The paper presents an experimental investigation of State-of-Health-related parameters of automotive lead-acid batteries under different operating and aging conditions. Although alternative battery technologies have gained increasing attention in recent years, lead-acid batteries are still widely used in vehicle starting systems, making battery condition assessment an important practical concern.

The study focuses on the variation of several electrical parameters commonly associated with battery health, including internal resistance, dynamic conductance, terminal voltage, Cold Cranking Amps (CCA), and available capacity. Experimental measurements were performed on automotive lead-acid batteries exhibiting different levels of charge and degradation in order to evaluate the influence of both State of Charge (SoC) and aging on their electrical performance.

The obtained results reveal significant relationships between battery condition and the investigated parameters. Battery aging is generally associated with an increase in internal resistance, accompanied by a decrease in dynamic conductance, available capacity, and starting capability. Furthermore, the influence of the State of Charge on the measured quantities is analyzed to distinguish temporary performance variations caused by charge level from long-term degradation effects associated with battery wear.

The correlations identified between the investigated parameters provide valuable insight into the behavior of lead-acid batteries throughout their service life. The results also enable an assessment of the suitability of different measurable quantities as indicators of battery condition and degradation. Particular attention is given to the sensitivity of each parameter to changes in charge state and aging, as well as to their potential use in battery diagnostics.

The findings provide experimental insight into the variation of commonly used battery health indicators under different charge and aging conditions. The obtained experimental dataset may also support the development, parameterization, and validation of battery models intended to reproduce battery behavior under various operating conditions with improved accuracy.