• Journal of Integrative Natural Science
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• v.10 no.1
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• pp.58-63
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• 2017

Photovoltaic (PV) are generally modeled using mathematical equations that describe the PV system behavior. Most of the modeling approach is very simple in terms of that PV module temperature is calculated from nominal constant cell temperature such as ambient temperature and incoming solar irradiance. In this paper, we newly present MATLAB model particularly embedding the effect of wind speed to describe more accurate cell temperature. For analyses and validate purpose of the proposed model, solar power is obtained and compared with and without wind speed from the 50Wp PV module provided by vendor datasheet. In the simulation result, we found that power output of the module is increased to 0.37% in terms of cell temperature a degreed down when we consider the wind speed in the model. This result is well corresponded with the well-known fact that normal PV is 0.4% power changed by cell temperature a degree difference. Therefore it shows that our modeling method with wind speed is more appropriate than the methods without the wind speed effect.

• 한국태양에너지학회:학술대회논문집
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• 2011.11a
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• pp.278-281
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• 2011

This system can predict the maximum output about all illumination levels so that the PV system designer can design the system having the best efficiency. For the output prediction exact about the solar cell, that is the device the basis most in the PV system, the basis has to be in order to try this way. The solution based on Lambert W-function are presented to express the transcendental current-voltage characteristic containing parasitic power consuming parameters like series and shunt resistances. A simple and efficient method for the extraction of a single current-voltage (I-V) curve under the constant illumination level is proposed. With the help of the Lambert W function, the explicit analytic expression for I is obtained. And the explicit analytic expression for V is obtained. This analytic expression is directly used to fit the experimental data and extract the device parameters. The I-V curve of the solar cell was expressed through the modeling using Lambert W-function and the numerical formula where there is the difficulty could be logarithmically expressed This method expresses with the I-V curve through the modeling using Lambert W-function which adds other loss ingredients to the equation2 as to the research afterward. And the solar cell goes as small and this I-V curve can predict the power penalty in the system unit.

• 한국신재생에너지학회:학술대회논문집
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• 2011.05a
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• pp.100.1-100.1
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• 2011

Electrochemical impedance spectroscopy(EIS) are using widely as a useful technique mainly in the field of electrochemical for the analysis of electrode reactions or characteristics of the composites. The response analysis of the systems technique provides comprehensive informations about the characteristic and structure of complex and internal reaction. The EIS is the method to measure impedance of the measurement target classified by the frequency, it select the equivalent impedance model to give same response from the result and it calculate the parameter. Therefore, the chemical reaction inside the fuel cell is to modeling to electrical impedance. And as repeating the same experiment in each of the operating point, we can get each different parameter. As a result, we can establish the equivalent impedance model in each operating point. Therefore, if we use these models, we can evaluate the fuel cell without the internal design parameter of the fuel cell as required in existing modeling. The EIS is used typically technique for distinguish status of fuel cell called SOH(State Of Health). When the fuel cell is degradation, Efficiency and health of the fuel cell is reduced because internal impedance is increase. As usage of these principles, we can evaluate state of fuel cell through the impedance analysis of fuel cells. In this study, we are presents EIS distinction system and algorithm for residential fuel cell systems. At the time of the fuel cell installation in the fields, the EIS system and proposed algorithm will be able to apply as technique for efficiency and performance evaluation about fuel cell system.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.12
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• pp.1079-1085
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• 2000

In this paper, we propose a method of cooperative control (T-cell modeling) and selection of group behavior strategy (B-cell modeling) based on immune system in distributed autonomous robotic system (DARS). An immune system is the living bodys self-protection and self-maintenance system. these features can be applied to decision making of the optimal swarm behavior in a dynamically changing environment. For applying immune system to DARS, a robot is regarded as a B-cell, each environmental condition as an antigen, a behavior strategy as an antibody, and control parameter as a T-cell, respectively. When the environmental condition (antigen) changes, a robot selects an appropriate behavior strategy (antibody). And its behavior strategy is stimulated and suppressed by other robots using communication (immune network). Finally, much stimulated strategy is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and immune network hypothesis, and it is used for decision making of the optimal swarm strategy. Adaptation ability of the robot is enhanced by adding T-cell model as a control parameter in dynamic environments.

• Journal of Energy Engineering
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• v.29 no.2
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• pp.1-9
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• 2020

