Adaptive Observer based Simultaneous Estimation of Model Parameters and State-of-Charge of Lithium-ion Battery

The problem of simultaneous estimation of model parameters and states is considered for a class of non-linear systems. The model of the system is expressed in linear parameterized form which contains explicit functions of unknown parameters. The model is used to design an adaptive observer to obtain the estimation of the states. At the same time, the unknown model parameters are estimated by using adaptive laws based on Sliding Mode Control (SMC). The stability of the designed observer is proved by using the Lyapunov approach. The resulting error dynamics is exponentially stable with robustness to external disturbances. The estimated error variables remain ultimately bounded even in the presence of disturbances. Simulation results are presented by using the technique for the problem of estimating the model parameters and State-of-Charge (SOC) of Lithium-ion Battery. The accuracy of the estimated variables obtained through simulation results shows the effectiveness of the technique.