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A New State of Charge Estimation Method for LiFePO4 Battery Packs Used in Robots

Ming‐Hui Chang, Han‐Pang Huang, Shu-Wei Chang

发表年份
2013
引用次数
37
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摘要

The accurate state of charge (SOC) estimation of the LiFePO4 battery packs used in robot applications is required for better battery life cycle, performance, reliability, and economic issues. In this paper, a new SOC estimation method, “Modified ECE + EKF”, is proposed. The method is the combination of the modified Equivalent Coulombic Efficiency (ECE) method and the Extended Kalman Filter (EKF) method. It is based on the zero-state hysteresis battery model, and adopts the EKF method to correct the initial value used in the Ah counting method. Experimental results show that the proposed technique is superior to the traditional techniques, such as ECE + EKF and ECE + Unscented Kalman Filter (UKF), and the accuracy of estimation is within 1%.

关键词

Extended Kalman filterState of chargeBattery (electricity)Control theory (sociology)Reliability (semiconductor)Kalman filterRobotState (computer science)Computer scienceEngineering

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