High Precision SoC Estimation of LiFePO4 Blade Batteries Using Improved OCV-Based PNGV Model

The state-of-charge (SoC) stands as a pivotal measure for ascertaining a battery's remaining capacity. Accurate SoC estimations can meaningfully enhance a battery's operational longevity, fortify safety standards, and enrich user experience. This paper presents an improved open circuit voltage (OCV)-based partnership for a new generation of vehicle (PNGV) model, specifically tailored for estimating the SoC of LiFePO4 blade batteries. These batteries are distinctively characterized by their advantages in safety, energy density, and thermal management. The proposed model uniquely integrates the SoC-dependent property of the battery's internal resistance, facilitating a marked improvement in estimation accuracy over existing PNGV models. Experimental results underscore the capability and effectiveness of the proposed model in estimating real-time discharging curves, achieving a remarkably low relative error rate of 0.85%.