The aging mechanisms of lead-acid batteries change the electrochemical characteristics. For example, sulfation influences the active surface area, and corrosion increases the resistance. Therefore, it is expected that the state of health (SoH) can be reflected through differentiable changes in the impedance of a lead-acid battery. However, for lead-acid batteries, no reliable SoH algorithm is available based on single impedance values or the spectrum. Additionally, the characteristic changes of the spectrum during aging are unknown. In this work, lead-acid test cells were aged under specific cycle regimes known as AK3.4, and periodic electrochemical impedance spectroscopy (EIS) measurements and capacity tests were conducted. It was examined that single impedance values increased linearly with capacity decay, but with varying slopes depending on the prehistory of the cell and measurement frequency of impedance. Thereby, possible reasons for ineffective SoH estimation were found. The spectra were fitted to an equivalent electrical circuit containing, besides other elements, an ohmic and a charge-transfer resistance of the negative electrode. The linear increase of the ohmic resistance and the charge-transfer resistance were characterized for the performed cyclic aging test. Results from chemical analysis confirmed the expected aging process and the correlation between capacity decay and impedance change. Furthermore, the positive influence of charging on the SoH could be detected via EIS. The results presented here show that SoH estimation using EIS can be a viable technique for lead-acid batteries.

Acid stratification is a common issue in lead-acid batteries. The density of the electrolyte rises from the top to the bottom and causes inhomogeneous current distribution over the electrodes. The consequences are unequal aging processes provoking earlier battery failure. In stationary applications electrolyte circulation pumps are sporadical installed in the battery to mix the acid. For automotive applications passive mixing systems are implemented by some battery manufacturers against stratification. Stratification does not show any distinct voltage-current profile to be recognizable online. However, it increases the voltage and affects the impedance, which both are essential information for diagnostic purpose. Impedance spectra were performed here on lead-acid test cells with adjusted stratification levels to analyze the influence on the impedance in details. It is observed, that the high-frequency impedance is decreased in the stratified cell and that in contrast to this the charge-transfer resistance is increased. Based on simulations with a spatially-resolved equivalent electrical circuit the increased charge-transfer resistance could be explained with an inhomogeneous State-of-Charge resulting in an accumulation of sulfate crystals in the bottom part of the electrodes. These sulfate crystals further affected recorded impedance spectra after the electrolyte was homogenized.

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Impedance or admittance measurements are a common indicator for the condition of lead-acid batteries in field applications such as uninterruptible power supply (UPS) systems. However, several commercially available measurement units use different techniques to measure and interpret the battery impedance. This paper describes common measurement methods and compares their indication for the state of health (SoH) to those of electrochemical impedance spectroscopy (EIS). For this analysis, two strings consisting each of 24 valve-regulated lead-acid (VRLA) batteries with a rated voltage of 12 V and about 7 Ah capacity were kept under standard UPS conditions in float charge for over 560 days. They were monitored continuously with a LEM Sentinel 2 and went into regular check-ups with impedance measurements by a Hioki BT3554 as well as electrochemical impedance spectroscopy (EIS) measurements with an impedance meter (μEIS). Today it is widely expected that solely the relative increase of the impedance reading is sufficient for the estimation of the available capacity. However, it can be shown that the measured relative increase deviates for different frequencies and therefore the choice of the excitation signal and measurement frequency does make a difference for the calculation of the available capacity. Finally, a method for a more decisive monitoring in field applications is suggested.