SOH Diagnostic and Prognostic Based on External Health Indicator of Lithium-ion Batteries

Abstract

The state-of-health (SOH) is a critical factor in guaranteeing the safe operation and reliability of Lithium-ion battery-related equipment. One of the main challenges is the accuracy and practicality of health indicator (HI) extraction and suitable algorithm for SOH diagnosis and prognosis. This paper proposes a new method that implements an extended Kalman filter (EKF) with an external HI to diagnose and prognose the SOH of Lithium-ion batteries (LIBs) and the results are expressed in form of a probability distribution function (PDF). First, aging experiments are conducted on LIBs. Second, an HI that has a strong relation to the SOH of LIBs is extracted from the terminal voltage of batteries. Third, EKF algorithm is implemented to diagnose and prognose the SOH of batteries. Fourth, the proposed method is verified with a series of experiments. The results demonstrate the effectiveness of the proposed method in terms of SOH diagnostic and prognostic.