• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.5
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• pp.58-65
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• 2015

This paper presents the design of an implantable stimulation IC intended for neural prosthetic devices using $0.18-{\mu}m$ standard CMOS technology. The proposed single-channel biphasic current stimulator prototype is designed to deliver up to 1 mA of current to the tissue-equivalent $10-k{\Omega}$ load using 12.8-V supply voltage. To utilize only low-voltage standard CMOS transistors in the design, transistor stacking with dynamic gate biasing technique is used for reliable operation at high-voltage. In addition, active charge balancing circuit is used to maintain zero net charge at the stimulation site over the complete stimulation cycle. The area of the total stimulator IC consisting of DAC, current stimulation output driver, level-shifters, digital logic, and active charge balancer is $0.13mm^2$ and is suitable to be applied for multi-channel neural prosthetic devices.

• Journal of Electrical Engineering and Technology
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• v.11 no.4
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• pp.905-914
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• 2016

This paper proposes a new phase current reconstruction technique for interleaved three-phase bidirectional dc-dc converters using a single current sensor. In the proposed current reconstruction algorithm, a single current sensor is employed at the dc-link, and the dc-link current information is sampled at either the peak or valley point of the pulse-width modulation (PWM) carriers regularly. From the obtained current information, all phase currents are reconstructed in a single PWM cycle. After that, the digital current controller is applied to achieve current balancing in each phase. Compare to the previous multiple current sensor method, the proposed strategy reduces the number of the current sensors in the interleaved three-phase bidirectional converter as well as reducing potential current sensing error caused by non-ideal characteristics of the multiple current sensors. The effectiveness of the proposed method is verified from the experiments based on a 3kW three-phase bidirectional converter prototype for the automotive battery charging application.

• Proceedings of the KIPE Conference
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• 2018.11a
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• pp.36-38
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• 2018

As the battery capacity requirement increases, battery cells are connected in a parallel configuration. However, the sharing current of each battery cell becomes unequal due to the imbalance between cell's impedance which results the mismatched states of charge (SOC). The conventional fixed-resistance balancing methods have a limitation in battery equalization performance and system efficiency. This paper proposes a battery equalization method based on dynamic resistance technique, which can improve equalization performance and reduce the loss dissipation. Based on the SOC rate of parallel connected battery cells, the switches in the equalization circuit are controlled to change the equivalent series impedance of the parallel branch, which regulates the current flow to maximize SOC utilization. To verify the method, operations of 4 parallel-connected 18650 Li-ion battery cells with 3.7V-2.6Ah individually are simulated on Matlab/Simulink. The results show that the SOCs are balanced within 1% difference with less power dissipation over the conventional method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.12B
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• pp.811-817
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• 2005

Efficient bandwidth management is necessary in order to provide high quality service to users in a multimedia wireless/mobile network. In this paper, I propose an on-line load balancing algorithm with preemption. This technique is able to balance the traffic load among cells accommodating heterogeneous multimedia services while ensuring efficient bandwidth utilization. The most important features of my algorithm are its adaptability, flexibility and responsiveness to current network conditions. In addition, my online scheme to control bandwidth adaptively is a cell-oriented approach. This approach has low complexity making it practical for real cellular networks. Simulation results indicate the superior performance of my algorithm.

• Journal of Theoretical and Applied Mechanics
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• v.3 no.1
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• pp.16-33
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• 2002

A concept of hierarchical modeling, the newest modeling technology. has been introduced early In 1990. This nu technology has a goat potential to advance the capabilities of current computational mechanics. A first step to Implement this concept is to construct hierarchical models, a family of mathematical models which are sequentially connected by a key parameter of the problem under consideration and have different levels in modeling accuracy, and to investigate characteristics In their numerical simulation aspects. Among representative model problems to explore this concept are elastic structures such as beam-, arch-. plate- and shell-like structures because the mechanical behavior through the thickness can be approximated with sequential accuracy by varying the order of thickness polynomials in the displacement or stress fields. But, in the numerical analysis of hierarchical models, two kinds of errors prevail: the modeling error and the numerical approximation errors. To ensure numerical simulation quality, an accurate estimation of these two errors Is definitely essential. Here, a local a posteriori error estimator for elastic structures with thin domain such as plate- and shell-like structures Is derived using element residuals and flux balancing technique. This method guarantees upper bounds for the global error, and also provides accurate local error Indicators for two types of errors, in the energy norm. Comparing to the classical error estimators using flux averaging technique, this shows considerably reliable and accurate effectivity indices. To illustrate the theoretical results and to verify the validity of the proposed error estimator, representative numerical examples are provided.

• Structural Engineering and Mechanics
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• v.8 no.5
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• pp.513-529
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• 1999

A concept of hierarchical modeling, the newest modeling technology, has been introduced in early 1990's. This new technology has a great potential to advance the capabilities of current computational mechanics. A first step to implement this concept is to construct hierarchical models, a family of mathematical models sequentially connected by a key parameter of the problem under consideration and have different levels in modeling accuracy, and to investigate characteristics in their numerical simulation aspects. Among representative model problems to explore this concept are elastic structures such as beam-, arch-, plate- and shell-like structures because the mechanical behavior through the thickness can be approximated with sequential accuracy by varying the order of thickness polynomials in the displacement or stress fields. But, in the numerical, analysis of hierarchical models, two kinds of errors prevail, the modeling error and the numerical approximation error. To ensure numerical simulation quality, an accurate estimation of these two errors is definitely essential. Here, a local a posteriori error estimator for elastic structures with thin domain such as plate- and shell-like structures is derived using the element residuals and the flux balancing technique. This method guarantees upper bounds for the global error, and also provides accurate local error indicators for two types of errors, in the energy norm. Compared to the classical error estimators using the flux averaging technique, this shows considerably reliable and accurate effectivity indices. To illustrate the theoretical results and to verify the validity of the proposed error estimator, representative numerical examples are provided.

