Abstract Battery management systems (BMSs) are essential for accessing and managing battery performance information, with state of health (SOH) estimation providing insights into the battery’s life expectancy. Electrochemical impedance spectroscopy (EIS) is a non-destructive method for SOH assessment. However, collecting EIS data across diverse operating conditions and battery types is both time-intensive and costly, presenting challenges related to data distribution and heterogeneity. This work