• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.847-858
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• 2015

Control strategy and corresponding parameters have significant impacts on the overall technical and economic characteristics of composite energy storage systems (CESS). A better control strategy and optimized control parameters can be used to improve the economic and technical characteristics of CESS, and determine the maximum power and stored energy capacity of CESS. A novel coordinated control strategy is proposed considering the coordination of various energy storage systems in CESS. To describe the degree of coordination, a new index, i.e. state of charge coordinated response margin of supercapacitor energy storage system, is presented. Based on the proposed control strategy and index, an optimization model was formulated to minimize the total equivalent cost in a given period for two purposes. The one is to obtain optimal control parameters of an existing CESS, and the other is to obtain the integrated optimal results of control parameters, maximum power and stored energy capacity for CESS in a given period. Case studies indicate that the developed index, control strategy and optimization model can be extensively applied to optimize the economic and technical characteristics of CESS. In addition, impacts of control parameters are discussed in detail.

• Journal of Power Electronics
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• v.19 no.4
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• pp.1054-1067
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• 2019

This paper systematically investigates the influence of device parameters spread on the current distribution of paralleled silicon carbide (SiC) MOSFETs. First, a variation coefficient is introduced and used as the evaluating norm for the parameters spread. Then a sample of 30 SiC MOSFET devices from the same batch of a well-known company is selected and tested under the same conditions as those on datasheet. It is found that there is big difference among parameters spread. Furthermore, comprehensive theoretical and simulation analyses are carried out to study the sensitivity of the current imbalance to variations of the device parameters. Based on the concept of the control variable method, the influence of each device parameter on the steady-state and transient current distributions of paralleled SiC MOSFETs are verified separately by experiments. Finally, some screening suggestions of devices or chips before parallel-connection are provided in terms of different applications and different driver configurations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.1749-1773
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• 2024

Recent advances in deep neural networks (DNNs) have greatly improved the accuracy and universality of various intelligent applications, at the expense of increasing model size and computational demand. Since the resources of end devices are often too limited to deploy a complete DNN model, offloading DNN inference tasks to cloud servers is a common approach to meet this gap. However, due to the limited bandwidth of WAN and the long distance between end devices and cloud servers, this approach may lead to significant data transmission latency. Therefore, device-edge collaborative inference has emerged as a promising paradigm to accelerate the execution of DNN inference tasks where DNN models are partitioned to be sequentially executed in both end devices and edge servers. Nevertheless, collaborative inference in heterogeneous edge environments with multiple edge servers, end devices and DNN tasks has been overlooked in previous research. To fill this gap, we investigate the optimization problem of collaborative inference in a heterogeneous system and propose a scheme CIS, i.e., collaborative inference scheme, which jointly combines DNN partition, task offloading and scheduling to reduce the average weighted inference latency. CIS decomposes the problem into three parts to achieve the optimal average weighted inference latency. In addition, we build a prototype that implements CIS and conducts extensive experiments to demonstrate the scheme's effectiveness and efficiency. Experiments show that CIS reduces 29% to 71% on the average weighted inference latency compared to the other four existing schemes.

• Computers and Concrete
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• v.13 no.1
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• pp.117-133
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• 2014

This study presents a rapid method for determining the steady state migration coefficient of concrete by measuring the electric current. This study determines the steady state chloride migration coefficient using the accelerated chloride migration test (ACMT). There are two stages to obtain the chloride migration coefficient. The first stage, the steady-state condition was obtained from the initial electric current at the beginning of ACMT. The second stage, the average electrical current in the steady state condition was used to determine the steady state chloride migration coefficient. The chloride migration coefficient can be determined from the average steady state current to avoid sampling and analyzing chlorides during the ACMT.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2003.09a
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• pp.66-73
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• 2003

The technique for the seismic reliability evaluation of the electric power network is presented. In the previous study, the state of the substations was represented by the bi-state which is classified as failure or survival. However, the hi-state model can result in oversimplified analysis, because substations are worked by the parallel operating system. In this paper, Considering the characteristics of the parallel operating system, the damage of the substation is expressed by the multi-state for the more realistic seismic reliability evaluation. Using Monte-Carlo simulation method, the seismic reliability for Korean 345㎸ electric power network is evaluated. Analysis results show that reliability levels of the network by the multi-state analysis is higher than that by the hi-state analysis and the electric power network in southeastern area of the Korean Peninsular may be vulnerable to earthquakes.

• Journal of Magnetics
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• v.22 no.1
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• pp.43-48
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• 2017

In order to detect the current flowing through concealed conductor, this paper proposes a new method based on derivative method. Firstly, this paper analyzes the main peak characteristic of the derivative function of magnetic field generated by a current-carrying conductor, and a relationship between the current flowing through the conductor and the main peak of the derivative function is obtained and applied to calculate the current. Then, the method is applied to detect the conductor current flowing through grounding grids of substations. Finally, the numerical experimental and field experiment verified the feasibility and accuracy of the method, and the computing results show that the method can effectively measure the conductor current of grounding grids with low error, and the error is within 5 %.

• Nuclear Engineering and Technology
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• v.49 no.1
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• pp.134-140
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• 2017

A well-performed core power control to track load changes is crucial in pressurized water reactor (PWR) nuclear power stations. It is challenging to keep the core power stable at the desired value within acceptable error bands for the safety demands of the PWR due to the sensitivity of nuclear reactors. In this paper, a state-space model predictive control (MPC) method was applied to the control of the core power. The model for core power control was based on mathematical models of the reactor core, the MPC model, and quadratic programming (QP). The mathematical models of the reactor core were based on neutron dynamic models, thermal hydraulic models, and reactivity models. The MPC model was presented in state-space model form, and QP was introduced for optimization solution under system constraints. Simulations of the proposed state-space MPC control system in PWR were designed for control performance analysis, and the simulation results manifest the effectiveness and the good performance of the proposed control method for core power control.

• International Journal of Automotive Technology
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• v.8 no.3
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• pp.361-373
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• 2007

In previous work, an approach based on maximizing the efficiency of an internal combustion engine while ignoring the power conversion efficiency of other powertrain components, such as the electric motor and power battery or ultracapacitor, was implemented in the steady-state optimization of an internal combustion engine for hybrid electric vehicles. In this paper, a novel control algorithm was developed and successfully justified as the basis for maximal power conversion efficiency of overall powertrain components. Results indicated that fuel economy improvement by 3.9% compared with the conventional control algorithm under China urban transient-state driving-cycle conditions. In addition, using the view of the novel control algorithm, maximal power generation of the electric motor can be chosen.

• Journal of Electrical Engineering and Technology
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• v.11 no.5
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• pp.1116-1127
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• 2016

• Fire Science and Engineering
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• v.28 no.3
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• pp.87-91
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• 2014

This paper is aimed to find electrical fire danger for analyzing the characteristics of temperature, current and voltage signals for motor on electric fan. In order to attain this purpose, detected were the temperature, current and voltage signals on electric wire with free (normal state) and locked (abnormal state) motor. For voltage and current signals, voltage signal is no big difference with normal and abnormal states and current signal is higher in abnormal state (highest 309 mA) than the normal state (highest 203 mA). In the case of Temperature signal, the temperature distribution of the motor as a whole is different. It is difference in the case of the normal state $4^{\circ}C$ and the abnormal state $18^{\circ}C$. In particular, most of the electric wiring to the motor of the fan is attached to the fixture of motor back. Considering at allowable temperature ($60^{\circ}C$) of the electric wire could be accelerated to insulation deterioration. The results of this study will be effectively used in analyzing for electric fire and developing the preventive devices of electric fan.