• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.12 no.4
• /
• pp.456-465
• /
• 2019

PHEV(Plug in Hybrid Electric Vehicle) and BEV(Battery Electric Vehicle) equip high voltage batteries to drive motor and vehicle electric system. Those vehicle require OBC(On-Board Charger) for charging batteries and LDC(Low DC/DC Converter) for converting from high voltage to low voltage. Since the charger and the converter actually separate each other in electrical vehicles, there is a margin to reduce the vehicle weight and area of installation by integration two systems. This paper studies a 1.5kW LDC converter that can be integrated into an OBC using an isolated current-fed converter by simplifying the design of LDC transformers. The proposed LDC can control the final output voltage of the LDC by using a fixed arbitrary output voltage of the bidirectional buck-boost converter, so that Compared to the existing OBC-LDC integrated system, it has the advantage of simplifying the transformer design considering the battery voltage range, converter duty ratio and OBC output turn ratio. Prototype of the proposed LDC was made to confirm normal operation at 200V ~ 400V input voltage and maximum efficiency of 91.885% was achieved at rated load condition. In addition, the OBC-LDC integrated system achieved a volume of about 6.51L and reduced the space by 15.6% compared to the existing independent system.

• Journal of Aerospace System Engineering
• /
• v.16 no.3
• /
• pp.42-51
• /
• 2022

An eVTOL aircraft, which is required to operate with low pollution/low noise in urban environments, mostly use battery-powered electric propulsion systems as power sources, not traditional propulsion systems such as reciprocating or turbine engines. Accordingly, certification preparation for the electric propulsion system and securing the safety of the electric propulsion system, are important issues. In the U.S., special technical standards equivalent to FAR Part 33 were issued to certify electric engines, and in Europe, various special conditions were established to certify electric propulsion systems. Thus, in Korea, the technical standards for the electric propulsion system for eVTOL aircraft must also be prepared in line with the U.S. and Europe. In this paper, SC E-19, the technical standard of the electric/hybrid propulsion system (EHPS) in special conditions, was analyzed. Additionally, securing the safety of the electric propulsion system of the aircraft are proposed, through the collaboration of SC E-19 technical standards with the existing aircraft safety evaluation procedure ARP 4761. Finally, through a case study of the Ehang 184 electric propulsion system, it has been confirmed that the proposed safety assurance method is applicable at the aircraft level.

• Journal of Intelligence and Information Systems
• /
• v.24 no.2
• /
• pp.85-109
• /
• 2018

