Lithium-ion battery state of charge estimation using improved coulomb counting method with adaptive error correction

Accurate state of charge (SoC) estimations are vital to guarantee the safe and efficient operation of Lithium-ion battery systems in electric vehicles. In this paper, an improved coulomb counting method with adaptive error correction (ICC-AEC) with dual closed-loop control system (DCLCS) for SoC estimation is proposed. Where, a DCLCS with first-order RC battery modeling using forgetting factor-based recursive least square (FF-RLS) algorithm is utilized to achieve high estimation accuracy by recalibrating the SoC factor and fast response time. To evaluate and validate the performance of the proposed algorithm, a dynamic load profile with a large range of temperature variation is considered. Further, SoC estimation results obtained from traditional mixed method (MM) with closed-loop control system (CLCS) and proposed ICC-AEC with DCLCS are compared. The results show that the SoC estimation error obtained from ICC-AEC with DCLCS is lesser than MM with CLCS under considered dynamic operating conditions.