An ElectroStatic Discharge Algorithm for Electric Vehicle Li Ion Battery Parameters Estimation

This study proposes a new algorithm for parameter estimation of the electric circuit model of Lithium (Li)-ion battery. The first-order battery-electric circuit model is considered in this work that resembles battery charging and discharging behaviors. The battery circuit element values have been modeled as polynomial equations with unknown coefficients. An accurate estimation of the battery circuit element values is profound to accurately find the battery State of Charge (SoC), an immeasurable quantity required in battery management systems (BMS). The ElectroStatic discharge algorithm (ESDA) is used in this study to estimate the unknown polynomial coefficients and, in turn, the values of the battery circuit elements. The accuracy of the proposed ESDA in estimating the battery circuit element values is compared to the recently proposed Artificial Hummingbird Optimization Technique (AHOT), Chameleon Swarm Algorithm (CSA), and Tuna Swarm Optimization (TSO). The results demonstrate the superiority of the proposed algorithm for charging and discharging in battery parameters estimation over the other algorithms with an accuracy gain of at least 10%.