Robust hybrid estimator for the state of charge of a lithium-ion battery - Awelewa, Ayokunle; Omiloli, Koto; Samuel, Isaac; Olajube, Ayobami; Popoola, Olawale (Frontiers in Energy Research, 2023)
The use of batteries for diverse energy storage applications is increasing, primarily because of their high energy density, and lithium-ion batteries (LiBs) are of particular significance in this regard. However, designing estimators that are robust to compute the state of charge (SOC) of these batteries in the presence of disturbance signals arising from different battery types remains a challenge. Hence, this paper presents a hybrid estimator that combines the extended Kalman Filter (EKF) and Sliding Mode Observer (SMO) via a switching function and tracking closed loop to achieve qualities of noise cancellation and disturbance rejection. The hybridization was carried out such that the inactive observer tracks the output of the used observer, at the same time feeding back a zero-sum signal to the input gain of the used observer. Results obtained show that noise filtering is preserved at a convergence time of 0.01 s. As well, the SOC estimation interval improves greatly from a range of [1, 0.93] and [0.94, 0.84] obtained from EKF and SMO, respectively, to a range of [1, 0]— inspite of the disturbance from a lithium-nickel (INR 18650) battery type.