• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.10
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• pp.5899-5905
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• 2014

Faults in electric power system can be a critical problem for vehicles. The system durability is determined mainly by the durability of their components and operating conditions. Monitoring the conditions of the electric power system may be necessary because it is very difficult to predict precisely when it will fail. Therefore, the aim of this study was to develop a diagnosis system for an electric power system of a vehicle. The alternator voltage, excitation voltage, lamp voltage, battery voltage, and engine rpm from a crank angle sensor are monitored continuously and the system fault can be then detected in real time. NI USB- 9201 DAQ and LabVIEW SW have been used to measure the voltages and analyze the data. Compared to conventional measurements for only each component, an integrated and portable measurement method was developed. In addition to the monitoring the electric power system in real time, the saved data from the measurement also provides valuable information to improve the durability of the components.

• Journal of the Microelectronics and Packaging Society
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• v.31 no.1
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• pp.16-22
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• 2024

Along with the high interest in electric vehicles and new renewable energy, there is a growing demand to apply lithium-ion batteries in the construction equipment industry. The capacity of heavy construction equipment that performs various tasks at construction sites is rapidly decreasing. Therefore, it is essential to accurately predict the state of batteries such as SOC (State of Charge) and SOH (State of Health). In this paper, the errors between actual electrochemical measurement data and estimated data were compared using the Dual Extended Kalman Filter (DEKF) algorithm that can estimate SOC and SOH at the same time. The prediction of battery charge state was analyzed by measuring OCV at SOC 5% intervals under 0.2C-rate conditions after the battery cell was fully charged, and the degradation state of the battery was predicted after 50 cycles of aging tests under various C-rate (0.2, 0.3, 0.5, 1.0, 1.5C rate) conditions. It was confirmed that the SOC and SOH estimation errors using DEKF tended to increase as the C-rate increased. It was confirmed that the SOC estimation using DEKF showed less than 6% at 0.2, 0.5, and 1C-rate. In addition, it was confirmed that the SOH estimation results showed good performance within the maximum error of 1.0% and 1.3% at 0.2 and 0.3C-rate, respectively. Also, it was confirmed that the estimation error also increased from 1.5% to 2% as the C-rate increased from 0.5 to 1.5C-rate. However, this result shows that all SOH estimation results using DEKF were excellent within about 2%.

• Journal of Energy Engineering
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• v.20 no.1
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• pp.1-7
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• 2011

The performance and life-cycle costs of electric vehicle(EV) and hybrid electric vehicle(HEV) depend inherently on battery packs. Temperature uniformity in a pack is an important factor for obtaining optimum performance for an EV or HEV battery pack, because uneven temperature distribution in a pack leads to electrically unbalanced battery cells and reduced pack performance. In this work, a three-dimensional modeling was carried out to investigate the effects of operating conditions on the thermal behavior of a lithium-ion battery pack for an EV or HEV application. Thermal conductivities of various compartments of the battery were estimated based on the equivalent network of parallel/series thermal resistances of battery components. Heat generation rate in a cell was calculated using the modeling results of the potential and current density distributions of a battery cell.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.6
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• pp.147-154
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• 2013

This study reports on the development and investigation of a BMS module using a new algorithm on the driving performance and battery life of electric vehicles. Here, the initial SOC was calculated using an open circuit voltage (OCV) method and a current integral method was later applied to the BMS module. We verified the performance of the BMS module by comparing both the results of the in-vehicle test and the BMS simulator test. Our verification test showed good agreement between the results of experiments and simulation with a small error of ${\pm}0.8%$. Here, we confirmed that the present, newly-developed BMS module not only can predict the battery life but can also monitor SOC, pack voltage, and current temperature.

• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.5
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• pp.65-72
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• 2006

In new generation vehicle technologies, a fuel cell vehicle becomes more important, by virtue of their emission merits. In addition, a fuel cell is considered as a major source to generate the electricity for vehicles in near future. This paper focuses on modeling of not only an electric vehicle and but also a fuel cell vehicle to estimate performances. And an EV cart is manufactured to verify the modeling. Speed, voltage, and current of the vehicle and modeling are compared to estimate them at acceleration test and driving mode test. The estimations are also compared with the data of the Ballard Nexa fuel cell stack. In order to investigate a fuel cell based vehicle, motor and fuel cell models are integrated in a electric vehicle model. The characteristics of individual components are also integrated. Calculated fuel cell equations show good agreements with test results. In the fuel cell vehicle simulation, maximum speed and hydrogen fuel consumption are estimated. Even though there is no experimental data from vehicle tests, the vehicle simulation showed physically-acceptable vehicle characteristics.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.1
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• pp.10-23
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• 2009

