• 한국기계가공학회지
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• 제11권5호
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• pp.1-7
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• 2012

The transportation is almost dependent on a single fuel petroleum with transportation energy dilemma. Hybrid Electric Vehicle(HEV) technology holds more advantages on efficiency improvements for petroleum consumption at the transportation. And bearing is recognized as the important component of gearbox. Gearboxes for HEV transmission have been ensured the highest reliability over some years in withstanding high dynamic loads. At the same time, the demands of lightweight design and cost minimization are required by thought-out design, high-quality material, superior production quality and maintenance. In order to design a reliable and lightweight gearbox, it is necessary to analyze bearing rating life methods between standard and different bearing companies with calculation methods for modification factors. In this paper, the influence of life time of bearings will be pointed out. Bearing contact stress and load stress distribution of HEV gearbox are obtained and compared with Romaxdesigner and BearinX. And the unequal wear of the left bearing for the gearbox intermediate shaft is investigated between simulation and test.

• 한국분무공학회지
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• 제19권1호
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• pp.25-32
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• 2014

For reduction of $CO_2$ emission emitted from combustion engine, the developed nations have been focused on R&D of hybrid electric vehicle. Further more, many automobile companies are researching on various techniques related to engine used in HEV to enhance fuel economy. One of key techniques is miller cycle that control a valve timing to reduce compression stroke for saving energy and increase expansion stroke for high power. In this study, it was investigated the in-cylinder flow characteristics of miller cycle with variable intake valve timing by using the ANSYS simulation code. For simulation, the key analytic parameter defined as intake valve closing timing and cam profile. As main results, it was shown that LIVC cause a lower pressure inside cylinder and had better control turbulence intensity.

• 한국수소및신에너지학회논문집
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• 제22권4호
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• pp.495-503
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• 2011

The sealed nickel-metal hydride (Ni-MH) secondary battery are primarily used as energy storage for the HEV. But, the research on Ni-MH battery has focused on anode materials. In the present study, we investigate to improve the electrochemical characteristics of Ni-MH batteries using the surface treatment of $Ni(OH)_2$ cathode by CoOOH. Surface treated $Ni(OH)_2$ cathode showed significant improvement in the activation behavior, rate capability, charge retention, and cycle life of the batteries were significantly improved. In addition, the surface treated electrode exhibited the higher overvoltage for oxygen evolution than the untreated electrode. This phenomenon indicates that the charge efficiency can be improved by suppressing the oxygen evolution on cathode.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 추계학술대회 논문집 학회본부
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• pp.527-530
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• 1997

최근 환경에 대한 각국의 관심이 높아지면서 자동차의 배기가스 및 소음에 관한 규제 차들이 날로 높아 가고 있는 실정이다. 이에 대한 해결책의 하나로 전기 자동차에 관한 관심이 고조되고 있으며, 특히 기계적 에너지와 전기적 에너지를 동시에 제어함으로써 외부의 별도 전원 공급이 필요 없이 구동이 가능한 병렬 복합형 전기자동차가 많은 연구의 대상이 되고 있다. 병렬 복합형 전기자동차의 전동기는 저속에서 구동 회전력을 보조하여 배기가스와 소음을 감소시키며, 고속에서는 내연 기관으로부터 에너지를 공급받아 배터리를 충전한다. 본 논문에서는 인공지능을 이용하여 다양한 주행 조건, 운행 패턴 등에 효과적으로 대응할 수 있으며 배기가스 및 소음을 감소시킬 수 있는 운행 제어 알고리즘을 제안하고 이를 주행시험을 통하여 그 타당성을 입증하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 제39회 하계학술대회
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• pp.756-757
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• 2008

Interior permanent magnet synchronous motor (IPMSM) which has high power density is usually applied to traction motor for hybrid electric vehicle. In order to analyze characteristics of IPMSM, d- and q-axis equivalent circuit analysis is generally used. However, the line current of IPMSM calculated by d- and q-axis equivalent circuit analysis differ from measured value. This error is mainly appeared under the flux weakening control. In order to reduce the error between calculated and measured line current, no-load linkage flux which is calculated with considering saturation of magnetic core and armature reaction is applied to characteristic analysis. The result of line current calculated by the method dealt with in this paper is verified by comparison with experimental results.

