• 전력전자학회:학술대회논문집
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• 전력전자학회 2016년도 전력전자학술대회 논문집
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• pp.345-346
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• 2016

The grid-connected energy storage systems, which could increase the reliability, efficiency, and cleanliness of the grid is presently restricted by the high cost of batteries. This problems could be solved by batteries retired from automotive services. These batteries can provide a low-cost system for energy storage and other applications such as residential applications and renewable energy integration. This paper gives an overview of technical requirements for the re-use of the electric vehicle batteries in energy storage systems.Firstly, the motivation of research is introduced. Secondly, the technologies needed for the re-use of the battery are introduced such asidentification of the battery characteristics, grading of the aged batteries, identification of the state-of-charge and state-of-health of the battery and suitable power electronic converter topologies. In addition the control strategy to maximize the battery lifespan and bypass the faulty batteries is presented and one-stop solution to implement the above mentioned technologies are also given.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권1호
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• pp.41-60
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• 2018

Recently, road traffic congestion is becoming a serious urban phenomenon, leading to massive adverse impacts on the ecology and economy. Therefore, solving this problem has drawn public attention throughout the world. One new promising solution is to take full advantage of vehicular ad hoc networks (VANETs). In this study, we propose a new traffic congestion detection and quantification method based on vehicle clustering and fuzzy assessment in VANET environment. To enhance real-time performance, this method collects traffic information by vehicle clustering. The average speed, road density, and average stop delay are selected as the characteristic parameters for traffic state identification. We use a comprehensive fuzzy assessment based on the three indicators to determine the road congestion condition. Simulation results show that the proposed method can precisely reflect the road condition and is more accurate and stable compared to existing algorithms.