Hysteresis modeling for model-based condition monitoring of lithium-ion batteries

A real-time battery model capable of accurately predicting the battery hysteresis effect is critical for a model-based battery conditional monitoring algorithm in advanced battery management systems. Battery condition monitoring involves tracking changes in physical parameters and operational states such as state of charge (SOC) and state of health (SOH) to ensure the optimal operation and safety of a battery system. This paper investigates and models the hysteresis behavior of lithium-ion battery cells and incorporates the hysteresis model in the real-time battery model to improve the accuracy of the SOC estimation in both charge and discharge modes over the entire operating SOC range and environmental temperature range of the cells. This also leads to accurate maximum capacity estimation to determine the SOH of the battery cells. In addition, a method for extracting the hysteresis model parameters is proposed. Experimental results for a cylindrical lithium-ion cell are provided to validate the proposed model and method.