Estimating battery state of health using electrochemical impedance spectroscopy and the relaxation effect

Among the most important tasks of a Battery Management System (BMS) are State of Charge (SoC) and State of Health (SoH) estimation. Many SoH estimation techniques are available, each with their advantages and drawbacks. These include methods based on a technique known as Electrochemical Impedance Spectroscopy (EIS). This technique provides detailed information about the battery's state of health but requires long rest times to prevent the battery relaxation effect from impacting the EIS measurement. In this paper EIS is shown to be able to track the short-term relaxation effect for batteries of different SoH. A SoH estimation method is proposed which combines fractional order impedance modeling and short-term relaxation effects with EIS characterization for rapid SoH determination. This empirical method is demonstrated to have an average SoH estimation error of less than 1%. As new methods arise to simplify EIS hardware requirements for real time applications, the proposed method offers a new way of utilizing EIS for SoH estimation.