In recent days, fuel cell has received attention from the world as an alternative power source to hydrocarbon used in automobile engines. With the industrial advances of fuel cell, There have been a lot of researches actively conducted to find a way of generating hydrogen. Among many hydrogen production methods, Solid Oxide Electrolysis Cell(SOEC) is not only a basic way but also environment-friendly method to produce hydrogen gas. Solid Oxide Electrolysis Cell has lower electrical energy demands and high thermal efficiency since it is possible to operate under high temperature and high pressure conditions. For these reasons, experimental researches as well as studies on numerical modeling for Solid Oxide Electrolysis Cell have been under way. However, studies on numerical modeling are relatively less enough than experimental accomplishments and have limited performance prediction, which mostly is considered as a result from inadequate effects of electrochemical properties by temperature and pressure. In this study, various experimental studies of commercial Membrane Electrode Assembly (MEA) composed of Ni-YSZ (40wt%, Ni-60 wt% YSZ)/8-YSZ (TOSOH, TZ8Y)/LSM (La_0.9Sr_0.1MnO₃) was utilized for improving effectiveness of SOEC model. After numerically analyzing effects of electrochemical properties according to operating temperature, causing the largest deviation between experiments and simulation are that Charge Transfer Coefficient (CTC), exchange current density, diffusion coefficient, electrical conductivity in SOEC. Analyzing temperature effect on parameter used in overpotential model is conducted for modeling of SOEC. cross-validation method is adopted for application of various MEA and evaluating feasibility of model. As a result, the study confirm that the numerical model of SOEC based on structured process of effectiveness evaluation makes performance prediction better.

• Geophysics and Geophysical Exploration
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• v.6 no.2
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• pp.77-86
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• 2003

We designed a new time-domain, finite-difference, elastic wave modeling technique, based on a displacement formulation. which yields nearly correct solutions to Lamb's problem. Unlike the conventional, displacement-based, finite-difference method using a node-based grid set (where both displacements and material properties such as density and Lame constants are assigned to nodal points), in our new finite-difference method, we use a cell-based grid set (where displacements are still defined at nodal points but material properties within cells). In the case of using the cell-based grid set, stress-free conditions at the free surface are naturally described by the changes in the material properties without any additional free-surface boundary condition. Through numerical tests, we confirmed that the new second-order finite differences formulated in the cell-based grid let generate numerical solutions compatible with analytic solutions unlike the old second-order finite-differences formulated in the node-based grid set.

• The Transactions of the Korean Institute of Power Electronics
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• v.18 no.1
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• pp.45-53
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• 2013

Fuel cell power system is one of the most promising energy source for the alternative energy because it has unique advantages such as high energy density, no power drop during operation, and feasible to make compact size. However, due to very low response time, fuel cell is difficult to correspond to drastic load changes and start-up operation. For solving these problem, fuel cell power system must include energy storage device such as Li-Poly battery or super capacitor. Therefore, bi-directional DC-DC converter must be required for this storage device and fuel cell-PCS control. This paper presents a design and modeling of the bi-directional DC/DC converter. Firstly, we present modeling the boost and buck mode of the bi-directional converter through both PWM switch model and state space averaging technique. Secondly, in order to minimize output ripple and transient response overshoot, we have two identical DC-DC converters interleaved and adopt two-loop voltage-current controller. The proposed bi-directional DC-DC converter's modeling method and control design have been verified with computer simulation and experimentation.

• Korean Chemical Engineering Research
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• v.53 no.2
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• pp.236-242
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• 2015

We present two data-driven modeling methods, partial least square (PLS) and artificial neural network (ANN), to predict the major operating and performance variables of a polymer electrolyte membrane (PEM) fuel cell stack. PLS and ANN models were constructed using the experimental data obtained from the testing of a 30 kW-class PEM fuel cell stack, and then were compared with each other in terms of their prediction and computational performances. To reduce the complexity of the models, we combined a variables importance on PLS projection (VIP) as a variable selection method into the modeling procedure in which the predictor variables are selected from a set of input operation variables. The modeling results showed that the ANN models outperformed the PLS models in predicting the average cell voltage and cathode outlet temperature of the fuel cell stack. However, the PLS models also offered satisfactory prediction performances although they can only capture linear correlations between the predictor and output variables. Depending on the degree of modeling accuracy and speed, both ANN and PLS models can be employed for performance predictions, offline and online optimizations, controls, and fault diagnoses in the field of PEM fuel cell designs and operations.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2004.04a
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• pp.186-189
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• 2004

A thermal model of carbon spun yam is presented. The unit cell of spun carbon yam is divided into a number of volume elements and the local material properties have been given to each element. By using Finite Difference Method (FDM), temperature distribution in the unit cell can be obtained. Effective thermal conductivity of the spun carbon yam unit cell is calculated using the temperature distribution and thermal conductivities of local elements.

• Interaction and multiscale mechanics
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• v.1 no.2
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• pp.191-209
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• 2008

In this paper, we model grain boundary evolution based on a multiple level set method. Grain boundary migration under a curvature-induced driving force is considered and the level set method is employed to deal with the resulting topological changes of grain structures. The complexity of using a level set method for modeling grain structure evolution is due to its N-phase nature and the associated geometry compatibility constraint. We employ a multiple level set method with a predictor-multicorrectors approach to reduce the gaps in the triple junctions down to the grid resolution level. A ghost cell approach for imposing periodic boundary conditions is introduced without solving a constrained problem with a Lagrange multiplier method or a penalty method. Numerical results for both uniform and random grain structures evolution are presented and the results are compared with the solutions based on a front tracking approach (Chen and Kotta et al. 2004b).