• Applied Chemistry for Engineering
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• v.35 no.1
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• pp.48-53
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• 2024

We predicted the calendar aging and long-term lifetime of lithium-ion batteries using an electrochemical-based SEI growth model. Numerical simulation was carried out employing the four different long-term SEI growth models (i.e., solvent diffusion limited model, electron migration limited model, Li-interstitial diffusion limited model, reaction limited model), and we calculated the capacity fade and loss of lithium inventory during calendar aging. The result showed that the electron migration limited model and Li-interstitial diffusion limited model showed lower capacity fade, while the solvent diffusion limited model and reaction limited model reached 80% of capacity fade within 10 years. During calendar aging, the lower storage temperature showed less capacity fade due to the hindrance of SEI growth rate. During cycling, the higher C-rate showed a shorter life cycle; however, the differences were not significant.

• International Journal of Contents
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• v.16 no.1
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• pp.75-86
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• 2020

As the elderly population is becoming an aging society, the elderly are experiencing many problems. Social security costs for the elderly are increasing and the un-linked social phenomenon is emerging. Thus, the social infrastructure and welfare system established in the past economic growth period are in danger of not functioning properly. People socially isolated or with chronic diseases among the elderly are exposed to various accidents. Thus, an active healthcare management service is imperative. Additionally, in the event of a dangerous situation, the system must have ways to notify guardians (family or medical personnel) regarding appropriate action. Thus, in this paper, we propose the smartphone-based healthcare and emergency response service platform. The proposed service platform aggregates movement of relevant data in real-time using a smartphone. Based on aggregated data, it will always recognize the user's movements and current state using the human motion recognition mechanism. Thus, the proposed service platform provides real-time status monitoring, activity reports, a health calendar, location-based hospital information, emergency situation detection, and cloud messaging server-based efficient notification to several subscribers such as family, guardians, and medical personnel. Through this service, users or guardians can augment the level of care for the elderly through the reports. Also, if an emergency situation is detected, the system immediately informs guardians so as to minimize the risk through immediate response.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.5
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• pp.436-442
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• 2020

ESS(energy storage system) has recently become an important power source in various areas due to increased renewable energy resources. The more ESS is used, the less the effective capacity of the ESS. Therefore, it is important to manage the remaining useful lifetime(RUL). RUL can be checked regularly by inspectors, but it is common to be monitored and estimated by an automated monitoring system. The accurate state estimation is important to ESS operator for economical and efficient operation. RUL estimation model usually requires complex mathematical calculations consisting of cycle aging and calendar aging that are caused by the operation frequency and over time, respectively. A lightweight RUL estimation model is required to be embedded in low-performance processors that are installed on ESS. In this paper, a lightweight ESS RUL estimation model is proposed to operate on low-performance micro-processors. The simulation results show less than 1% errors compared to the original RUL model case. In addition, a performance analysis is conducted based on ATmega 328. The results show 76.8 to 78.3 % of computational time reduction.