Inline state of health estimation of lithium-ion batteries using state of charge calculation

Abstract

The determination of state-of-health (SOH) and state-of-charge (SOC) is challenging and remains as an active research area in academia and industry due to its importance for Li-ion battery applications. The estimation process poses more challenges after substantial battery aging. This paper presents an inline SOH and SOC estimation method for Li-ion battery packs, specifically for those based on LiFePO4 chemistry. This new hybridized SOC and SOH estimator can be used for battery packs. Inline estimated model parameters were used in a compounded SOC + SOH estimator consisting of the SOC calculation based on coulomb counting method as an expedient approach and an SOH observer using an extended Kalman filter (EKF) technique for calibrating the estimates from the coulomb counting method. The algorithm's low SOC and SOH estimation error, fast response time, and less-demanding computational requirement make it practical for on-board estimations. The simulation and experimental results, along with the test bed structure, are presented to validate the proposed methodology on a single cell and a 3S1P LiFePO4 battery pack.