Recommender system recommends the items expected to be purchased by a customer in the future according to his or her previous purchase behaviors. It has been served as a tool for realizing one-to-one personalization for an e-commerce service company. Traditional recommender systems, especially the recommender systems based on collaborative filtering (CF), which is the most popular recommendation algorithm in both academy and industry, are designed to generate the items list for recommendation by using 'overall rating' - a single criterion. However, it has critical limitations in understanding the customers' preferences in detail. Recently, to mitigate these limitations, some leading e-commerce companies have begun to get feedback from their customers in a form of 'multicritera ratings'. Multicriteria ratings enable the companies to understand their customers' preferences from the multidimensional viewpoints. Moreover, it is easy to handle and analyze the multidimensional ratings because they are quantitative. But, the recommendation using multicritera ratings also has limitation that it may omit detail information on a user's preference because it only considers three-to-five predetermined criteria in most cases. Under this background, this study proposes a novel hybrid recommendation system, which selectively uses the results from 'traditional CF' and 'CF using multicriteria ratings'. Our proposed system is based on the premise that some people have holistic preference scheme, whereas others have composite preference scheme. Thus, our system is designed to use traditional CF using overall rating for the users with holistic preference, and to use CF using multicriteria ratings for the users with composite preference. To validate the usefulness of the proposed system, we applied it to a real-world dataset regarding the recommendation for POI (point-of-interests). Providing personalized POI recommendation is getting more attentions as the popularity of the location-based services such as Yelp and Foursquare increases. The dataset was collected from university students via a Web-based online survey system. Using the survey system, we collected the overall ratings as well as the ratings for each criterion for 48 POIs that are located near K university in Seoul, South Korea. The criteria include 'food or taste', 'price' and 'service or mood'. As a result, we obtain 2,878 valid ratings from 112 users. Among 48 items, 38 items (80%) are used as training dataset, and the remaining 10 items (20%) are used as validation dataset. To examine the effectiveness of the proposed system (i.e. hybrid selective model), we compared its performance to the performances of two comparison models - the traditional CF and the CF with multicriteria ratings. The performances of recommender systems were evaluated by using two metrics - average MAE(mean absolute error) and precision-in-top-N. Precision-in-top-N represents the percentage of truly high overall ratings among those that the model predicted would be the N most relevant items for each user. The experimental system was developed using Microsoft Visual Basic for Applications (VBA). The experimental results showed that our proposed system (avg. MAE = 0.584) outperformed traditional CF (avg. MAE = 0.591) as well as multicriteria CF (avg. AVE = 0.608). We also found that multicriteria CF showed worse performance compared to traditional CF in our data set, which is contradictory to the results in the most previous studies. This result supports the premise of our study that people have two different types of preference schemes - holistic and composite. Besides MAE, the proposed system outperformed all the comparison models in precision-in-top-3, precision-in-top-5, and precision-in-top-7. The results from the paired samples t-test presented that our proposed system outperformed traditional CF with 10% statistical significance level, and multicriteria CF with 1% statistical significance level from the perspective of average MAE. The proposed system sheds light on how to understand and utilize user's preference schemes in recommender systems domain.

• International Journal of Control, Automation, and Systems
• /
• v.1 no.3
• /
• pp.321-331
• /
• 2003

Experimental software datasets describing software projects in terms of their complexity and development time have been the subject of intensive modeling. A number of various modeling methodologies and modeling designs have been proposed including such approaches as neural networks, fuzzy, and fuzzy neural network models. In this study, we introduce the concept of the Rule-based fuzzy polynomial neural networks (RFPNN) as a hybrid modeling architecture and discuss its comprehensive design methodology. The development of the RFPNN dwells on the technologies of Computational Intelligence (CI), namely fuzzy sets, neural networks, and genetic algorithms. The architecture of the RFPNN results from a synergistic usage of RFNN and PNN. RFNN contribute to the formation of the premise part of the rule-based structure of the RFPNN. The consequence part of the RFPNN is designed using PNN. We discuss two kinds of RFPNN architectures and propose a comprehensive learning algorithm. In particular, it is shown that this network exhibits a dynamic structure. The experimental results include well-known software data such as the NASA dataset concerning software cost estimation and the one describing software modules of the Medical Imaging System (MIS).

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.7 no.1
• /
• pp.99-118
• /
• 2013

Electrocardiograms (ECGs) are widely used by clinicians to identify the functional status of the heart. Thus, there is considerable interest in automated systems for real-time monitoring of arrhythmia. However, intra- and inter-patient variability as well as the computational limits of real-time monitoring poses significant challenges for practical implementations. The former requires that the classification model be adjusted continuously, and the latter requires a reduction in the number and types of ECG features, and thus, the computational burden, necessary to classify different arrhythmias. We propose the use of adaptive learning to automatically train the classifier on up-to-date ECG data, and employ adaptive feature selection to define unique feature subsets pertinent to different types of arrhythmia. Experimental results show that this hybrid technique outperforms conventional approaches and is therefore a promising new intelligent diagnostic tool.

