Resonance frequency analysis of lead-acid cells: An EIS approach to predict the state-of-health. (February 2020)

• Record Type: Journal Article
• Authors: Calborean, Adrian; Bruj, Olivia; Murariu, Teodora; Morari, Cristian
• Is Part Of: Journal of energy storage. Volume 27(2020)
• Publication Date: 2020-02
• Subjects: Lead-acid cells -- PEIS spectroscopy -- Controlled aging -- Frequency dependent impedance -- Resonance frequency -- Aging fitting model; Energy storage -- Periodicals; Energy storage -- Research -- Periodicals; 621.3126
• DOI: 10.1016/j.est.2019.101143
• Languages: English
• ISSNs: 2352-152X

Abstract

Highlights: The EIS data are used to perform a qualitative analysis of the lead-acid battery SOH. Controlled aging of the battery was made in order to find a correlation based on resonance frequency parameter. Impedance plots vs frequency shifting diagrams emphasize an accurate prediction tool for SOH. For cells produced under controlled conditions, we get a larger lifetime. An inferior degradation speed to the cells manufactured in laboratory was resulted. Abstract: We present in this work a new electrochemical impedance spectroscopy approach for lifetime prediction of lead-acid cells under imposed aging conditions. Frequency dependent impedance fluctuations are being monitored during charging and discharging sequences of battery for two distinct states of charges. We monitored the battery impedance behavior in two distinct states: at 100% state of charge, and secondly, at 75% state-of-charge. During the aging process, we encompassed the impedance plots vs frequency shifting diagrams, in the framework of a single parameter, we refer here to resonant frequency of the circuit. The validation of our model was demonstrated by comparing the resonance frequency values in three fabricated cells, thus emphasizing the changes that appear in the various physical details, depending on battery fabrication methodology. For State-of-Charge = 100% the degradation of the battery is leading to an important variation of its resonance frequency, while for State-of-Charge = 75%, the fluctuations of resonance frequency are significantly smaller. Monitoring just one parameter, we developed an accurate fitting model function capable to predict the lead-acid cells aging process. We can say that for the cell produced under controlled conditions, we get a larger lifetime and an inferior degradation speed to the cells manufactured in laboratory.