• 전기학회논문지P
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• 제60권1호
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• pp.32-36
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• 2011

In this study, authors have proposed the autonomous state estimation which has been composed with IEC61850, GPS time synchronization and objective model design concept. The proposed method is able to supervise/correct measurement and communication error from SCADA. The major advantages of the proposed autonomous state estimation are that it is possible to evaluate integrity of data measured and transferred from SCADA, to reduce human intervention and to expense national-size applications such as EMS (Energy Management System), WAMS (Wide Area Monitoring System) or WAPS (Wide Area Protection System). This study addresses the issues related to the operation of the smart grid and proposes a new automated approach to achieve this goal. Through applying the proposed system to IEEE 14-bus test electric system, we prove the possibility of the proposed idea.

• 전기학회논문지
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• 제57권5호
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• pp.839-844
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• 2008

A novel state of health estimation method for hybrid electric vehicle lithium battery using sliding mode observer has been presented. A simple R-C circuit method has been used for the lithium battery modeling for the reduced calculation time and system resources due to the simple matrix operations. The modeling errors of simple model are compensated by the sliding mode observer. The design methodology for state of health estimation using dual sliding mode observer has been presented in step by step. The structure of the proposed system is simple and easy to implement, but it shows robust control property against modeling errors and temperature variations. The convergence of proposed observer system has been proved by the Lyapunov inequality equation and the performance of system has been verified by the sequence of urban dynamometer driving schedule test. The test results show the proposed observer system has superior tracking performance with reduced calculation time under the real driving environments.

• 설비공학논문집
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• 제11권1호
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• pp.125-132
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• 1999

Studies are being done to replace conventional refrigerants with alternatives that have low or no ozone depletion and greenhouse warming Potentials, yet possess appropriate pro perties for a refrigeration cycle. To achieve this goal, a consistent set of thermodynamic properties of the working fluid is required. A common problem with the possible alternative refrigerants is that sufficient experimental data do not exist, thus making it difficult to develp complete equations of state that can predict properties in all regions including the vapor-liquid equilibrium. One solution is the use of the generalized equation of state correlations that can predict thermodynamic properties with a minimum number of characteristic parameters. Characteristic parameters required for the generalized equation of state are, in general, critical temperature, critical pressure, critical volume and normal boiling temperature. In this study, estimation of these characteristic parameters of refrigerants by group contribution method is developed.

• 전기학회논문지P
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• 제57권2호
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• pp.115-120
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• 2008

The EKF(Extended Kalman filter) method which is the state estimation algorithm of nonlinear stochastic system depends on the initial error and the estimated states. Therefore, the divergence of the estimated state can be caused if the initial values of the estimated states are not chosen as approximate real state values. In this paper, the demerit of the existing EKF method is improved using the EKF algorithm transformated by STWS(Single Term Walsh Series). This method linearizes each sampling interval of continous-time system through the derivation of an algebraic iterative equation without discretizing continuous system by the characteristic of STWS, the convergence of the estimated states can be improved. The validity of the proposed method is checked through comparison with the existing EKF method in simulation.

• 제어로봇시스템학회논문지
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• 제11권6호
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• pp.477-483
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• 2005

This article describes a robust state estimation method which enables to produce reliable estimates in spite of heavy perturbation including plant uncertainty and external disturbances. The main idea is to combine the standard state estimator with the perturbation observer in the estimator frame. The perturbation observer reflects equivalent quantity of plant uncertainty and external disturbances during the estimation process so that the state estimator dynamics gets as close as possible to the real plant dynamics. The robust state estimator proposed in this paper is given in a recursive discrete-time form which is very useful fur implementation purpose. In terms of the error dynamics derived for the robust state estimator, we discuss the stability issue and noise sensitivity. The effectiveness and practicality of the robust state estimator are verified through numerical examples and experimental results.

• Journal of applied mathematics & informatics
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• 제39권5_6호
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• pp.851-858
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• 2021

In general, secondary batteries are widely used as an electric energy source. Among them, the state of energy storage of mobile devices is very important information. As a method of estimating a state, there is a method of estimating the state by integrating the current according to an energy storage state of a battery, and a method of designing a state estimator by measuring a voltage and estimating a charge amount based on a battery model. In this study, we designed the state estimator using an extended Kalman filter to increase the precision of the state estimation of the charge amount by including the error of the system model and having the robustness to the noise.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2016년도 전력전자학술대회 논문집
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• pp.309-310
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• 2016

Sealed flooded lead acid batteries are becoming popular in the industry because of their low cost as compared to their counterparts. State of Charge (SOC) estimation has always been an important factor in battery management systems. For the accurate SOC estimation, open circuit voltage (OCV) hysteresis should be modelled accurately. The hysteresis phenomenon of the sealed flooded lead acid battery is discussed in detail and its ultimate modeling is proposed based on the conventional parallelogram method. The SOC estimation is performed by using Unscented Kalman Filter (UKF) while the parameters of the battery are estimated using Auto Regressive with external input (ARX) method. The validity of the proposed method is verified by the experimental results. The SOC estimation error by the proposed method is less than 3 % all wing the 125hr test.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2013년도 추계학술대회 논문집
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• pp.200-201
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• 2013

This paper investigates a new approach for Li-Ion battery state-of-charge (SOC) estimation using sliding mode observer (SMO) technique including parameters aging compensation via recursive least squares (RLS). The main advantages of this approach would be low computational load, easiness of implementation along with the robustness of the method for internal battery model parameters estimation. The proposed algorithm was first tested on a set of acquired battery data using implementation in Simulink and later developed as C-code module for firmware application.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.980-983
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• 1996

A new version of the discrete-time optimal FIR (finite impulse response) filter utilizing only the measurements of finite sliding estimation window is suggested for linear time-invariant state-space models. This filter is called the BLUFIR (best linear unbiased finite impulse response) filter since it provides the BLUE (best linear unbiased estimate) of the state obtained from the measurements of the estimation window. It is shown that the BLUFIR filter has the deadbeat property when there are no noises in the estimation window.

• 전기의세계
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• 제28권3호
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• pp.57-64
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• 1979

The static state estimation are divided into two groups; estimation and detection & identification. This paper centers on detection and identification algorithm. Especially, the identification of line errors is focused on and is performed by the extended W.L.S. algorithm with line swithching states. Here, line switching states mean the discrete values of line admittance which are influenced by unexpected line switching. The numerical results are obtained from the assumption that the noise vector is independent zero mean Gaussian random variables.