A systematic model-based degradation behavior recognition and health monitoring method for lithium-ion batteries

Degradation is a complex and intricate process which relates strongly to the state of health (SoH) of a lithium-ion battery. Due to the ambiguous mechanism and sensitivity to the objective factors of lithium-ion batteries, it is difficult to recognize the degradation state and monitor the SoH of a battery. A recognition method for the degradation state to estimate the remaining capacity online has been presented. First, through the analysis of the results of electrochemical impedance spectroscopy (EIS) tests at different SoHs, the degradation level can be detected by the EIS measurement. Second, according to the fractional order theory, an online parameter identification approach with the fractional order impedance model has been proposed for the degradation analysis. Third, the correlation between variation of parameters and degradation level is discussed and the SEI (Solid Electrolyte Interphase) resistance is extracted to predict the remaining capacity by selecting an appropriate fitting function. Finally, the effectiveness of the presented method is validated by the test data, and the estimation error of the remaining capacity can be guaranteed within 3%.