• Journal of Electrical Engineering and Technology
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• 제9권3호
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• pp.859-865
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• 2014

Optimization of an electric machine is mainly a nonlinear multi-modal problem. For the optimization of the multi-modal problem, many function calls are required with much consumption of time. To address this problem, this paper proposes a novel hybrid algorithm in which function calls are less than conventional methods. Specifically, the proposed method uses the kriging metamodel and the fill-blank technique to find an approximated solution in a whole problem region. To increase the convergence speed in local peaks, a parallel gradient assisted simplex method is proposed and combined with the kriging meta-model. The correctness and usefulness of the proposed hybrid algorithm is verified through a mathematical test function and applied into the practical optimization as the cogging torque minimization for an interior permanent magnet synchronous machine.

• 한국인터넷방송통신학회논문지
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• 제20권1호
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• pp.135-140
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• 2020

최근 사물인터넷, 지능형 시스템 등의 활성화로 실시간 임베디드 시스템의 전력 절감 기술이 중요해지고 있다. 본 논문은 멀티코어 이기종메모리 환경에서 실시간 시스템의 전력 소모량을 절감하는 P-GA (parallel genetic algorithm) 스케줄링 알고리즘을 제안한다. P-GA는 멀티코어를 위한 PF (proportional fairness) 알고리즘에 기반한 프로세서의 전압 및 주파수 동적 조절 기법에 차세대 비휘발성메모리 기술을 결합하여 시스템의 전력 소모를 더욱 줄인다. 특히, 유전 알고리즘을 사용하여 태스크별 수행 프로세서의 전압 및 주파수 모드와 메모리의 종류를 최적화하여 태스크 집합의 전력 소모량을 최소화한다. 시뮬레이션 실험을 통해 P-GA가 기존 방식 대비 최대 2.85배의 전력 소모량을 감소할 수 있음을 보인다.

• Advances in Automotive Engineering
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• 제1권1호
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• pp.105-121
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• 2018

The hybrid electric powertrain is a robust solution that allows for major improvements in both fuel economy and emission reduction. In the present study, a through-the-road hybrid vehicle model with an electric motor driving the rear axle and an Internal Combustion Engine (ICE) driving the front axle has been constructed. We then present a systematic method for the determination of a real time applicable optimal Energy Management Strategy (EMS) for a hybrid road vehicle. More precisely, we compare the performance of rule-based EMS strategies to an optimization-based strategy, namely ECMS (Equivalent Consumption Minimization Strategy). The comparison is conducted in parallel with a parameterization of the size of the internal combustion engine and the implementation of a Continuously Variable Transmission (CVT) that allows following the line of best fuel economy. For the FTP-75 driving cycle, the constrained engine On-off control algorithm is shown to offer a 28% improvement potential of fuel consumption compared to the conventional internal combustion engine while the ECMS strategy achieves an improved potential of nearly 33%.

• 유공압시스템학회논문집
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• 제5권4호
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• pp.1-9
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• 2008

In this paper, an energy regeneration algorithm is proposed to make the maximum use of the regenerative braking energy for a parallel hybrid electric vehicle(HEV) equipped with a continuous variable transmission(CVT). The regenerative algorithm is developed by considering the battery state of charge(SOC), vehicle velocity and motor capacity. The hydraulic module consists of a reducing valve and a power unit to supply the front wheel brake pressure according to the control algorithm. In order to evaluate the performance of the regenerative braking algorithm and the hydraulic module, a hardware-in-the-loop simulation (HILS) is performed. In the HILS system, the brake system consists of four wheel brakes and the hydraulic module. Dynamic characteristics of the HEV are simulated using an HEV simulator. In the HEV simulator, each element of the HEV powertrain such as internal combustion engine, motor, battery and CVT is modelled using MATLAB/$Simulink^{(R)}$. In the HILS, a driver operates the brake pedal with his or her foot while the vehicle speed is displayed on the monitor in real time. It is found from the HILS that the regenerative braking algorithm and the hydraulic module suggested in this paper provide a satisfactory braking performance in tracking the driving schedule and maintaining the battery state of charge.

• 한국측량학회지
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• 제37권6호
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• pp.445-452
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• 2019

