• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.780_781
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• 2009

This paper proposes efficiency optimization control of IPMSM drive using hybrid intelligent controller(HIC). The design of the speed controller based on fuzzy-neural network that is implemented using fuzzy control and neural network. The design of the current based on adaptive fuzzy control using model reference and the estimation of the speed based on neural network using ANN controller. In order to maximize the efficiency in such applications, this paper proposes the optimal control method of the armature current. The optimal current can be decided according to the operating speed and the load conditions. This paper proposes speed control of IPMSM using ALM-FNN, current control of model reference adaptive fuzzy control(MTC) and estimation of speed using ANN controller. The proposed control algorithm is applied to IPMSM drive system controlled HIC, the operating characteristics controlled by efficiency optimization control are examined in detail.

• The Transactions of the Korean Institute of Power Electronics
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• v.8 no.4
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• pp.336-343
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• 2003

Generally, brushless DC motor(BLDCM) driving system uses hall sensors or encoders as the mechanical position or speed sensors. It is necessary to achieve the information's of rotor position for driving trapezoidal type brushless DC motor without any position sensor. This paper proposes a sensorless driving system with absolute rotor position detecting circuit which acquires both commutating phase and commutating time by analyzing motor phase voltages. Proposed system is applied to a 10k[W] rating motor which actually used in Hybrid Electric Vehicles. The experimental results will show the validity of the proposed system and the practical use of proposed sensorless drive.

• The Transactions of the Korean Institute of Power Electronics
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• v.10 no.3
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• pp.282-289
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• 2005

This paper proposes a fuzzy neural network controller based on the vector control for interior permanent magnet synchronous motor(IPMSM) drive system. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability This paper does not oかy presents speed control of IPMSM using neuro-fuzzy control(NFC) but also speed estimation using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. Thus, it is presented the theoretical analysis as well as the analysis results to verify the effectiveness of the proposed method in this paper.

• Journal of Power Electronics
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• v.8 no.4
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• pp.291-300
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• 2008

In this paper power system and drive-train for omni-directional autonomous mobile robots with multiple energy storage units are presented. Because in proposed system, which is implemented in soccer robots, the ability of power flow control from of multiple separated energy storage units and speed control for each motor are combined, these robots can be derived by more than one power source. This capability, allow robot to diversify its energy source by employing hybrid power sources. In this research Lithium ion polymer batteries have been used for main and auxiliary energy storage units because of their high power and energy densities. And to protect them against deep discharge, over current and short circuit, a protection circuit was designed. The other parts of our robot power system are DC-DC converters and kicker circuit. The simulation and experimental results show proposed scheme and extracted equations are valid and energy management and speed control can be achieved properly using this method. The filed experiments show robot mobility functions to perform the requested motion is enough and it has a high maneuverability in the field.

• Journal of Power Electronics
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• v.6 no.4
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• pp.322-329
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• 2006

In the last decade, the increasing restrictions imposed on the exhaust emissions from internal combustion engines and traffic limitations have increased the development of electrical propulsion systems for automotive applications. The goal of electrical and hybrid vehicles is the reduction of global emissions, which in turn leads to a decrease in fuel resource exploitation. This paper presents a novel approach for control of Induction Motors (IM) using the Particle Swarm Optimization (PSO) algorithm to optimize the parameters of the Proportional Integral Controller (PI-Controller). The overall system is simulated under various operating conditions. The use of PSO as an optimization algorithm makes the drive robust and insensitive to load variation with faster dynamic response and higher accuracy. The system is tested under variable operating conditions. The simulation results show a positive dynamic response with fast recovery time.

• The Transactions of the Korean Institute of Power Electronics
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• v.21 no.5
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• pp.388-395
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• 2016

Electric vehicles (EV) and hybrid EVs (HEV) are designed and manufactured by GM, Toyota, Honda, and Hyundai motors. The propulsion system design process for EV requires integrating subsystem designs into an overall system model to maximize the performance of a given propulsion architecture. Therefore, high-power density and high-torque density are important attributes required for EV applications. To improve torque and power density, propulsion motors are designed for saturation during high-torque operation. The nonlinearity associated with core saturation is modeled by incorporating the cross-coupling inductances, which also behave nonlinearly. Furthermore, in EV environments, the battery is directly connected to the DC link, and the battery changes depending on the state of charge. It will be onerous if as many optimal current commands as different $V_{dc}$ were made. This paper presents the optimal current commands in the various operating condition and the current control technique in EV environments.

• Transactions of the Korean Society of Automotive Engineers
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• v.15 no.2
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• pp.182-186
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• 2007

This paper studied performance characteristics of hybrid automotive to replace existing fossil fuel vehicles. Specially, about power split type HEV that is T-HEV's drive system when a vehicle drives at steady speed, monitored both output of each engine, motor and generator and battery SOC (state of charge) and analyzed performance characteristic of power transmission system and electricity power parts. This study shows those that acquired and analyzed information from signals between HCU and each controller of actual T- vehicle. From this study, it is confirmed that each conditions of EV and HEV drive can be a improvement with respect to the fuel efficiency of vehicles.

• Proceedings of the KIEE Conference
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• 2007.10c
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• pp.126-128
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• 2007

This paper proposes maximum torque control of IPMSM drive using Adaptive Fuzzy-Neuro controller and artificial neural network(ANN). The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. This paper proposes the analysis results to verify the effectiveness of the Adaptive Fuzzy-Neuro and ANN controller.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.10
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• pp.671-677
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• 2004

This paper presents the design of a now controller for the read/write head of a hard disk drive. The general controller for seeking is the time-optimal control. However if we use only the time optimal control law, this could be vulnerable to chattering effect. To solve this problem, we propose a modified controller design algorithm in this paper. The proposed controller consists of bang-bang control for seeking and sliding-mode control for tracking. Moreover, to test the robustness and stability of control system, a bounded disturbance is selected to maximize a severity index. Simulation results show the superiority of the proposed controller through comparison with time optimal VSC(variable structure control).

• International Journal of Fluid Machinery and Systems
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• v.1 no.1
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• pp.121-139
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• 2008

For mechanical drive steam turbines, the investigation results of corrosion fatigue phenomena in the transient zone are introduced, including basic phenomena on expansion line and actual design and damage experience. These results were analyzed from the standpoint of stress intensity during the start of cracking. In order to resolve such problems, preventive coating and blade design methods against fouling and corrosive environments are developed. Detailed evaluation test results are given for coating performance using a unique test procedure simulating fouling phenomena and washing conditions. Finally, the results of the successful modification of internals and on-line washing results on site are introduced.