Enhanced SVSF for SoC Estimation of Lithium Ion Batteries

The last decade has witnessed a spike in Lithium-ion batteries usage. This fact is due to the battery interesting characteristics. This technology needs careful monitoring to avoid overcharge and deep discharge and ensure user safety. This paper proposes an enhanced version of the Smooth Variable Structure Filter (ESVSF) to estimate the State of Charge (SoC) of lithium ion batteries. The ESVSF algorithm proposes a variable boundary layer with an online and dynamic covariance error determination. This technique is validated on LCO batteries of nominal capacity 2.1Ah and validated on a Random Walk (RW) discharge profile. The correct operation of the proposal is confirmed throw simulation results.