured value interval length, which is an important parameter of the proposed finite impulse response filter, and to obtain a gain, the covariance matrix of the error is set as a cost function, and a linear matrix inequality is used to minimize it. In order to verify the superiority and robustness of the proposed digital phase-locked loop, a simulation was performed for comparison and analysis with the existing method in a situation where noise information was inaccurate.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.5
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• pp.635-643
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• 2018

This paper propose a method to identify the motor parameters and improve input voltage error which affect the low speed position error of the back-emf(back electromotive force) based sensorless algorithm and to secure the operation reliability and stability even in the case where the load fluctuation is severe and the start and low speed operation frequently occurs. In the model-based observer used in this paper, stator resistance, inductance, and input voltage are particularly influential factors on low speed performance. Stator resistance can cause resistance value fluctuation which may occur in mass production process, and fluctuation of resistance value due to heat generated during operation. The inductance is influenced by the fluctuation due to the manufacturing dispersion and at a low speed where the change of the current is severe. In order to find stator resistance and inductance which have different initial values and fluctuate during operation and have a large influence on sensorless performance at low speed, they are commonly measured through 2-point calculation method by 2-step align current injection. The effect of voltage error is minimized by offsetting the voltage error. In addition, when the command voltage is used, it is difficult to estimate the back-emf due to the relatively large distortion voltage due to the dead time and the voltage drop of the power device. In this paper, we propose a simple circuit and method to detect the voltage by measuring the PWM(Pulse Width Modulation) pulse width and compensate the voltage drop of the power device with the table, thereby minimizing the position error due to the exact estimation of the back-emf at low speed. The suitability of the proposed algorithm is verified through experiment.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.6
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• pp.31-38
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• 2003

Among mitigation techniques for electric and magnetic field (EMF) from an overhead transmission line a passive loop is a way that can be cheap and easily installed on the existing towers and have a satisfactory effect as well. However current induced in the passive loop causes transmission power loss and the phase imbalance increases since geometrical asymmetry of the transmission lines becomes larger. So in order to evaluate the power loss and the phase imbalance due to a passive loop, this paper represent a 345[kV] 1-circuit flat type transmission line as asymmetrical 3-phase distributed parameter line model where the effect of a passive loop is embedded in the line parameters, and then formulates differential equations. By solving these equations voltages and currents of each phase at receiving end become known. We find out that power losses occur differently at each phase and positive sequence component decreases at receiving end while negative sequence component increase. In general phase imbalance due to a passive loop is slight, but it increases in proportional to the induced current and length of section where the passive loop is installed. Thus the phase imbalance should be included in terms of cost for introducing a passive loop.

• Journal of Bio-Environment Control
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• v.26 no.4
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• pp.258-267
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• 2017

The price competitiveness of photovoltaic system (PV system) has risen recently due to the growth of industries, however, it is rarely applied to the greenhouse compared to other renewable energy. In order to evaluate the application of PV system in the greenhouse, power generation and optimal installation area of PV panels should be analyzed. For this purpose, the prediction of the heating and cooling loads of the greenhouse is necessary at first. Therefore, periodic and maximum energy loads of a multi-span greenhouse were estimated using Building Energy Simulation(BES) and optimal installation area of PV panels was derived in this study. 5 parameter equivalent circuit model was applied to analyzed power generation of PV system under different installation angle and the optimal installation condition of the PV system was derived. As a result of the energy simulation, the average cooling load and heating load of the greenhouse were 627,516MJ and 1,652,050MJ respectively when the ventilation rate was $60AE{\cdot}hr^{-1}$. The highest electric power production of the PV system was generated when the installation angle was set to $30^{\circ}$. Also, adjustable PV system produced about 6% more electric power than the fixed PV system. Optimal installation area of the PV panels was derived with consideration of the estimated energy loads. As a result, optimal installation area of PV panels for fixed PV system and adjustable PV system were $521m^2$ and $494m^2$ respectively.

• Animal Bioscience
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• v.36 no.1
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• pp.75-83
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• 2023

Objective: The objective of this study was to describe a methodological procedure to quantify the heat production (HP) partitioning in basal metabolism or fasting heat production (FHP), heat production due to physical activity (HPA), and the thermic effect of feeding (TEF) in roosters. Methods: Eighteen 54-wk-old Hy Line Brown roosters (2.916±0.15 kg) were allocated in an open-circuit chamber of respirometry for O₂ consumption (VO₂), CO₂ production (VCO₂), and physical activity (PA) measurements, under environmental comfort conditions, following the protocol: adaptation (3 d), ad libitum feeding (1 d), and fasting conditions (1 d). The Brouwer equation was used to calculate the HP from VO₂ and VCO₂. The plateau-FHP (parameter L) was estimated through the broken line model: HP = U×(R-t)×I+L; I = 1 if t<R or I = 0 if t>R; Where the broken-point (R) was assigned as the time (t) that defined the difference between a short and long fasting period, I is conditional, and U is the decreasing rate after the feed was withdrawn. The HP components description was characterized by three events: ad libitum feeding and short and long fasting periods. Linear regression was adjusted between physical activity (PA) and HP to determine the HPA and to estimate the standardized FHP (st-FHP) as the intercept of PA = 0. Results: The time when plateau-FHP was reached at 11.7 h after withdrawal feed, with a mean value of 386 kJ/kg^0.75/d, differing in 32 kJ from st-FHP (354 kJ/kg^0.75/d). The slope of HP per unit of PA was 4.52 kJ/mV. The total HP in roosters partitioned into the st-FHP, termal effect of feeding (TEF), and HPA was 56.6%, 25.7%, and 17.7%, respectively. Conclusion: The FHP represents the largest fraction of energy expenditure in roosters, followed by the TEF. Furthermore, the PA increased the variation of HP measurements.