• The Transactions of the Korean Institute of Power Electronics
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• v.26 no.2
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• pp.96-105
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• 2021

Large-scale power converters consist of series or parallel module combinations. In these modular converter systems, the interleaving technique can be applied to improve capacitor reliability by reducing the ripple of the I/O current in which each module operates as a phase difference. However, when applying the interleaving technique for conventional three-level boost converters, the short-circuit period of the converter can be an obstacle. Such problem is caused by the absence of a low-level inductor of the conventional three-level boost converter. To solve this problem, a three-level boost converter with a low-level inductor is proposed and analyzed to enable interleaved operation. In the proposed circuit, the current ripple of the output capacitor depends on the neutral point connections between the modules. In this study, the ripple current is analyzed by the neutral point connections of the three-level boost converter that has a low-level inductor, and the effectiveness of the proposed circuit is proven by simulation and experiment.

• Journal of Ocean Engineering and Technology
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• v.27 no.4
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• pp.83-89
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• 2013

A numerical scheme based on a mode superposition method is presented for the dynamic response analysis of a top-tensioned riser (TTR) under sheared current loads. The natural frequencies and mode shapes of the TTR have been calculated analytically for a beam with a slowly varying tension and pinned-pinned boundary conditions at the top and bottom ends. The lift coefficients and corresponding amplitudes used to estimate the vortex-induced modal force and damping for each mode were predicted via iterative calculations based on the input and output power balancing concept. Here, the power-in regions were controlled by the normal distribution function, for which the center was coincident with the lock -in location by local vortex-shedding, and the range was defined by the constant standard deviation for the reduced velocity by the local current speed. Finally, dynamic responses such as root-mean-squared displacement and stress were calculated using the mode superposition technique. In order to verify the presented scheme, a numerical calculation was performed for a TTR under an arbitrary linearly sheared current and linearly varying tension. A comparison with the results of the existing software showed that the presented scheme could give reliable and feasible solutions. Case studies were performed to investigate the effects of various current loads and tensions.

• Journal of Power Electronics
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• v.16 no.2
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• pp.654-665
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• 2016

The pumping of electric power from photovoltaic (PV) farms is normally carried out using transformers, which require heavy mounting structures and are thus costly, less efficient, and bulky. Therefore, transformerless schemes are developed for the injection of power into the grid. Compared with the H4 inverter topology, the H6 topology is a better choice for pumping PV power into the grid because of the reduced common mode current. This paper presents how the perturb and observe (P&O) algorithm for maximum power point tracking (MPPT) can be implemented in the H6 inverter topology along with the improved sinusoidal current injected to the grid at unity power factor with the average current mode control technique. On the basis of the P&O MPPT algorithm, a power reference for the present insolation level is first calculated. Maintaining this power reference and referring to the AC sine wave of bus bars, a sinusoidal current at unity power factor is injected to the grid. The proportional integral (PI) controller and fuzzy logic controller (FLC) are designed and implemented. The FLC outperforms the PI controller in terms of conversion efficiency and injected power quality. A simulation in the MATLAB/SIMULINK environment is carried out. An experimental prototype is built to validate the proposed idea. The dynamic and steady-state performances of the FLC controller are found to be better than those of the PI controller. The results are presented in this paper.

• Smart Structures and Systems
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• v.30 no.6
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• pp.613-626
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• 2022

Guaranteeing the quality and integrity of structural health monitoring (SHM) data is very important for an effective assessment of structural condition. However, sensory system may malfunction due to sensor fault or harsh operational environment, resulting in multiple types of data anomaly existing in the measured data. Efficiently and automatically identifying anomalies from the vast amounts of measured data is significant for assessing the structural conditions and early warning for structural failure in SHM. The major challenges of current automated data anomaly detection methods are the imbalance of dataset categories. In terms of the feature of actual anomalous data, this paper proposes a data anomaly detection method based on data-level and deep learning technique for SHM of civil engineering structures. The proposed method consists of a data balancing phase to prepare a comprehensive training dataset based on data-level technique, and an anomaly detection phase based on a sophisticatedly designed network. The advanced densely connected convolutional network (DenseNet) and Transformer encoder are embedded in the specific network to facilitate extraction of both detail and global features of response data, and to establish the mapping between the highest level of abstractive features and data anomaly class. Numerical studies on a steel frame model are conducted to evaluate the performance and noise immunity of using the proposed network for data anomaly detection. The applicability of the proposed method for data anomaly classification is validated with the measured data of a practical supertall structure. The proposed method presents a remarkable performance on data anomaly detection, which reaches a 95.7% overall accuracy with practical engineering structural monitoring data, which demonstrates the effectiveness of data balancing and the robust classification capability of the proposed network.