Improved State-of-Charge Estimation for Batteries Using Internal Resistance Variations

Internal resistance of a battery reflects its distinct characteristics, including factors such as state of health (SOH), state of charge (SOC), reversibility, thermal runaway, etc. This paper develops a simple non-invasive battery analysis approach based on modified intermittent current interruption (ICI) methods for characterizing the internal resistance <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(\mathbf{R}_{\text{int}})$</tex> and variations of internal resistance <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(\Delta \mathbf{R}_{\text{int}})$</tex> at different SOC and different testing currents. The decreasing trend of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{R}_{\text{int}}$</tex> while increasing SOC, alongside the notable increase in <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{R}_{\text{int}}$</tex> coupled with capacity loss, highlights the potential of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{R}_{\text{int}}$</tex> as a reliable indicator for assessing the SOC of batteries. More importantly, the paper presents a study on <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\Delta \mathbf{R}_{\text{int}}$</tex> between discharged states and charged states and identifies an increasing trend between <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\Delta \mathbf{R}_{\text{int}}$</tex> with the usable capacity of batteries under different testing currents. This positive correlation suggests that <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\Delta \mathbf{R}_{\text{int}}$</tex> could be an enhanced parameter in non-invasive battery analysis for predicting the SOC of batteries, especially suitable for Battery Management System (BMS) applications. The <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\Delta \mathbf{R}_{\text{int}}$</tex> model, which highlights the internal resistance variations caused by charge transfer during lithiation and delithation process, provides a robust solution for predicting the SOC of batteries while overcoming cell-to-cell variations in battery packs.