• Journal of Drive and Control
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• v.16 no.2
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• pp.80-90
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• 2019

Fuel cell hybrid electric vehicle is an attractive solution to reduce pollutants, such as noise and carbon dioxide emission. This study presents an approach for energy management and control algorithm based on energetic macroscopic representation for a fuel cell hybrid electric vehicle that is powered by proton exchange membrane fuel cell, battery and supercapacitor. First, the detailed model of the fuel cell hybrid electric vehicle, including fuel cell, battery, supercapacitor, DC-DC converters and powertrain system, are built on the energetic macroscopic representation. Next, the power management strategy was applied to manage the energy among the three power sources. Moreover, the control scheme that was based on back-stepping sliding mode control and inversed-model control techniques were deduced. Simulation tests that used a worldwide harmonized light vehicle test procedure standard driving cycle showed the effectiveness of the proposed control method.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.355-363
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• 2022

This paper presents the modeling for islanded hybrid AC/DC microgrid and the verification of the proposed supervisory controller for energy management for this microgrid. The supervisory controller allows the microgrid system to operate in different power flows through the proposed control algorithm, it has several roles in the management of the energy flow between the different components of the microgrid for reliable operation. The proposed microgrid has both essential objectives such as the maximum use of renewable energies resources and the reduction of multiple conversion processes in an individual AC or DC microgrids. The microgrid system considered for this study has a solar photovoltaic (PV), a wind turbine (WT), a battery (BT), and a AC/DC loads. A small islanded hybrid AC/DC microgrid has been modeled and simulated using the MATLAB-Simulink. The simulation results show that the system can maintain stable operation under the proposed supervisory controller when the microgrid is switched from one operating mode of energy flow to another.

• Journal of the Korean Society of Propulsion Engineers
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• v.26 no.3
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• pp.1-9
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• 2022

The aircraft targeted in this study is a vertical take-off and landing aircraft with 4 to 5 passengers, and the propulsion system for the aircraft is a distributed hybrid propulsion system that uses a gas turbine engine and a battery pack as the main power source to supply the power required by multiple motors. In this study, a design/analysis platform for a hybrid propulsion system was developed using the MATLAB/Simulink program based on the preliminary design results. Through simulation analysis, the output characteristics and operating range of each power source according to the mission profile were confirmed, and through this, the feasibility of the preliminary design result was confirmed.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.5
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• pp.1303-1317
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• 2024

The development of high-performance underwater propulsion devices has gained importance with the expansion of recreational and industrial diving applications. This study aims to develop and validate a waterjet-type diver propulsion system capable of achieving a top speed of 3.8 knots and an operational time of over 120 minutes. Utilizing advanced modeling and simulation techniques, the design focuses on minimizing hydrodynamic resistance and optimizing buoyancy. Structural and fluid dynamic analyses were conducted to ensure the device's stability and performance under 20 atm pressure at a depth of 200 meters. The propulsion system employs a sensorless BLDC motor and a 36V lithium-ion battery pack to enhance efficiency and reliability. Field tests confirmed an average speed of 3.88 knots and a continuous operation time of 150 minutes, exceeding the initial targets. This research demonstrates significant advancements in diver propulsion technology, providing valuable insights for future underwater equipment development. The outcomes are poised to enhance the safety, efficiency, and usability of diver propulsion devices, with broader applications in marine research, environmental monitoring, and resource exploration.

• Aerospace Engineering and Technology
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• v.9 no.2
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• pp.176-184
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• 2010

The power simulator for a LEO satellite is a useful tool to analyze mission validity and energy balance for various mission scenarios by estimating power generation, power consumption, depth of discharge, bus voltage, charging/discharging current, etc. In this paper, it is described the calculation algorithm of the solar array (SA) power, the satellite load power and the battery modeling method to develop a satellite power simulation. To simulate the SA power generation, three different operation modes (DET, MPPT, CV) of SAR (Solar Array Regulator) are considered with a SA model. The satellite load power is estimated using the satellite unit power database, the unit on/off configuration at some satellite operation modes. The bus voltage and battery charging/discharging current at the specific DoD (Depth of Discharge) are calculated based on the battery characteristics. By this satellite power simulator, it can be conveniently analyzed the energy balance and the validity of a planned mission of a LEO satellite.

