scholarly journals State-of-Health of Li-ion Battery Estimation Based on the Efficiency of the Charge Transfer Extracted from Impedance Spectra

2022 ◽  
Vol 12 (2) ◽  
pp. 885
Author(s):  
Ahmed Yahia Kallel ◽  
Viktor Petrychenko ◽  
Olfa Kanoun

Several studies show that impedance spectroscopy is a suitable method for online battery diagnosis and State-of-Health (SoH) estimation. However, the most common method is to model the acquired impedance spectrum with equivalent circuits and focus on the most sensitive parameters, namely the charge-transfer resistance. This paper introduces first a detailed model of a battery cell, which is then simplified and adapted to the observable spectrum behavior. Based on the physical meaning of the model parameters, we propose a novel approach for SoH assessment combining parameters of the impedance spectrum by building the ratio of the solid electrolyte interphase (SEI) resistance to the total resistance of SEI and the charge transfer. This ratio characterizes the charge-transfer efficiency at the electrodes’ surfaces and should decrease systematically with SoH. Four different cells of the same type were cycled 400 times for the method validation, and impedance spectroscopy was performed at every 50th cycle. The results show a systematic correlation between the proposed ratio and the number of cycles on individual cell parameters, which build the basis of a novel online method of SoH assessment.

Energies ◽  
2019 ◽  
Vol 12 (23) ◽  
pp. 4507 ◽  
Author(s):  
Yusuke Abe ◽  
Natsuki Hori ◽  
Seiji Kumagai

Lithium-ion batteries (LIBs) using a LiFePO4 cathode and graphite anode were assembled in coin cell form and subjected to 1000 charge-discharge cycles at 1, 2, and 5 C at 25 °C. The performance degradation of the LIB cells under different C-rates was analyzed by electrochemical impedance spectroscopy (EIS) and scanning electron microscopy. The most severe degradation occurred at 2 C while degradation was mitigated at the highest C-rate of 5 C. EIS data of the equivalent circuit model provided information on the changes in the internal resistance. The charge-transfer resistance within all the cells increased after the cycle test, with the cell cycled at 2 C presenting the greatest increment in the charge-transfer resistance. Agglomerates were observed on the graphite anodes of the cells cycled at 2 and 5 C; these were more abundantly produced in the former cell. The lower degradation of the cell cycled at 5 C was attributed to the lowered capacity utilization of the anode. The larger cell voltage drop caused by the increased C-rate reduced the electrode potential variation allocated to the net electrochemical reactions, contributing to the charge-discharge specific capacity of the cells.


Soft Matter ◽  
2014 ◽  
Vol 10 (34) ◽  
pp. 6467-6476 ◽  
Author(s):  
Choonghyun Sung ◽  
Katelin Hearn ◽  
Jodie Lutkenhaus

Layer-by-layer assemblies exhibit increased conductivity and decreased charge transfer resistance upon heating through the thermal transition.


2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Elyas Rafiee ◽  
Mansour Farzam ◽  
Mohammad Ali Golozar ◽  
Ali Ashrafi

Variation of electrochemical impedance with dislocation density was investigated using electrochemical impedance spectroscopy (EIS). For this purpose, EIS measurements were carried out on 10, 20, 30, 40, and 50% cold-rolled commercially pure copper in 0.1 M NaCl (pH = 2) solution. Nyquist plots illustrated that the electrochemical reactions are controlled by both charge transfer and diffusion process. Increasing dislocation density, the magnitude of electrochemical impedance of samples was decreased. Decreasing magnitude of impedance at intermediate frequencies indicated increasing double-layer capacitance. Charge transfer resistance decreased from value 329.6 Ωcm2 for annealed sample to 186.3 Ωcm2 for sample with maximum dislocation density (1.72×1015 m−2). Phase angles were lower for samples that contained more dislocation density, indicating more tendencies to loss of electrons and releasing atoms into electrolyte.


Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 788
Author(s):  
Hien T. Ngoc Le ◽  
Sungbo Cho

Aggregation of amyloid-β (aβ) peptides into toxic oligomers, fibrils, and plaques is central in the molecular pathogenesis of Alzheimer’s disease (AD) and is the primary focus of AD diagnostics. Disaggregation or elimination of toxic aβ aggregates in patients is important for delaying the progression of neurodegenerative disorders in AD. Recently, 4-(2-hydroxyethyl)-1-piperazinepropanesulfonic acid (EPPS) was introduced as a chemical agent that binds with toxic aβ aggregates and transforms them into monomers to reduce the negative effects of aβ aggregates in the brain. However, the mechanism of aβ disaggregation by EPPS has not yet been completely clarified. In this study, an electrochemical impedimetric immunosensor for aβ diagnostics was developed by immobilizing a specific anti-amyloid-β (aβ) antibody onto a self-assembled monolayer functionalized with a new interdigitated chain-shaped electrode (anti-aβ/SAM/ICE). To investigate the ability of EPPS in recognizing AD by extricating aβ aggregation, commercially available aβ aggregates (aβagg) were used. Electrochemical impedance spectroscopy was used to probe the changes in charge transfer resistance (Rct) of the immunosensor after the specific binding of biosensor with aβagg. The subsequent incubation of the aβagg complex with a specific concentration of EPPS at different time intervals divulged AD progression. The decline in the Rct of the immunosensor started at 10 min of EPPS incubation and continued to decrease gradually from 20 min, indicating that the accumulation of aβagg on the surface of the anti-aβ/SAM/ICE sensor has been extricated. Here, the kinetic disaggregation rate k value of aβagg was found to be 0.038. This innovative study using electrochemical measurement to investigate the mechanism of aβagg disaggregation by EPPS could provide a new perspective in monitoring the disaggregation periods of aβagg from oligomeric to monomeric form, and then support for the prediction and handling AD symptoms at different stages after treatment by a drug, EPPS.


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