The study of the application of the sliding mode observer method that estimates the state of charge. Based on the state space model of battery established on the model of improved EMF equivalent circuit, a sliding mode state observer is designed to help improve the jitter problem. Considering the nonlinear terms in the model for the analysis of the stability of the observer and the characteristics of the industry under its derivative, and using Lagrange mean value theory to guarantee the convergence conditions of the observer, the design parameters of the observer can thus be determined .Then, this thesis compares the simulation of this method under Matlab environment with the extended Kalman filter method. The results show that the method has higher estimation accuracy in the case of the same battery modeling errors. Therefore, the SOC estimation of the sliding mode observer can effectively reduce the state of charge estimation error introduced by the model error.
Fuzzy Sliding Mode Observer with Grey Prediction for the Estimation of the State-of-Charge of a Lithium-Ion Battery
