• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.733-741
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• 2018

Capacity estimation is indispensable to ensure the safety and reliability of lithium-ion batteries in electric vehicles (EVs). Therefore it's quite necessary to develop an effective on-board capacity estimation technique. Based on experiment, it's found constant current charge time (CCCT) and the capacity have a strong linear correlation when the capacity is more than 80% of its rated value, during which the battery is considered healthy. Thus this paper employs CCCT as the health indicator for on-board capacity estimation by means of relevance vector machine (RVM). As the ambient temperature (AT) dramatically influences the capacity fading, it is added to RVM input to improve the estimation accuracy. The estimations are compared with that via back-propagation neural network (BPNN). The experiments demonstrate that CCCT with AT is highly qualified for on-board capacity estimation of lithium-ion batteries via RVM as the results are more precise and reliable than that calculated by BPNN.

• ETRI Journal
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• v.37 no.1
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• pp.11-20
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• 2015

This paper deals with optimal power allocation for channel estimation of orthogonal frequency-division multiplexing uplinks in time-varying channels. In the existing literature, the estimation of time-varying channel response in an uplink environment can be accomplished by estimating the corresponding channel parameters. Accordingly, the optimal power allocation studied in the literature has been in terms of minimizing the mean square error of the channel estimation. However, the final goal for channel estimation is to enable the application of coherent detection, which usually means high spectral efficiency. Therefore, it is more meaningful to optimize the power allocation in terms of capacity. In this paper, we investigate capacity with imperfect channel estimation. By exploiting the derived capacity expression, an optimal power allocation strategy is developed. With this developed power allocation strategy, improved performance can be observed, as demonstrated by the numerical results.

• Structural Engineering and Mechanics
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• v.60 no.6
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• pp.1021-1038
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• 2016

Considerable part of reinforced concrete building has suffered from destructive earthquakes in Turkey. This situation makes necessary to determine nonlinear behavior and seismic performance of existing RC buildings. Inelastic response of buildings to static and dynamic actions should be determined by considering both flexural plastic hinges and brittle shear hinges. However, shear capacities of members are generally neglected due to time saving issues and convergence problems and only flexural response of buildings are considered in performance assessment studies. On the other hand, recent earthquakes showed that the performance of older buildings is mostly controlled by shear capacities of members rather than flexure. Demand estimation is as important as capacity estimation for the reliable performance prediction in existing RC buildings. Demand estimation methods based on strength reduction factor (R), ductility (${\mu}$), and period (T) parameters ($R-{\mu}-T$) and damping dependent demand formulations are widely discussed and studied by various researchers. Adopted form of $R-{\mu}-T$ based demand estimation method presented in Eurocode 8 and Turkish Earthquake Code-2007 and damping based Capacity Spectrum Method presented in ATC-40 document are the typical examples of these two different approaches. In this study, eight different existing RC buildings, constructed before and after Turkish Earthquake Code-1998, are selected. Capacity curves of selected buildings are obtained with and without considering the brittle shear capacities of members. Seismic drift demands occurred in buildings are determined by using both $R-{\mu}-T$ and damping based estimation methods. Results have shown that not only capacity estimation methods but also demand estimation approaches affect the performance of buildings notably. It is concluded that including or excluding the shear capacity of members in nonlinear modeling of existing buildings significantly affects the strength and deformation capacities and hence the performance of buildings.

• Proceedings of the Safety Management and Science Conference
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• 2002.05a
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• pp.257-262
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• 2002

There are two methodologies to increase transport capacity of railway. The one is to invest railroad equipment or vehicles, and the other is to improve operation efficiency through optimization. All of these is intended to increase transport capacity by improving line capacity So far, we treat line capacity as the criteria for evaluating investment alternatives or for restricting tram frequencies, and this criteria is calculated statical and experimental numerical formula. But, line capacity has special attribute that change dynamically according to operational condition, so there is a need of new line capacity estimation system. The Purpose of this paper is to present a new line capacity estimation system based on the probability simulation and its applications.