In this paper we propose a novel mobile terminal software architecture supporting energy efficient handover operation in heterogeneous networks. Since the legacy proposals for L3 handover are mostly dependent on IETF Mobile IP which has some problems in movement detection mechanism and no considerations on nested heterogeneous network environment as a result they make serious overload on networks and terminals by performing unnecessary handover in such network environments. The proposed architecture has terminal-oriented network selection and switching architecture where a mobile terminal periodically monitors network status and selects the optimum network, and reduces energy consumption by making L3 handover of Mobile IP to the finally selected network. The network selection method first picks up some candidate networks by considering a terminal speed and power consumption estimation, and determines the final target handover network among the candidates after evaluating multiple factors including QoS required by a terminal, network status, user preference and terminal battery status. Finally we verify the functionality and performance of the energy efficient vertical handover architecture by means of adopting it into a real mobile terminal.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.8
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• pp.185-194
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• 2014

In this paper, we proposed the clothing management system using the smart hanger. Proposed system consists of smart hanger, base module, and server, and the smart hanger consists of MCU, LED, RFID reader, RF chip, ring sensor, and battery. The smart hanger reads the RFID tag attached to the clothes and wirelessly transmitted to the server. The server associated base module communicates with the smart hanger and transmits information to the server. The server manages clothing through the DB, and can display various information through the web page and the smart phone. In order to verify the usefulness of the proposed system, we did experiment with the management system for clothing store and laundry where using a lot of hangers. Performance tests of the smart hanger are applied to check the current consumption and can be predicted the battery life with the proposed low power algorithm. The clothing store management system can be increased sales and convenience of the consumer. The laundry management system can be increased the efficiency of laundry category and convenience of the consumer.

• The Journal of the Korea Contents Association
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• v.10 no.3
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• pp.53-63
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• 2010

Recently, various monitoring systems are implemented actively by using wireless sensor networks(WSN). When implementing WSN-based monitoring system, there are three important issues to consider. At First, we need to consider a sensor node failure detection method to support the ongoing monitoring. Secondly, because sensor nodes use limited battery power, we need an efficient data filtering method to reduce energy consumption. At Last, a reducing processing overhead method is necessary. The existing Kalman filtering scheme has good performance on data filtering, but it causes too much processing overhead to estimate sensed data. To solve these problems, we, in this paper, propose a new data filtering scheme based on data statical analysis. First, the proposed scheme periodically aggregates node survival massages to support a node failure detection. Secondly, to reduce energy consumption, it sends the sample data with a node survival massage and do data filtering based on those messages. Finally, it analyzes the sample data to estimate filtering range in a server. As a result, each sensor node can use only simple compare operation for filtering data. In addition, we show from our performance analysis that the proposed scheme outperforms the Kalman filtering scheme in terms of the number of sending messages.

• Journal of KIISE:Databases
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• v.36 no.4
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• pp.280-291
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• 2009

Skyline Query processing is important to wireless sensor applications in order to process multi-dimensional data efficiently. Most skyline researches about sensor network focus on minimizing the energy consumption due to the battery powered constraints. In order to reduce energy consumption, Filtering Method is proposed. Most existing researches have assumed a snapshot skyline query processing and do not consider continuous queries and use data generated in ancestor node. In this paper, we propose an energy efficient method called Bottom up filtering tuple selection for continuous skyline query processing. Past skyline data generated in child nodes are stored in each sensor node and is used when choosing filtering tuple. We also extend the algorithms, called Support filtering tuple(SFT) that is used when we choose the additional filtering tuple. There is a temporal correlation between previous sensing data and recent sensing data. Thus, Based on past data, we estimate current data. By considering this point, we reduce the unnecessary communication cost. The experimental results show that our method outperforms the existing methods in terms of both data reduction rate(DRR) and total communication cost.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.8B
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• pp.637-646
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• 2012

Recently, Wireless Sensor Networks (WSNs) are used in many applications. When sensor nodes are deployed on special areas, where humans have any difficulties to get in, the nodes form network topology themselves. By using the sensor nodes, users are able to obtain environmental information. Due to the lack of the battery capability, sensor nodes should be efficiently managed with energy consumption in WSNs. In specific applications (e.g. in intrusion detections), intruders tend to occur unexpectedly. For the energy efficiency in the applications, an appropriate algorithm is strongly required. In this paper, we propose tree-based routing algorithm for the specific applications, which based on the intrusion detection. In addition, In order to decrease traffic density, the proposed algorithm provides enhanced method considering link cost and load balance, and it establishes efficient links amongst the sensor nodes. Simultaneously, by using the proposed scheme, parent and child nodes are (re-)defined. Furthermore, efficient routing table management facilitates to improve energy efficiency especially in the limited power source. In order to apply a realistic military environment, in this paper, we design three scenarios according to an intruder's moving direction; (1) the intruder is passing along a path where sensor nodes have been already deployed. (2) the intruders are crossing the path. (3) the intruders, who are moving as (1)'s scenario, are certainly deviating from the middle of the path. In conclusion, through the simulation results, we obtain the performance results in terms of latency and energy consumption, and analyze them. Finally, we validate our algorithm is highly able to adapt on such the application environments.