리튬이온 배터리 펄스파워 예측을 위한 DCIR-SOC Relationship 구현
Implementation of the DCIR-SOC Relationship for Pulse Power Capability Prediction of a Li-Ion Cell
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초록
Because of differences in electrochemical characteristics among state-of-charges (SOCs) in an operating range of Li-Ion cell, it is clearly required to establish the relationship using information on the SOC and internal resistance. Therefore, this research newly implements the relationship based on two information on direct current internal resistance (DCIR) and SOC for pulse power capability of a Li-Ion cell. For implementation of the DCIR, the discharging/charging pulse currents are sequently applied to measure the voltage drop/rise during 10 seconds. Then, based on the Ohmic law, it is possible to obtain the DCIR at an arbitrary SOC range. This is made up of single repetitions of the profile, separated by a 10% SOC constant current discharge segment. After obtaining the DCIR-SOC relationship, it can be expected to provide the equivalent electrical-circuit model (EECM)-based pulse power capability prediction algorithm using the extended Kalman filter (EKF).
Abstract
Because of differences in electrochemical characteristics among state-of-charges (SOCs) in an operating range of Li-Ion cell, it is clearly required to establish the relationship using information on the SOC and internal resistance. Therefore, this research newly implements the relationship based on two information on direct current internal resistance (DCIR) and SOC for pulse power capability of a Li-Ion cell. For implementation of the DCIR, the discharging/charging pulse currents are sequently applied to measure the voltage drop/rise during 10 seconds. Then, based on the Ohmic law, it is possible to obtain the DCIR at an arbitrary SOC range. This is made up of single repetitions of the profile, separated by a 10% SOC constant current discharge segment. After obtaining the DCIR-SOC relationship, it can be expected to provide the equivalent electrical-circuit model (EECM)-based pulse power capability prediction algorithm using the extended Kalman filter (EKF).
참고문헌 (7)
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