• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.25 no.11
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• pp.930-937
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• 2012

Newly developed Series hybrid low-floor articulated vehicle which can meet both road and railway running conditions. It has the rated driving speed of 80 km/h and three driving modes with hybrid(engine+battery) driving mode, engine driving mode, battery driving mode. The battery driving mode requires the several 10 km running without additional charging operation. The vehicle has been equipped with LPB (lithium polymer battery) pack for the series hybrid propulsion system. LPB pack consists of 168 cells (3.7 V in a cell, 80 Ah) in series, DC Circuit breaker, mechanical rack, BMS (battery management system). This paper has shown the design process of LPB pack and application to the vehicle. Driving results in the road was successful to be satisfied with the requirement of the series hybrid vehicle.

• Journal of applied mathematics & informatics
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• v.14 no.1_2
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• pp.267-275
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• 2004

While the convergence of the classical Fourier series has been well known, the rate of its convergence is not well acknowledged. The results regarding the rate of convergence of the Fourier series and wavelet expansions can be found in the book of Walter[5]. In this paper, we give the rate of convergence of hybrid sampling series associated with orthogonal wavelets.

• 한국신재생에너지학회:학술대회논문집
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• 2010.11a
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• pp.95-95
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• 2010

In recent, there are tremendous requirements to improve the fuel economy of vehicle. For satisfaction of requirements, Hybrid Electric Vehicle or other technologies are suggested and implemented. However, it should be noted that almost 35% energy loss is occurred in the shape of exhaust gas as ever. For increase the efficiency of vehicle, it is certain that the exhaust gas energy should be recover, and generate energy. In previous studies, the technologies such as turbo-compound, thermoelectric and rankine cycle are suggested to recover the exhaust heat energy in vehicle. But, they focus on the conventional vehicle or parallel Hybrid Electric Vehicle. Series Hybrid Electric Vehicle has advantage that the engine and drive shaft are de-coupled. It means that the engine can be operated in high efficiency area regardless with vehicle states. Therefore, if rankine cycle is applied to series hybrid electric vehicle, operating condition of that becomes almost steady. So, in this study, theoretical analysis on the efficiency of rankine cycle applied to series hybrid electric city bus is carried and the energy recovered from exhaust gas during vehicle drive cycle is calculated.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.1
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• pp.92-98
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• 2013

There are lots of studies about hybrid electric vehicles (HEVs) because of the global warming and energy problems. Series and parallel HEVs are the common types of many developing hybrid vehicle types. Series HEV uses engine only as the generator for the battery but parallel HEV utilizes engine for driving and generating of the vehicle. In this paper, backward simulations based on dynamic programming were conducted for the fuel economy analysis of two different types of hybrid transit buses depending on driving cycles. It is shown that there is a relation between the type of HEV and the characteristics of driving cycles. Regarding the aggressiveness, the series hybrid bus is more efficient than the parallel system on highly aggressive driving cycle. On the other hand, the parallel hybrid bus is more efficient than the series system on low aggressive driving cycle. Based on this results of the paper, it is expected to choose more efficient type of the hybrid buses according to the driving cycle.

• Journal of applied mathematics & informatics
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• v.17 no.1_2_3
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• pp.719-736
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• 2005

An understanding of Fourier series and their generalization is important for physics and engineering students, as much for mathematical and physical insight as for applications. Students are usually confused by the so-called Gibbs' phenomenon, an overshoot between a discontinuous function and its approximation by a Fourier series as the number of terms in the series becomes indefinitely large. In this paper we give short story of Gibbs phenomenon in chronological order.

• Journal of applied mathematics & informatics
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• v.12 no.1_2
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• pp.199-209
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• 2003

When a sampling theorem holds in wavelet subspaces, sampling expansions can be a good approximation to projection expansions. Even when the sampling theorem does not hold, the scaling function series with the usual coefficients replaced by sampled function values may also be a good approximation to the projection. We refer to such series as hybrid sampling series. For this series, we shall investigate the local convergence and analyze Gibbs phenomenon.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.2
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• pp.159-166
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• 2014

The study is conducted on the subject of optimization of components sizing for series hybrid electric propulsion systems. The components sizing of series type hybrid system is very important because each component of series type is larger than the corresponding component of the parallel type or series-parallel type. If the components sizing is greater or less than what is required to this system, the performance of the system is getting worse. The methodology for the sizing of a driving motor is introduced based on the foundation of determined system configuration and performance target. And the sizing of an engine/generator and a battery is achieved based on simulation results using Dynamic Programming. It is possible to find the optimal sizing of these components by comparing fuel efficiency of hybrid electric propulsion system for 8 driving cycles.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.4
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• pp.366-373
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• 2012

In this paper, serious changes in the electromagnetic environment with increasing power and energy capabilities for electric driving and military mission are discussed. Design and control strategies on the Electro-Magnetic Compatibility(EMC) for the series hybrid electric vehicle are proposed to minimize the effects of electromagnetic interferences.

• The KIPS Transactions:PartD
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• v.15D no.1
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• pp.31-40
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• 2008

We generally use lower-dimensional transformations to convert high-dimensional sequences into low-dimensional points in similar sequence matching. These traditional transformations, however, show different characteristics in indexing performance by the type of time-series data. It means that the selection of lower-dimensional transformations makes a significant influence on the indexing performance in similar sequence matching. To solve this problem, in this paper we propose a hybrid approach that integrates multiple transformations and uses them in a single multidimensional index. We first propose a new notion of hybrid lower-dimensional transformation that exploits different lower-dimensional transformations for a sequence. We next define the hybrid distance to compute the distance between the transformed sequences. We then formally prove that the hybrid approach performs the similar sequence matching correctly. We also present the index building and the similar sequence matching algorithms that use the hybrid approach. Experimental results for various time-series data sets show that our hybrid approach outperforms the single transformation-based approach. These results indicate that the hybrid approach can be widely used for various time-series data with different characteristics.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.1-17
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• 2013

In this article, several types of hybrid forecasting models are suggested. In particular, hybrid models using the generalized additive model (GAM) are newly suggested as an alternative to those using neural networks (NN). The prediction performances of various hybrid and non-hybrid models are evaluated using simulated time series data. Five different types of seasonal time series data related to an additive or multiplicative trend are generated over different levels of noise, and applied to the forecasting evaluation. For the simulated data with only seasonality, the autoregressive (AR) model and the hybrid AR-AR model performed equivalently very well. On the other hand, if the time series data employed a trend, the SARIMA model and some hybrid SARIMA models equivalently outperformed the others. In the comparison of GAMs and NNs, regarding the seasonal additive trend data, the SARIMA-GAM evenly performed well across the full range of noise variation, whereas the SARIMA-NN showed good performance only when the noise level was trivial.