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Secondary Battery SOC Estimation Technique for an Autonomous System Based on Extended Kalman Filter

자율이동체를 위한 2차 전지의 확장칼만필터에 기초한 SOC 추정 기법

  • 전창완 (순천향대학교 전기통신공학과) ;
  • 이유미 (순천향대학교 전기통신공학과)
  • Published : 2008.09.01

Abstract

Every autonomous system like a robot needs a power source known as a battery. And proper management of the battery is very important for proper operation. To know State of Charge(SOC) of a battery is the very core of proper battery management. In this paper, the SOC estimation problem is tackled based on the well known Extended Kalman Filter(EKF). Combined the existing battery model is used and then EKF is employed to estimate the SOC. SOC table is constructed by extensive experiment under various conditions and used as a true SOC. To verify the estimation result, extensive experiment is performed with various loads. The comparison result shows the battery estimation problem can be well solved with the technique proposed in this paper. The result of this paper can be used to develop related autonomous system.

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