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

Harting, Nina; Wolff, Nicolas; Röder, Fridolin; Krewer, Ulrike

doi:10.1149/2.1031902jes

Cited by 23 publications

(21 citation statements)

References 37 publications

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“…Moreover, even more sensitive to reactions and degradation at the surface is the nonlinear version of impedance spectroscopy, nonlinear frequency response analysis [44] . Among other advantages, it enables one to distinguish between plating and cycling aging [45,46] . However, even today this method is not easy to interpret.…”

Section: Introductionmentioning

confidence: 99%

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The Effects of Gas Saturation of Electrolytes on the Performance and Durability of Lithium‐Ion Batteries

et al. 2021

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Traces of species in batteries are known to impact battery performance. The effects of gas species, although often reported in the electrolyte and evolving during operation, have not been systematically studied to date and are therefore barely understood. This study reveals and compares the effects of different gases on the charge-discharge characteristics, cycling stability and impedances of lithium-ion batteries. All investigated gases have been previously reported in lithium-ion batteries and are thus worth investigating: Ar, CO 2 , CO, C 2 H 4 , C 2 H 2 , H 2 , CH 4 and O 2 . Gas-electrolyte composition has a significant influence on formation, coulombic and energy efficiencies, C-rate capability, and aging. Particularly, CO 2 and O 2 showed a higher C-rate capability and a decrease in irreversible capacity loss during the first cycle compared to Ar. Similar discharge capacities and aging behaviors are observed for CO, C 2 H 4 and CH 4 . Acetylene showed a large decrease in performance and cycle stability. Furthermore, electrochemical impedance spectroscopy revealed that the gases mainly contribute to changes in charge transfer processes, whereas the effects on resistance and solid electrolyte interphase performance were minor. Compared to all other gas-electrolyte mixtures, the use of CO 2 saturated electrolyte showed a remarkable increase in all performance parameters including lifetime.

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Section: Introductionmentioning

confidence: 99%

“… [44] Among other advantages, it enables one to distinguish between plating and cycling aging. [ 45 , 46 ] However, even today this method is not easy to interpret. Thus, for an initial study, we used EIS and discharge curves at different currents to study the impact of gases on performance.…”

Section: Introductionmentioning

confidence: 99%

The Effects of Gas Saturation of Electrolytes on the Performance and Durability of Lithium‐Ion Batteries

et al. 2021

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“…In contrast, there are few studies on the cycle life of Li-ion batteries. Besides, due to the strong nonlinear [25][26][27][28] characteristics of Li-ion batteries, there is little in-depth discussion on the effective cycle criteria of Li-ion batteries, and most studies use the criteria based on impedance and capacity [29][30][31][32]. As a result, the shortcomings of the cyclic method that it is difficult to accurately estimate the number of cycles has not been compensated.…”

Section: Introductionmentioning

confidence: 99%

An Improved Rainflow Algorithm Combined with Linear Criterion for the Accurate Li-ion Battery Residual Life Prediction

Huang¹,

Wang²,

Xu³

et al. 2021

International Journal of Electrochemical Science

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Li-ion battery health assessment has been widely used in electric vehicles, unmanned aerial vehicle and other fields. In this paper, a new linear prediction method is proposed. By weakening the sensitivity of the Rainflow algorithm to the peak data, it can be applied to the field of battery, and can accurately count the number of Li-ion battery cycles, and skip the cumbersome link of parameter identification. Then, a linear criterion is proposed based on the idea of proportion, which makes the life prediction of Li-ion battery linear. Under the verification of multiple sets of data, the prediction error of this method is kept within 2.53%. This method has the advantages of high operation efficiency and simple operation, which provides a new idea for battery life prediction in the field of electric vehicles and aerospace.

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“…There are few novel methods reported in the literature where some kind of special arrangements are made to estimate the SOH [22][23][24] . In 22 , the response of an AC excitation current is processed using the nonlinear frequency response analysis (NFRA) technique to estimate the capacity fade due to the loss of active material. In 23 , the battery is charged with pulse charging technique and the electrical equivalent circuit parameters are estimated using two ANNs for lower and upper frequency ranges.…”

mentioning

confidence: 99%

“…3. Special kinds of probing signals are injected for SOH estimation, which may not be feasible when the battery is in use 22,23 . 4.…”

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confidence: 99%

An Incremental Voltage Difference Based Technique for Online State of Health Estimation of Li-ion Batteries

Naha

Han

Agarwal

et al. 2020

Sci Rep

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Accurate state of health (SoH) estimation of rechargeable batteries is important for the safe and reliable operation of electric vehicles (eVs), smart phones, and other battery operated systems. We propose a novel method for accurate SoH estimation which does not necessarily need full charging data. Using only partial charging data during normal usage, 10 derived voltage values (v sei) are collected. the initial v sei point is fixed and then for every 1.5% increase in the Coulomb counting, other points are selected. The difference between the v sei values (Δv sei) and the average temperature during the charging form the feature vector at different SOH levels. The training data set is prepared by extrapolating the charging voltage curves for the complete SOH range using initial 400 cycles of data. The trained artificial neural network (Ann) based on the feature vector and SoH values can be used in any battery management system (BMS) with a time complexity of only O n () 4. Less than 1% mean absolute error (MAe) for the test cases has been achieved. the proposed method has a moderate training data requirement and does not need any knowledge of previous SoH, state of charge (Soc) vs. ocV relationship, and absolute Soc value.

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

Cited by 23 publications

References 37 publications

The Effects of Gas Saturation of Electrolytes on the Performance and Durability of Lithium‐Ion Batteries

The Effects of Gas Saturation of Electrolytes on the Performance and Durability of Lithium‐Ion Batteries

An Improved Rainflow Algorithm Combined with Linear Criterion for the Accurate Li-ion Battery Residual Life Prediction

An Incremental Voltage Difference Based Technique for Online State of Health Estimation of Li-ion Batteries

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