State-of-health monitoring of 18650 4S packs with a single-point impedance diagnostic

Love, Corey T.; Virji, Maheboob B.V.; Rocheleau, Richard; Swider‐Lyons, Karen

doi:10.1016/j.jpowsour.2014.05.033

Cited by 95 publications

(50 citation statements)

References 27 publications

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“…1 (1539.5 K), E a was estimated to be 0.13 eV. The impedance response and activation energy in this frequency range has been attributed to the ionic conductivity of the SEI, and the value obtained in this work for the Tenergy 18650 LiCoO 2 cells was comparable to other literature-reported values for commercial lithium-ion batteries [10,15,30,33].…”

Section: Resultssupporting

confidence: 79%

“…Consequently, non-invasive diagnostic techniques for lithiumion batteries have recently garnered considerable attention, particularly those using electrochemical impedance spectroscopy (EIS). EIS-based analyses havetraditionally been used for determining internal resistances and capacitances, thermophysical properties, and/or for modeling thermal behavior of batteries [22,[29][30][31].With respect to battery diagnostics, researchers have exhibited EIS-based correlations to monitor both state of health (SOH) [32][33][34][35][36][37] and internal temperature [10,15,16,21,[37][38][39][40].These diagnostic techniques are particularly attractive for several reasons: (i) as previously-mentioned, EIS measurements are non-invasive and therefore do not require battery disassembly or physical insertion of thermocouples or other instrumentation; (ii) they are virtually instantaneous (<1 second) in comparison to the cell's thermal response time; and (iii) they can be applied to any lithium-ion battery chemistry or cell geometry.…”

Section: Introductionmentioning

confidence: 99%

“…SOH determinations via EIS have been performed to detect abuse and/or capacity fadeof commercial lithium-ion batteries through various mechanisms, including overcharge [32,33], overdischarge [34], and aging effects [35,36]. Among these types of battery problems, overcharging is perhaps the most concerning with regard to large format battery packs due to a battery management system's inability to detect unbalanced battery voltages or inaccurate state of charge measurements [33].…”

Section: Introductionmentioning

confidence: 99%

“…Among these types of battery problems, overcharging is perhaps the most concerning with regard to large format battery packs due to a battery management system's inability to detect unbalanced battery voltages or inaccurate state of charge measurements [33]. Love and coworkers have investigated this issue at length using EIS to probe the SOH of both single-and multi-cell lithium-ion batteries and battery packs subjected to intentional overcharge abuse tests [32,33]. Interestingly, this technique was able to detect an overcharged cell whether EIS was performed on individual batteries or on the entire pack as a whole, illustrating the promise and versatility of these types of diagnostic tests.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Expanding the Operational Limits of the Single-Point Impedance Diagnostic for Internal Temperature Monitoring of Lithium-ion Batteries

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Love

Rose-Pehrsson

et al. 2015

Electrochimica Acta

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Section: Resultssupporting

confidence: 79%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Expanding the Operational Limits of the Single-Point Impedance Diagnostic for Internal Temperature Monitoring of Lithium-ion Batteries

Spinner

Love

Rose-Pehrsson

et al. 2015

Electrochimica Acta

Self Cite

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“…The battery used was a recycled used laptop battery type 18650, which had 5 battery cells variation (Love et al, 2014).…”

Section: Methodsmentioning

confidence: 99%

Performance Analysis of Power Bank Fitted with Recycled Laptop Batteries

Hartono

Sunarno

Sarwanto

2017

JPII

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The result of observation at Science Laboratory of State Vocational High School 3 of Surakarta shows that the power capacity of power bank fitted with recycled laptop batteries was not tested. Power bank test was conducted by preparing used laptop batteries type 18650 from its packaging for a total of five cells, selecting batteries based on their physical appearance, cleaning the pole connections, testing the voltage, testing temperature when power charging from electric outlet to power bank, testing the power drain, testing the power capacity without load, charging in the case, testing the module when power charging from electric outlet to power bank, testing the power capacity level indicator, testing power charging from power bank to recharged device, installing the power bank analyzer, and recording voltage measurement results, electric current flowing, duration of time needed to charge, and power capacity left after charging. The electric load used was a 1.2 watt LED lamp. After that, the calculation of battery power capacity was conducted, in accordance with the technical specification listed in the power, then compared to the result of test of power capacity stored in recycled power bank. Based on the result of technical specification calculation, the power bank produced had a power capacity of 50.000 watt hours. Meanwhile, in the experiment with LED lamp electric load, the power bank had a power capacity of 44.6756 watt hours. The comparison of power capacity between the technical specification and the experiment shows that the recycled power bank had performance of 89.4%. Thus, recycled power bank met the requirement of feasibility to be learning media of physics project.

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Simulation of Factor on SOC Inconsistency within a Series‐Connected Lithium‐Ion Battery Pack

Zhang

Yang

Chi

2022

Advcd Theory and Sims

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This paper outlines a new simulation approach to study the effect of factors on the state of charge (SOC) consistency of Li‐ion battery packs. The proposed method is based on a system model and the Monte Carlo method. The system model includes 100 serial connected equivalent circuit models and their respective parameters. This paper divides the internal and external factors into two categories: independent factors such as internal resistance, capacity, Coulombic efficiency, leakage current, and comprehensive factors related to temperature. The Monte Carlo method simulates the differences and distribution of independent factors among cells. Temperature‐dependent factors are modeled with empirical formulas. Simulation results show that the main factors affecting SOC consistency are differences in battery temperature, leakage current, and Coulombic efficiency. Meanwhile, slight differences in capacity and internal resistance have little effect on SOC inconsistency. Furthermore, this paper demonstrates the effectiveness of the system model.

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State-of-health monitoring of 18650 4S packs with a single-point impedance diagnostic

Cited by 95 publications

References 27 publications

Expanding the Operational Limits of the Single-Point Impedance Diagnostic for Internal Temperature Monitoring of Lithium-ion Batteries

Expanding the Operational Limits of the Single-Point Impedance Diagnostic for Internal Temperature Monitoring of Lithium-ion Batteries

Performance Analysis of Power Bank Fitted with Recycled Laptop Batteries

Simulation of Factor on SOC Inconsistency within a Series‐Connected Lithium‐Ion Battery Pack

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