Parameter extraction of the Cole-impedance model for in-situ monitoring of electrochemical sources

An important application of equivalent electrical circuit modeling is in Electrochemical Impedance Spectroscopy (EIS) analysis. Reliable and accurate parameter estimation of such circuits allows for identifying the source of impedance changes, which can be significant for condition monitoring of electrochemical sources in various industrial applications. The time delay between measurements and maintenance action can be reduced with in-situ parameter estimation, followed by decision-making. A method for estimating parameters of the Cole-impedance model is presented in this paper. The method can be used in modeling the impedance of batteries, fuel cells, and solar cells. Our method has been first validated using synthetic datasets, and by comparison with the relevant references. Relative errors in the case of noiseless synthetic data were lower than 0.1 %. Moreover, we processed the experimental impedance data of the lithium-ion battery at the four state of charge (SOC) levels (94.73 %, 89.47 %, 78.95 % and 68.42 %) and at three ambient temperatures (0 degrees C, 10 degrees C and 25 degrees C). Root Mean Square Errors in the case of real and imaginary part of battery impedance were lower than 1.5 omega and 0.75 omega, respectively. It was observed that impedance changes as a function of both temperature and SOC. Identifying different reasons for impedance changes can be of great importance in optimized battery storage or regular exploitation. Finally, the estimation method was deployed on a microcontroller with 8 kB of SRAM and a clock speed of 16 MHz, and the parameters were estimated in just 7.5 s.