Real-time Recycled ion-Lithium Battery SOC Estimation Using Forgetting Factor RLS Algorithm

Estimating the state of charge (SOC) of lithium batteries is critical for the management and diagnosis of these devices. This article proposes an estimation method using for-getting factor recursive least square (FFRLS) algorithm. Using the comprehensive predictor and the consideration of noise, the tracking effects of the FFRLS algorithm show that the improved forgetting factor function can effectively improve the accuracy and estability of estimating the SOC in non-invasive real time to obtain the battery parameters without having to remove it from the circuit. Experimental results will be presented in the final version of this paper.