본 연구에서는 대용량 위성영상의 무감독분류를 위해 k-means clustering 알고리즘의 병렬처리 코드를 개발하여 PC-cluster에서 구현하였다. 이를 위해 OpenMP (Open Multi-Processing)를 기반으로 CPU (Central Processing Unit)의 다중코어를 이용하는 intra-node 코드와 message passing interface를 기반으로 PC-cluster를 이용하는 inter-nodes 코드, 그리고 이 둘을 병용하는 hybrid 코드를 구현하였다. 본 연구에 사용한 PC-cluster는 한 대의 마스터 노드와 여덟 대의 슬래이브 노드로 구성되어 있고 각 노드에는 여덟 개의 다중코어가 장착되어 있다. PC-cluster에는 Microsoft Windows와 Canonical Ubuntu의 두 가지 운영체제를 설치하여 병렬처리 성능을 비교하였다. 실험에 사용한 자료는 두 가지 다중분광 위성영상으로서 중용량인 LANDSAT 8 OLI (Operational Land Imager) 영상과 대용량인 Sentinel 2A 영상이다. 병렬처리의 성능을 평가하기 위하여 speedup과 efficiency를 측정한 결과 전반적으로 speedup은 N/2 이상, efficiency는 0.5 이상으로 나타났다. Microsoft Windows와 Canonical Ubuntu를 비교한 결과 Ubuntu가 2-3배의 빠른 결과를 나타내었다. 순차처리와 병렬처리 결과가 일치하는지 확인하기 위해 각 클래스의 밴드별 중심값과 분류된 화소의 수를 비교하고 결과 영상간 화소대 화소 비교도 수행하였다. Intra-node 코드를 구현할 때에는 OpenMP에 의한 false sharing이 발생하지 않도록 주의해야 하고, PC-cluster에서 대용량 위성영상을 처리하기 위해서는 파일 I/O에 의한 성능저하를 줄일 수 있도록 코드 및 하드웨어를 설계해야 함을 알 수 있었다. 또한 PC-cluster에 설치된 운영체제에 따라서도 성능 차이가 발생함을 알 수 있었다.

• International Journal of Contents
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• 제1권1호
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• pp.50-58
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• 2005

Generally, multidimensional data such as image and spatial data require large amount of storage space. There is a limit to store and manage those large amounts of data in single workstation. If we manage the data on parallel computing environment which is being actively researched these days, we can get highly improved performance. In this paper, we propose a parallel multidimensional index structure that exploits the parallelism of the parallel computing environment. The proposed index structure is nP(processor)-nxmD(disk) architecture which is the hybrid type of nP-nD and 1P-nD. Its node structure in-creases fan-out and reduces the height of an index. Also, a range search algorithm that maximizes I/O parallelism is devised, and it is applied to k-nearest neighbor queries. Through various experiments, it is shown that the proposed method outperforms other parallel index structures.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2006년도 춘계공동학술대회 논문집
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• pp.1133-1138
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• 2006

This paper considers a hybrid flow shop scheduling problem for the objective of minimizing the number of tardy jobs. The hybrid flow shop consists of two stages in series, each of which has multiple identical parallel machines, and the problem is to determine the allocation and sequence of jobs at each stage. A branch and bound algorithm that gives the optimal solutions is suggested that incorporates the methods to obtain the lower and upper bounds. Dominance properties are also derived to reduce the search space. To show the performance of the algorithm, computational experiments are done on randomly generated problems, and the results are reported.

• Journal of Electrical Engineering and Technology
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• 제8권4호
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• pp.930-937
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• 2013

In this paper, a motor control algorithm for performing a mode change without an integrated starter generator (ISG) is suggested for the automatic transmission-based hybrid electric vehicle (HEV). Dynamic models of the HEV powertrains such as engine, motor, and mode clutch are derived for the transient state during the mode change, and the HEV performance simulator is developed. Using the HEV performance bench tester, the characteristics of the mode clutch torque are measured and the motor torque required for the mode clutch synchronization is determined. Based on the dynamic models and the mode clutch torque, a motor torque control algorithm is presented for mode changes, and motor control without the ISG is investigated and compared with the existing ISG control.

• Journal of information and communication convergence engineering
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• 제8권1호
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• pp.13-18
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• 2010

The composite stock cutting problem is defined as allocating rectangular and irregular patterns onto a large composite stock sheet of finite dimensions in such a way that the resulting scrap will be minimized. In this paper, we introduce a novel approach to hybrid optimization algorithm called MGA in MPI (Message Passing Interface) environments. The proposed MGA combines the benefit of rapid convergence property of Mean Field Annealing and the effective genetic operations. This paper also proposes the efficient data structures for pattern related information.

• Current Optics and Photonics
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• 제2권6호
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• pp.612-622
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• 2018

In wave-front-sensor-less adaptive optics (WFS-less AO) systems, the Jacopo Antonello (JA) method belongs to the model-based class and requires few iterations to achieve acceptable distortion correction. However, this method needs a lot of measurements, especially when it deals with moderate or severe aberration, which is undesired in free-space optical communication (FSOC). On the contrary, the stochastic parallel gradient descent (SPGD) algorithm only requires three time measurements in each iteration, and is widely applied in WFS-less AO systems, even though plenty of iterations are necessary. For better and faster compensation, we propose a WFS-less hybrid approach, borrowing from the JA method to compensate for low-order wave front and from the SPGD algorithm to compensate for residual low-order wave front and high-order wave front. The correction results for this proposed method are provided by simulations to show its superior performance, through comparison of both the Strehl ratio and the convergence speed of the WFS-less hybrid approach to those of the JA method and SPGD algorithm.