• Journal of Energy Engineering
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• v.20 no.4
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• pp.278-285
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• 2011

Computational modelling and simulation for the charge-discharge characteristics of Lithium-ion batteries have been carried out. The battery system consists of a simplified 2-dimensional single cell for the modelling, in which the thermal modelling on the charge-discharge characteristics was conducted in the temperature range from 288 K through 318 K by using FEMLAB as an engineering PDE solver. While material parameters adopted in the present modelling were dependent on the system temperature, their thermal modelling were applied on the simulations of the charge-discharge period and the rate of transferring charges systematically. The resulting simulation shows that the cycle of the charge-discharge shorten itself by reducing the system temperature, regardless of the charge-discharge rates. In addition, the mass-transport phenomena of Lithium ion have been discussed in connection with the charge-discharge characteristics in the battery.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.2
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• pp.477-485
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• 2015

Most existing simulators for wireless sensor networks(WSNs) are modeling battery-based sensors and providing MAC and routing protocols designed for battery-based WSNs. However, recently, as energy harvesting sensor systems have been studied more extensively, there is an increasing need for appropriate simulators, but few related studies have employed such simulators. Unlike existing simulators, simulators for energy harvesting WSNs require a new energy model that is integrated with the energy-harvesting model, rechargeable battery model, and energy-consuming model. Additionally, it should enable the applications of the well-known MAC and routing protocols designed for energy-harvesting WSNs, as well as a user-friendly interface for convenience. In this work, we design and implement a user-friendly simulator for solar energy-harvesting WSNs.

• Journal of the Korean Institute of Gas
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• v.24 no.6
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• pp.91-97
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• 2020

Lithium-ion batteries (LIBs) have a longer lifespan, higher energy density, and lower self-discharge rates than other batteries, therefore, they are preferred as an Energy Storage System (ESS). However, during years 2017-2019, 28 ESS fire accidents occurred in Korea, and accurate capacity estimation of LIB is essential to ensure safety and reliability during operations. In this study, data-driven modeling that predicts capacity changes according to the charging cycle of LIB was conducted, and developed models were compared their performance for the selection of the optimal machine learning model, which includes the Decision Tree, Ensemble Learning Method, Support Vector Regression, and Gaussian Process Regression (GPR). For model training, lithium battery test data provided by NASA was used, and GPR showed the best prediction performance. Based on this study, we will develop an enhanced LIB capacity prediction and remaining useful life estimation model through additional data training, and improve the performance of anomaly detection and monitoring during operations, enabling safe and stable ESS operations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1603-1611
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• 2021

As IMO environmental regulations are tightened, the need to establish a system that can reduce emissions is increasing, and for this purpose, various power control management systems have been studied and implemented as a new energy management system for ships. In this study, we design a control process through modeling for Bi-Directional Converter (BDC) application with bi-directional power flow to link batteries, which are energy storage devices, to conventional generator power systems, and propose mechanisms for batteries optimized for varying loads. This work models MATLAB/Simulink as a BDC and simulates current control and state of charge (SOC) optimization at the time of charging and discharging batteries according to load scenarios. Through this, the battery, power, and load were interlocked so that the generator operated on board could be operated in the optimal operation range, and power control management was performed to enable the generator to operate in the high fuel efficiency range.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.1
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• pp.121-135
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• 2013

This paper propose an efficient algorithm for selecting electric bus charging facility location. In nature, the optimal charging facility location problem is similar to Set Covering Problem. Set Covering Problem is the problem of covering all the rows of an $m{\times}n$ matrix of ones and zeros by a subset of columns with a minimal cost. It has many practical applications of modeling of real world problems. The Set Covering Problem has been proven to be NP-Complete. In order to overcome the computational complexity involved in seeking optimal solutions, this paper present an enhanced greedy algorithm and simulated annealing algorithm. In this paper, we apply the developed algorithm to Seoul's public bus system.