Analysis of online lyapunov-based adaptive state of charge observer for lithium-ion batteries under low excitation level

Abstract

The online estimation of the state-of-charge (SOC) of Li-ion battery using the adaptive Lyapunov-based observer is an attractive proposition due to the ensured stability, adaptability and reduced computing requirement. However, the observer requires the presence of the persistent excitation (PE) to guarantee the convergence of the battery model parameters to their correct values. The PE is satisfied using sufficiently rich (SR) signal that contains spectral components to excite the battery model. This paper revisits several important works that utilize such observer and highlights the absence of PE in their practical implementation. Since the previous works utilize dc excitation that lacks the SR characteristics, the validity of the published results is questionable. To rectify the problem, a scheme known as the forced excitation is proposed to estimate the battery parameters under dc or low excitation level. The SR signal is generated by chopping the battery current at a certain rate for specific interval. Moreover, the disruption of the load current (due to the chopping) is compensated using the supercapacitor. The concept is simulated by Matlab/Simulink and is realized experimentally using a Panasonic NCR18650B Li-ion battery. The forced excitation algorithm is implemented on the DS1104 dSPACE platform. The results show that the proposed method satisfies the PE condition and is able to correctly estimate the SOC even with low excitation signals.