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http://dx.doi.org/10.21289/KSIC.2022.25.3.387

Prediction Method of End of Charge Voltage using Battery Parameter Measurement  

Kim, Ho-Yong (Dept. of Electrical Engineering, Chonnam National University)
Wang, Yi-Pei (Dept. of Electrical Engineering, Chonnam National University)
Park, Seong-Mi (Dept. of Lift Engineering, Korea Lift College)
Park, Sung-Jun (Dept. of Electrical Engineering, Chonnam National University)
Son, Gyung-Jong (Dept. of Electrical Engineering, Chonnam National University)
Publication Information
Journal of the Korean Society of Industry Convergence / v.25, no.3, 2022 , pp. 387-396 More about this Journal
Abstract
Recently, e-Mobility, which is a personal mobility device such as an electric bicycle or an electric scooter, is rapidly emerging. However, since E-Mobility has various voltage systems due to the characteristics of its products, it is essential for companies that operate them to use multiple dedicated chargers. A universal charger capable of charging batteries of various voltage systems with one charger is required to reduce the cost of purchasing and managing multiple dedicated chargers. For this, information on the EOC(End of Charge) is essential. In order to know the EOC, it is necessary to detect the internal impedance of the battery. However, the internal impedance of the battery changes according to various conditions such as SOH(State Of Health), SOC(State Of Charge), and ambient temperature. By observing the change in these parameters, the state of the battery can be diagnosed and the EOC can be predicted. In this paper, we propose an algorithm to analyze the battery's internal impedance and to predict the EOC, in order to acquire information on the EOC of the battery, which is an essential requirement of a universal charger.
Keywords
E-Mobility; Battery; EOC(End of Charge) Voltage; SOH(State Of Health); SOC(State Of Charge); DCIR(Direct Current Internal Resistance);
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
연도 인용수 순위
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