• 한국기계가공학회지
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• 제11권4호
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• pp.25-30
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• 2012

The transportation is almost dependent on a single fuel petroleum with transportation energy dilemma. Hybrid Electric Vehicle(HEV) technology holds more advantages on efficiency improvements for petroleum consumption at the transportation. And bearing is recognized as the important component of gearbox. Gearboxes for HEV transmission have been ensured the highest reliability over some years in withstanding high dynamic loads. At the same time, the demands of lightweight design and cost minimization are required by thought-out design, high-quality material, superior production quality and maintenance. In order to design a reliable and lightweight gearbox, it is necessary to analyze bearing rating life methods between standard and different bearing companies with calculation methods for modification factors. In this paper, the influence of life time of bearings will be pointed out. Bearing contact stress and load stress distribution of HEV gearbox are obtained and compared with Romaxdesigner and BearinX. And the unequal wear of the left bearing for the gearbox intermediate shaft is investigated between simulation and test.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제55권2호
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• pp.89-97
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• 2006

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. The paper is proposed maximum torque control of IPMSM drive using learning mechanism-fuzzy neural network(LM-FNN) controller and artificial neural network(ANN). The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_{d}$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using LM-FNN controller and ANN controller. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of IPMSM using LM-FNN and estimation of speed using ANN controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled LM-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper is proposed the analysis results to verify the effectiveness of the LM-FNN and ANN controller.

• 한국정밀공학회지
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• 제27권10호
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• pp.77-83
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• 2010

In this paper, the noise of HEV(hybrid electric vehicle)-relay module during the turn-on and turnoff switching is experimentally analyzed and an effective method is proposed to reduce the impact noise. First, enclosure methods of 100A relay part with urethane and silicon are tested to find out a better material to isolate the noise. This result shows that the urethane is a better for the noise isolation of relay, so the relays enclosed by urethane are installed in the relay module. Second, the noise of HEV-relay module is analyzed experimentally to identify the noise generation mechanism. From this result, it is found that the vibration transmitted to battery pack through bolt generates the structural borne noise with the frequency band of 200~2000 Hz, which is more serious when the switch is turned off. Finally, the direction of switching and the joint structure are modified in order to isolate the vibration transmitted to battery back. Both methods are very effective to reduce the switching noise.

• Journal of Electrical Engineering and Technology
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• 제9권3호
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• pp.1125-1131
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• 2014

Application of residential demand response (DR) programs are currently realized up to a limited extent due to customers' difficulty in manually responding to the time-differentiated prices. As a solution, this paper proposes an automatic home load management (HLM) framework to achieve the household minimum payment as well as meet the operational constraints to provide customer's comfort. The projected HLM method controls on/off statuses of responsive appliances and the charging/discharging periods of plug-in hybrid electric vehicle (PHEV) and battery storage at home. This paper also studies the impacts of different time-varying tariffs, i.e., time of use (TOU), real time pricing (RTP), and inclining block rate (IBR), on the home load management (HLM). The study is effectuated in a smart home with electrical appliances, a PHEV, and a storage system. The simulation results are presented to demonstrate the effectiveness of the proposed HLM program. Peak of household load demand along with the customer payment costs are reported as the consequence of applying different pricings models in HLM.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2006년도 춘계학술대회 논문집
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• pp.309-314
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• 2006

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. This paper proposes maximum torque control of IPMSM drive using adaptive learning fuzzy neural network and artificial neural network. This control method is applicable over the entire speed range which considered the limits of the inverter's current md voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using adaptive teaming fuzzy neural network and artificial neural network. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper proposes speed control of IPMSM using adaptive teaming fuzzy neural network and estimation of speed using artificial neural network. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled adaptive teaming fuzzy neural network and artificial neural network, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper proposes the analysis results to verify the effectiveness of the adaptive teaming fuzzy neural network and artificial neural network.