• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.24 no.4
• /
• pp.536-545
• /
• 2020

When general statistical regression methods are applied to predict the battery remaining time of a mobile smart device, they yielded the poor accuracy of estimating battery remaining time as the deviations of battery usage time per battery level became larger. In order to improve the estimation accuracy of general statistical regression methods, a preprocessing task is required to refine the measured raw data with large deviations of battery usage time per battery level. In this paper, we propose a data preprocessing framework that preprocesses raw measured battery consumption data and converts them into refined battery consumption data. The numerical results obtained by experimenting the proposed data preprocessing framework confirmed that it yielded good performance in terms of accuracy of estimating battery remaining time under general statistical regression methods for given refined battery consumption data.

• International Journal of Computer Science & Network Security
• /
• v.21 no.11
• /
• pp.338-344
• /
• 2021

The recently continuous enhancement and development in the biomedical side for the betterment of human life. The Wireless Body Area Networks is a significant tool for the current researcher to design and transfer data with greater data rates among the sensors and sensor nodes for biomedical applications. The core area for research in WBANs is power efficiency, battery-driven devices for health and medical, the Charging limitation is a major and serious problem for the WBANs.this research work is proposed to find out the optimal solution for battery-friendly technology. In this research we have addressed the solution to increasing the battery lifetime with variable data transmission rates from medical equipment as Wireless Endoscopy Capsules, this device will analyze a patient's inner body gastrointestinal tract by capturing images and visualization at the workstation. The second major issue is that the Wireless Endoscopy Capsule based systems are currently not used for clinical applications due to their low data rate as well as low resolution and limited battery lifetime, in case of these devices are more enhanced in these cases it will be the best solution for the medical applications. The main objective of this research is to power optimization by reducing the power consumption of the battery in the Wireless Endoscopy Capsule to make it battery-friendly. To overcome the problem we have proposed the algorithm for "Battery Friendly Algorithm" and we have compared the different frame rates of buffer sizes for Transmissions. The proposed Battery Friendly Algorithm is to send the images on average frame rate instead of transmitting the images on maximum or minimum frame rates. The proposed algorithm extends the battery lifetime in comparison with the previous baseline proposed algorithm as well as increased the battery lifetime of the capsule.

• Journal of IKEEE
• /
• v.27 no.1
• /
• pp.85-92
• /
• 2023

Recently, as the era of the 4th Industrial Revolution approaches, IoT devices that emphasize portability are increasing. At the same time, battery usage is also increasing rapidly. With the rapid increase in battery usage, issues related to battery safety have become inevitable problems and many studies have been conducted. This paper deals with explosion issues caused by swelling among various battery issues, and includes research and development of a system that detects battery swelling by identifying resistance changes. The core technology of this study is to develop a system that frequently detects changes in the resistance of wires drawn on the battery through changes in volume that occur when the battery swelling, and uses the resistance changes to prevent battery explosion. In addition, through pattern analysis, it was analyzed how the wire should be constructed to cause a lot of resistance changes.

• Restorative Dentistry and Endodontics
• /
• v.47 no.4
• /
• pp.45.1-45.10
• /
• 2022

Objectives: This study evaluated the relationship between the battery charge level and irradiance of light-emitting diode (LED) light-curing units (LCUs) and how these variables influence the Vickers hardness number (VHN) of a bulk-fill resin. Materials and Methods: Four LCUs were evaluated: Radii Plus (SDI), Radii-cal (SDI), Elipar Deep Cure (Filtek Bulk Fill, 3M Oral Care), and Poly Wireless (Kavo Kerr). Irradiance was measured using a radiometer every ten 20-second activations until the battery was discharged. Disks (4 mm thick) of a bulk-fill resin (Filtek Bulk Fill, 3M Oral Care) were prepared, and the VHN was determined on the top and bottom surfaces when light-cured with the LCUs with battery levels at 100%, 50% and 10%. Data were analyzed by 2-way analysis of variance, the Tukey's test, and Pearson correlations (α = 5%). Results: Elipar Deep Cure and Poly Wireless showed significant differences between the irradiance when the battery was fully charged versus discharged (10% battery level). Significant differences in irradiance were detected among all LCUs, within each battery condition tested. Hardness ratios below 80% were obtained for Radii-cal (10% battery level) and for Poly Wireless (50% and 10% battery levels). The battery level showed moderate and strong, but non-significant, positive correlations with the VHN and irradiance. Conclusions: Although the irradiance was different among LCUs, it decreased in half of the devices along with a reduction in battery level. In addition, the composite resin effectiveness of curing, measured by the hardness ratio, was reduced when the LCUs' battery was discharged.

• Journal of Information Technology Applications and Management
• /
• v.30 no.1
• /
• pp.1-9
• /
• 2023

Interest in the future of the battery market is growing as Tesla announces plans to increase production of electric vehicles and to produce batteries. Tesla announced an action plan to reduce battery prices by 56% through 'Battery Day', which included expansion of factories to internalize batteries and improvement of materials and production technology. In the trend of automobile electrification, the expansion of the battery market, which accounts for 40% of the cost of electric vehicles, is inevitable, and the size of the electric vehicle battery market in 2026 is expected to increase more than five times compared to 2016. With the development of materials and process technology, the energy density of electric vehicle batteries is increasing while the price is decreasing. Soon, electric vehicles and internal combustion locomotives are expected to compete on the same line. Recently, the mileage of electric vehicles is approaching that of an internal combustion locomotive due to the installation of high-capacity batteries. In the EV battery market, Korean, Chinese and Japanese companies are fiercely competing. Based on market share in the first half of 2020, LG Chem, CATL, and Panasonic are leading the EV battery supply, and the top 10 companies included 3 Korean companies, 5 Chinese companies, and 2 Japanese companies. All-solid, lithium-sulfur, sodium-ion, and lithium air batteries are being discussed as the next-generation batteries after lithium-ion, among which all-solid-state batteries are the most active. All-solid-state batteries can dramatically improve stability and charging speed by using a solid electrolyte, and are excellent in terms of technology readiness level (TRL) among various technology alternatives. In order to increase the competitiveness of the battery industry in the future, efforts to increase the productivity and economy of electric vehicle batteries are also required along with the development of next-generation battery technology.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.16 no.6
• /
• pp.385-391
• /
• 2023

