Covariance controlled state-of-charge estimator of LiFePO4 cells using a simplified hysteresis model

Abstract

Equivalent circuit model (ECM)-based state-of-charge (SOC) estimation has been considered as one of the most important aspects in battery management system (BMS). However, in case of a lithium iron phosphate (LiFePO4) cell, because of the flatness and hysteresis effect of the open-circuit voltage (OCV) curve, there are inevitable drawbacks directly related to both erroneous SOC information and the slow SOC convergence speed caused by incorrect OCV characteristics. Therefore, this approach gives insight to the design and implementation of the ECM-based SOC estimator that is suitable for an actual LiFePO4 cell. Two approaches for settlement in current OCV issues are as follows. Firstly, through linearization between coordinated charging and discharging OCVs, an OCV hysteresis model can be easily implemented. This model incorporating OCV measurement data is adequately applied to the model-based SOC estimator using the extended Kalman filter (EKF). Secondly, a well-adjusted measurement error covariance controlled in the EKF is used to alleviate an undesired SOC fluctuation that surely results in low BMS performance. This measurement error covariance additionally enables us to provide the fast SOC convergence speed against an inaccurate initial SOC value. This approach has been sufficiently validated by extensive experimental results conducted on LiFePO4 cells that had a rated capacity of 14 Ah by EIG. Consequently, our validation showed the clearness of the proposed work for a reliable SOC estimator of a LiFePO4 cell.