Estimation methods for the state of charge and capacity in various states of health of LiFePO4 batteries

Accurately estimating the capacity and state of charge (SOC) of Li-ion batteries at various aging levels is a crucial function of the Battery Management System (BMS). However, the battery's capacity and open circuit voltage (OCV) change as it ages, which poses challenges to accurately estimating the SOC and capacity of aging batteries. To address this problem, the present paper suggests a capacity iterative loop estimation technique that relies on SOC fusion estimation. The aim is to attain precise SOC and capacity estimation of LiFePO4 aging batteries. Firstly, the RC equivalent circuit model's first-order parameters, along with the OCV-SOC comparison table, the SOC correction interval, and the capacity regression interval for various aging stages are obtained offline. Afterwards, the OCV is identified using the least-squares method with a forgetting factor. The SOC estimation is then performed by combining the correction interval with the open-circuit voltage method and the amperage integration method fusion. Finally, the capacity calibration process for the aged battery is achieved through the iterative loop estimation method, employing the capacity regression interval. The aged battery's capacity calibration is achieved through the use of an iterative cycle estimation approach based on the capacity regression interval. The effectiveness of the method is further verified by experiments, which show that the capacity estimation error of the aged battery is not more than 3 %, and the SOC estimation errors of multiple tests are mainly concentrated below 2 %, indicating outstanding estimation precision.