Incremental State-of-Charge determination of a Lithium-ion battery based on Capacity update using Particle Filtering framework

Abstract

State-of-Charge (SOC) is considered as one of the key components of a Battery Management System (BMS), which provides an indication of the remaining charge in a battery. Accurate SOC measurement facilitates longer battery life and mitigates any possible catastrophic battery failure. However, accurate estimation of the battery SOC continues to be a challenging task. There are several topologies to find the SOC of a battery but none of them incorporates the aging factor of a battery due to repeated usage. Considering this fact, the proposed methodology considers the degrading capacity impacts on the incremental SOC of a battery. Incremental SOC is defined as the difference in SOC levels between two successive time intervals. The proposed model is developed based on Particle filtering (PF) framework which eliminates the need of extensive data. In the proposed approach, the incremental SOC has been considered as an indirect indication of the battery health. For validation purpose, battery data from NASA PCoE has been used. The proposed approach revealed that when battery capacity degradation is considered, a correction of 8.73 % (absolute) in incremental SOC is observed, and prediction of incremental SOC with relative error of 1.23 % in reference to the improved incremental SOC was achieved.