• Journal of Power Electronics
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• v.13 no.3
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• pp.429-436
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• 2013

Online simulations are utilized to reduce time and cost in the development and performance optimization of plug-in hybrid electric vehicle (PHEV) and electric vehicles (EV) systems. One of the most important factors in an online simulation is the accuracy of the model. In particular, a model of a battery should accurately reflect the properties of an actual battery. However, precise dynamic modeling of high-capacity battery systems, which significantly affects the performance of a PHEV, is difficult because of its nonlinear electrochemical characteristics. In this study, a dynamic model of a high-capacity battery cell for a PHEV is developed through the extraction of the equivalent impedance parameters using electrochemical impedance spectroscopy (EIS). Based on the extracted parameters, a battery cell model is implemented using MATLAB/Simulink, and charging/discharging profiles are executed for comparative verification. Based on the obtained results, the model is optimized for a high-capacity battery cell for a PHEV. The simulation results show good agreement with the experimental results, thereby validating the developed model and verifying its accuracy.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.7
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• pp.29-40
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• 2009

This paper proposes a modeling and controller design approach for a hybrid wind power generation system that considers a fixed wind-turbine and a dump load. Since operating conditions are kept changing, it is challenge to design a control for reliable operation of the overall system To consider variable operating conditions, Takagi-Sugeno (TS) fuzzy model is taken into account to represent time-varying system by expressing the local dynamics of a nonlinear system through sub-systems, partitioned by linguistic rules. Also, each fuzzy model has uncertainty. Thus, in this paper, a modem nonlinear control design technique, the sliding mode nonlinear control design, is utilized for robust control mechanism In the simulation study, the proposed controller is compared with a proportional-integral (PI) controller. Simulation results show that the proposed controller is more effective against disturbances caused by wind speed and load variation than the PI controller, and thus it contributes to a better quality wind-hybrid power generation system.

• Journal of the Korea Institute of Military Science and Technology
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• v.19 no.5
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• pp.559-566
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• 2016

Cables for Towed Array Sonar System(TASS) were developed. In order to verify the performance of cables, environmental and operational conditions as well as functional requirements were investigated during design stage. Double armored high and low voltage integrated cable for towed body and two kinds of cables, armored and light weight power and optic hybrid cables for towed array sensor system were developed by modeling and simulation. Customized manufacturing process and test method, such as foam extrusion and dynamic fatigue test were applied to this development. In conclusion, underwater towed hybrid cable with high tensile strength and compact structure were developed.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.10a
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• pp.285-289
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• 2009

In this paper, we propose to research the dynamic Matlab/Simulink model of supercapacitor bank(SCB) for a microgrid application. We demonstrated that this model id sufficient to design the control system of entire power storage system, SCB, the chopper and grid connected converter. The proposed dynamic model is simulated with the help of Matlab/$Simulink^{TK}$ in the MTG/PC/SCB hybrid energy system. The study results show that SCB have a good performance to curb power fluctuation in building microgrid application.

• Transactions of the Korean hydrogen and new energy society
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• v.30 no.2
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• pp.136-146
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• 2019

A solid oxide fuel cell (SOFC) based hybrid desiccant cooling system model is developed to study the effect of fuel utilization rate of the SOFC on the reduction of energy consumption and $CO_2$ emission. The SOFC-based hybrid desiccant cooling system consists of an SOFC system and a Hybrid desiccant cooling system (HDCS). The SOFC system includes a stack and balance of plant (BOP), and HDCS. The HDCS consists of desiccant rotor, indirect evaporative cooler, electric heat pump (EHP), and heat exchangers. In this study, using energy load data of a commercial office building and SOFC-based HDCS model, the amount of ton of oil equivalent (TOE) and ton of $CO_2$ ($tCO_2$) are calculated and compared with the TOE and $tCO_2$ generation of the EHP using grid electricity.

• Earthquakes and Structures
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• v.24 no.6
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• pp.393-404
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• 2023

This paper presents the application of hybrid-simulation-based adapter elements for the non-linear two-scale analysis of reinforced concrete frames with masonry infills under seismic-like demands. The approach provides communication and distribution of the computations carried out by two or more remote or locally distributed numerical models connected through the OpenFresco Framework. The modeling consists of a global analysis formed by macro-elements to represent frames and walls, and to reduce global degrees of freedom, portions of the structure that require advanced analysis are substituted by experimental elements and dimensional couplings acting as interfaces with their respective sub-assemblies. The local sub-assemblies are modeled by solid finite elements where the non-linear behavior of concrete matrix and masonry infill adopt a continuum damage representation and the reinforcement steel a discrete one, the conditions at interfaces between concrete and masonry are considered through a contact model. The methodology is illustrated through the analysis of a frame-wall system subjected to lateral loads comparing the results of using macro-elements, finite element model and experimental observations. Finally, to further assess and validate the methodology proposed, the paper presents the pushover analysis of two more complex structures applying both modeling scales to obtain their corresponding capacity curves.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.7
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• pp.536-543
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• 2004

In this paper, we proposed a new method of modeling a neuro-fuzzy system using a hybrid clustering algorithm. The initial parameters and the number of clusters of the proposed system are optimally chosen simultaneously with respect to the process of regression, which is a unique characteristics of the proposed system. The proposed algorithm presented in this work improves the overall performance of the proposed a neuro-fuzzy system by choosing a proper number of clusters adaptively according the characteristics of given data. The process of clustering is performed by deciding on the number of classes, which yields the property of convergence of the system. In experiments, the superiority of the proposed neuro-fuzzy system is demonstrated, especially the process of optimizing parameters and clustering of learning speed.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1145-1150
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• 1993

In this paper, two methods of fuzzy modeling are prsented to describe the input-output relationship effectively based on relation characteristics utilizing simplified reasoning and neuro-fuzzy reasoning. The methods of modeling by the simplified reasoning and the neuro-fuzzy reasoning are used when the input-output relation of a system is 'crisp' and 'fuzzy', respectively. The structure and the parameter identification in the modeling method by the simplified reasoning are carried out by means of FCM clustering and the proposed GA hybrid scheme, respectively. The structure and the parameter identification in the modeling method by the neuro-fuzzy reasoning are carried out by means of GA and BP algorithm, respectively. The feasibility of the proposed methods are evaluated through simulation.

• Structural Engineering and Mechanics
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• v.61 no.2
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• pp.283-293
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• 2017

The main contribution of the present paper is to propose an intelligent fuzzy inference system approach for modeling the debonding strength of masonry elements retrofitted with Fiber Reinforced Polymer (FRP). To achieve this, the hybrid of meta-heuristic optimization methods and adaptive-network-based fuzzy inference system (ANFIS) is implemented. In this study, particle swarm optimization with passive congregation (PSOPC) and real coded genetic algorithm (RCGA) are used to determine the best parameters of ANFIS from which better bond strength models in terms of modeling accuracy can be generated. To evaluate the accuracy of the proposed PSOPC-ANFIS and RCGA-ANFIS approaches, the numerical results are compared based on a database from laboratory testing results of 109 sub-assemblages. The statistical evaluation results demonstrate that PSOPC-ANFIS in comparison with ANFIS-RCGA considerably enhances the accuracy of the ANFIS approach. Furthermore, the comparison between the proposed approaches and other soft computing methods indicate that the approaches can effectively predict the debonding strength and that their modeling results outperform those based on the other methods.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.69.5-69
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• 2002

1. Introduction 2. System Description 3. Hybrid Modeling of SM Reactor 4. Simulation Results 5. Optimization of Operating Condition 6. Conculsion