A neuro-fuzzy system to evaluate the remaining useful life of the lithium-ion battery using the impedance spectrum in the overall range of SOCs

Lithium-ion batteries are widely used in various applications, including electric vehicles, because of their appealing characteristics. As the demand for batteries grows, addressing future challenges related to waste batteries becomes increasingly important. Among the methods for assessing the remaining lifespan of waste batteries, battery impedance analysis has gained prominence for its simplicity and cost-effectiveness. This study proposes a model for estimating battery lifespan by analyzing impedance measurements across different state-of-charge (SOC) levels and employing a neuro-fuzzy system. Experimental data were gathered by aging multiple lithium batteries to measure impedance spectra at various SOC intervals from which impedance parameters were derived. Then, these parameters were utilized to develop a lifespan estimation model whose effectiveness was validated through error analysis comparing measured and predicted values. Notably, the accuracy of the lifespan model was enhanced by leveraging data from multiple batteries.