Second‐Order Harmonic in the Current Response to Sinusoidal Perturbation Voltage for Lead‐Acid Battery: An Application to a State‐of‐Charge Indicator

Abstract

Distortion of the current response to sinusoidal alternating perturbation voltage has been quantitatively measured as a function of state of charge for commercially available lead-acid batteries. The input amplitude adopted here was greater than those used for ordinary impedance measurement. The distortion is represented as a power spectrum. Among higher order harmonics, that of the second one was selected for the parameter of a state-of-charge indicator. Excellent linearity was observed for the state of charge. It was also clarified that, compared to other parameters of the indicator, such as terminal voltage, impedance of fundamental tone, and concentration of sulfuric acid, this parameter is less influenced by other factors during practical operation, such as discharge current and rest time.Many types of state-of-charge indicators have been proposed for use in primary and secondary batteries. In particular, interests have been directed to lead-acid batteries, which are very popular as SLI batteries, emergency power supplies, and electric vehicle power sources. For the last case, especially, a state-of-charge indicator serves as a fuel meter and plays an important role in the system. As for the SLI batteries, though state-of-charge is presently not monitored, it is hoped that its indication can be incorporated into the car's indicator system for the sake of convenience.Recently, special efforts have been made to develop various advanced secondary batteries for vehicular and load leveling applications. In consideration of their operational conditions, a correct understanding of the state-of-charge is very important. Consequently, the need for the development of indicators of high accuracy at low cost now becomes greater and greater.Most indicators proposed so far are based in principle on terminal voltage (1), impedance (2), and especially the concentration of sulfuric acid in the case of lead-acid batteries. Density (3), refractive index (4), and saturated humidity (5) have been studied as physical properties representing the concentration of sulfuric acid. The state-ofcharge can also be obtained from integrated current. To measure these physical quantities accurately, simply, and automatically in packed batteries, many devices have been proposed (1-5). Still, many problems remain, and only a few devices have proved good enough to be of practical use. For example, when sulfuric acid concentration is selected as a parameter, a large time delay exists between the change of residual charge and the corresponding concentration at the probe. Thus, real-time monitoring is not possible in this case. Terminal voltage takes different values in the absence and in the presence of a load. If this difference is corrected according to current, the device will be very complicated and costly. Finally, fundamental wave impedance is largely dependent on rest time for lead-acid batteries (6). An attempt is now being made to apply it to primary cells before use (2).Thus, a new parameter closely correlated to the residual charge of ...

Computer Simulations of the Impedance Response of Lithium Rechargeable Batteries

“…The slopes of these plots (either using the real or imaginary component of the impedance) in the diffusion-dominated region can be used to calculate the diffusion coefficient using the standard formula 7 [20] where the slope A is in units of ⍀ cm 2 s Ϫ1/2 . The ratio of true area to superficial area appears in this formula in the form of the (aL) parameter.…”

“…14 A review of the literature reveals little data on the impedance of sealed, commercial lithium-ion batteries, 15 but these data may eventually be applied in state-of-charge determination, state-of-health and cycle-life prediction, and electronic control and monitoring, as has been the case with other battery systems. [16][17][18][19][20][21][22][23][24] One limitation to date in EIS studies of batteries has been the interpretation of the impedance spectra. Battery impedance data are impacted by a complicated set of processes including porous-electrode effects, the superposition of the separator and two electrode impedance responses, transient and nonlinear responses, and the additional artifacts of the battery current collectors, terminals, and other peripherals.…”

State-of-Health Identification of Lithium-Ion Batteries Based on Nonlinear Frequency Response Analysis: First Steps with Machine Learning

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State-of-Health Diagnosis of Lithium-Ion Batteries Using Nonlinear Frequency Response Analysis

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