• Proceedings of the KSR Conference
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• 2002.05a
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• pp.122-127
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• 2002

There are two methodologies to increase transport capacity of railway. The one is to invest railroad equipment or vehicles, and the other to improve operation efficiency through operation optimization. All of these is intended to increase transport capacity by improving line capacity. So far, we treat line capacity as the criteria for evaluating investment alternatives or for restricting train frequencies, and this criteria is calculated statical and experimental numerical formula. But, line capacity has special attribute that change dynamically according to operational condition, so there is a need of new line capacity estimation system. The Purpose of this paper is to present a new line capacity estimation system based on the probability simulation and its applications.

• Journal of the Korea Safety Management & Science
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• v.4 no.3
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• pp.167-175
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• 2002

There are two methodologies to increase transport capacity of railway. One is to invest railroad equipment or vehicles, and the other is to improve operation efficiency through optimization. All of these is intended to increase transport capacity by improving the line capacity. So far, we treat the line capacity as the criteria for evaluating investment alternatives or for restricting train frequencies, and this criteria is calculated statical and experimental numerical formula. But, line capacity has special attribute that changes dynamically according to operational conditions, so there is a need of new line capacity estimation system. The Purpose of this paper is to present a new estimation system of line capacity based on the probability simulation and its applications.

• International Journal of Highway Engineering
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• v.17 no.5
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• pp.123-133
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• 2015

PURPOSES : This study aimed to develop a new highway capacity estimation method and provide comparative results among traditional capacity estimation methods and the recommended values in the latest version of KHCM. METHODS : The limitations of the existing methods, such as inconsistency and underestimation of the capacity value, are summarized through an extensive literature review. To overcome these limitations, a new method is introduced by adopting a definition of capacity and traffic flow characteristics at or near breakdown points. This method can produce the capacity value by searching a point corresponding to the maximum traffic flow through analysis of gradient changes (point of inflection) of the traffic flow and speed distribution. Comparative results of capacity values from each method are also presented to validate the new method by using data collected from detectors on freeways. RESULTS: From the analysis results, it is shown that a consistent capacity value can be estimated by applying the new method. In addition, the resulting capacity values are 3%-4% higher than those recommended in KHCM. CONCLUSIONS : The capacity values listed in the current KHCM tend to produce underestimated results. The new method presented in this paper may be included in the future edition of KHCM.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.693-698
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• 2000

Aspects of classical information theory, such as rate distortion theory, investigate how to encode and decode information from an independently identically distributed source so that the asymptotic distortion rate between the source and its quantized representation is minimized. However, in most natural dynamics, the source state is highly corrupted by disturbances, and the measurement contains the noise. In recent coder-estimator sequence is developed for state estimation problem based on observations transmitted with finite communication capacity constraints. Unlike classical estimation problems where the observation is a continuous process corrupted by additive noises, the condition is that the observations must be coded and transmitted over a digital communication channel with finite capacity. However, coder-estimator sequence does not provide such a quantitative analysis as a variance for estimation error. In this paper, under the assumption that the estimation error is Gaussian distribution, a variance for coder-estimation sequence is proposed and its fitness is evaluated through simulations with a simple example.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.2
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• pp.92-95
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• 2015

Capacity reflecting effects of quantized feedback information is evaluated through computer simulation for practical implementation of polarization angle estimation and compensation. In the dual-polarization antenna case, evaluated capacity values varies more than four times depending on accuracy of the polarization angle estimation and compensation. Using 6-bit the quantized feedback information, we can achieve 96.8 percentage of the capacity of the perfect feedback information case.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.8
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• pp.63-68
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• 2004

The capacity of MIMO systems is numerically analyzed when channel estimation error exists. The analysis shows that the capacity is influenced by Mean Square Error (MSE) as well as average Signal to Noise Ratio (SNR). Furthermore, in this paper we present the standard selecting a channel estimator suitable to a system owing to get a tolerable channel estimation error in a given average SNR and channel capacity loss. The simulation results show that the tolerable MSEs for 1 bps/Hz capacity loss are about 10$^{-2}$ and 10$^{-4}$ at n dB and 40 dB average SNR, respectively.