• Journal of Institute of Control, Robotics and Systems
• /
• v.20 no.2
• /
• pp.138-142
• /
• 2014

This research presents an A* based algorithm which can be applied to Unmanned Ground Vehicle self-navigation in order to make the driving path smoother. Based on the grid map, A* algorithm generated the path by using straight lines. However, in this situation, the knee points, which are the connection points when vehicle changed orientation, are created. These points make Unmanned Ground Vehicle continuous navigation unsuitable. Therefore, in this paper, B-spline curve function is applied to transform the path transfer into curve type. And because the location of the control point has influenced the B-spline curve, the optimal control selection algorithm is proposed. Also, the optimal path tracking speed can be calculated through the curvature radius of the B-spline curve. Finally, based on this algorithm, a path created program is applied to the path results of the A* algorithm and this B-spline curve algorithm. After that, the final path results are compared through the simulation.

• ETRI Journal
• /
• v.42 no.1
• /
• pp.17-25
• /
• 2020

Multiple-input multiple-output systems can achieve a full sum rate (SR) via full duplex (FD). However, its performance is degraded by self-interference (SI) that occurs between the transmitter and receiver at the same node and thus is constrained by error floors. Conversely, half duplex (HD) can avoid the SI albeit at lower spectral efficiency, and the slope of its error curve is determined by the diversity order. In this study, a link selection scheme based on switching between FD and HD is examined as a simple method to improve the bit error rate (BER) performance of FD systems. In the proposed link selection algorithm, either FD or HD is selected based on the received minimum distance and signal-to-interference plus noise ratio. Simulation results indicate that the proposed hybrid FD/HD switching system offers significant BER performance improvement when compared with that of the conventional FD and FD based on only the received minimum distance under the same fixed SR. Under relatively sufficient SI cancellation, it is demonstrated to outperform the HD with a diversity advantage in low and medium signal-to-noise ratio region.

• Journal of Institute of Control, Robotics and Systems
• /
• v.21 no.2
• /
• pp.137-144
• /
• 2015

In hybrid or electric vehicles, the hydraulic brake system must be controlled cooperatively with the traction motor for regenerative braking. Recently, a motor driven brake system with a PMSM (Permanent Magnet Synchronous Motor) has replaced conventional vacuum boosters to increase regenerative power. Unlike industry motor controls, additional source codes such as functional safety are essential in automotive applications to meet ISO26262 standards. Therefore, the control logic execution time increases, which also causes an extension of the motor current control period. The increased current control period makes precise motor current control challenging inhigh speed ranges where the motor is driven by high frequency. In this paper, a PWM update strategy and a time delay compensation method are suggested to improve current control and system performance. The proposed methods are experimentally verified.

• Korean Chemical Engineering Research
• /
• v.49 no.5
• /
• pp.505-509
• /
• 2011

Visible light-activated photocatalysts (based on doped titania) are the subject of intensive current research due to the promise they offer in relation to solar powered systems for photocatalysis, hybrid systems for $CO_2$ conversion and hydrogen production from water. Current synthetic methodologies suffer from one or more serious shortcomings, which seriously hinder practical application. These include high cost, irreproducibility, difficulty in controlling the dopant level and unsuitability for scale up. In this review new reproducible and controllable methods (developed by Lambert group, Cambridge University) allowing the synthesis of practical quantities of efficient, visible light active anion (e.g. N, C and B) doped $TiO_2$ photocatalysts are summarized.

• Journal of Electrical Engineering and Technology
• /
• v.12 no.2
• /
• pp.726-737
• /
• 2017

The use of energy storage systems (ESSs) has become a feasible solution to solve the wind power intermittency issue. However, the use of ESSs increases the system cost significantly. In this paper, an optimal power flow control scheme to minimize the ESS capacity is proposed by using the zero-phase delay low-pass filter which can eliminate the phase delay between the dispatch power and the wind power. In addition, the filter time constant is optimized at the beginning of each dispatching interval to ensure the fluctuation mitigation requirement imposed by the grid code with a minimal ESS capacity. And also, a short-term power dispatch control algorithm is developed suitable for the proposed power dispatch based on the zero-phase delay low-pass filter with the predetermined ESS capacity. In order to verify the effectiveness of the proposed power management approach, case studies are carried out by using a 3-MW wind turbine with real wind speed data measured on Jeju Island.