As the use of electric vehicles has increased to minimize carbon emissions, the analyzing the state and performance of lithium-ion batteries that is instrumental in electric vehicles have been important. Comprehensive analysis using not only the voltage, current and temperature of the battery pack, which can affect the condition and performance of the battery, but also the driving data and charging pattern data of the electric vehicle is required. Therefore, a thorough analysis is imperative, utilizing electric vehicle operation data, charging pattern data, as well as battery pack voltage, current, and temperature data, which collectively influence the condition and performance of the battery. Therefore, collection and preprocessing of battery data collected from electric vehicles, collection and preprocessing of data on driver driving habits in addition to simple battery data, detailed design and modification of artificial intelligence algorithm based on the analyzed influencing factors, and A battery analysis and evaluation model was designed. In this paper, we gathered operational data and battery data from real-time electric buses. These data sets were then utilized to train a Random Forest algorithm. Furthermore, a comprehensive assessment of battery status, operation, and charging patterns was conducted using the explainable Artificial Intelligence (XAI) algorithm. The study identified crucial influencing factors on battery status, including rapid acceleration, rapid deceleration, sudden stops in driving patterns, the number of drives per day in the charging and discharging pattern, daily accumulated Depth of Discharge (DOD), cell voltage differences during discharge, maximum cell temperature, and minimum cell temperature. These factors were confirmed to significantly impact the battery condition. Based on the identified influencing factors, a battery analysis and evaluation model was designed and assessed using the Random Forest algorithm. The results contribute to the understanding of battery health and lay the foundation for effective battery management in electric vehicles.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.37 no.2
• /
• pp.70-76
• /
• 2014

In industrial situation, electronic and electro-mechanical systems have been using different type of batteries in rapidly increasing numbers. These systems commonly require high reliability for long periods of time. Wider application of battery for low-power design as a prime power source requires us knowledge of failure mechanism and reliability of batteries in terms of load condition, environment condition and other explanatory variables. Battery life is an important factor that affects the reliability of such systems. There is need for us to understand the mechanism leading to the failure state of battery with performance characteristic and develop a method to predict the life of such battery. The purpose of this paper is to develope the methodology of monitoring the health of battery and determining the condition or fate of such systems through the performance reliability to predict the remaining useful life of primary battery with load condition, operating condition, environment change in light of battery life variation. In order to evaluate on-going performance of systems and subsystems adopting primary batteries as energy source, The primitive prototype for performance reliability analysis device was developed and related framework explained.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.18 no.3
• /
• pp.240-246
• /
• 2013

An Uninterruptible Power Supply(UPS) is a system designed to deliver energy during accidents that the AC mains is out of its acceptable limits, without interruption of power flow through the load. Battery Discharger is the device to supply high quality power to the Inverter, when accidents occur, such as Power Failure. The Battery Discharger should have a fast response characteristics. The LLC resonant converter for UPS battery discharger is proposed. The proposed Battery Discharger offers substantial improvements in efficiency, size and cost. The proposed Battery Discharger of UPS approach is a good solution for high power applications above KW. To verify the validity of proposed Battery Discharger, simulations and experiments are carried out.

• Journal of international Conference on Electrical Machines and Systems
• /
• v.2 no.4
• /
• pp.460-465
• /
• 2013

Electrical equipments of nuclear power plant are divided into class 1E and non-class 1E. Electrical equipment and systems that are essential to emergency reactor shutdown, containment isolation, reactor core cooling, and containment and reactor heat removal, are classified as class 1E. batteries of nuclear power plant are divided into four channels, which are physically and electrically separate and independent. The battery bank of class 1E DC power system of the nuclear power plant use lead-acid batteries in present. The lead acid battery, which has a high energy density, is the most popular form of energy storage. Kt factor of lead-acid battery is used to determine battery size and it is one of calculatiing coefficient for capacity. this paper analyzes Kt factor of lead-acid battery for the DC power system of nuclear power plant. In addition, correlation between Kt parameter and peukert's exponent of lead-acid battery for nuclear plant are discussed. The analytical results contribute to optimize of determining size Lead-acid battery bank.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.8 no.2
• /
• pp.90-95
• /
• 2009

This paper presents a new lithium ion unit-cell and pack battery by using a new formulation ratio of material. The three types of formulation ratio for the unit-cell were used. The life cycle and basic properties of the lithium ion unit-cell$({\Psi}18{\times}65(mm))$ about one of them were acquired by the charge-discharge experiment. The nominal voltage, nominal capacity and cycle life output of the lithium ion unit-cell is respectively 3.7V, 2.4Ah, and above 500cycle. Pack type lithium ion battery has the size of $29.5{\times}73.5{\times}115(mm)$ and the weight of 300g. As the results, the weight and bulk of lithium ion battery used to a safety lamp were decreased to 1/4 and 1/7. In addition, the comparison of the new lithium ion battery and lead storge battery for confirming the effectiveness of the new lithium ion battery have been performed.