Fractional Order Modeling of a Li-ion Battery using Recursive Least Squares Approach considering the Effect of Aging and Variable Forgetting Factor

Abstract

Modeling of a Li-ion battery plays a pivotal role in the battery management system (BMS) of electrical vehicles (EVs). In battery modeling, the fractional order model (FOM) becomes the better alternative compared to the integral order model (IOM) as it provides greater accuracy and deals with the fractional calculus in solving the differential equations of the battery. However, the precise estimation of the parameters is required for the proper use of the FOM in practical applications. In this paper, the recursive least square (RLS) algorithm is considered based on its recursive nature and its ability to estimate the parameter when the new data is already available. For improved parameter estimation, the forgetting factor (FF) has been taken into account in the RLS method. In order to add some weights to the estimates a variable forgetting factor (VFF) is introduced in the RLS algorithm. This paper analyzes the FOM and its parameters based on the RLS algorithm in which the VFF has been incorporated. A new approach to RLS has been proposed by considering the aging effect of the battery after that it went through a significant number of charging and discharging cycles. The comparative analysis for different cycles and variations in parameters for the aging effect and variable forgetting factor recursive least square (VFFRLS) method can be seen from the results.