Correlation between capacity and impedance of lithium-ion cells during calendar and cycle life

Schuster, Simon F.; Brand, Martin J.; Campestrini, Christian; Gleissenberger, Markus; Jossen, Andreas

doi:10.1016/j.jpowsour.2015.11.096

Cited by 97 publications

(50 citation statements)

References 48 publications

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“…In addition to determining the cost, safety, specific energy, power, and reliability issues, lifetime prediction for LIBs under real operating conditions is a major step for dependable integration of LIBs into vehicles and stationary applications and to eliminate warranty issues. Accelerated aging tests have been regarded as a powerful alternative to replace the cost‐ and time‐intensive aging tests under real‐life operating conditions . However, many experiments still needs to be performed to obtain the maximum operating conditions at which the aging test can be conducted without altering the decay mechanisms.…”

Section: Introductionsupporting

confidence: 71%

Time‐Effective Accelerated Cyclic Aging Analysis of Lithium‐Ion Batteries

et al. 2019

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We propose a time-effective framework for accelerated cyclic aging analysis of lithium-ion batteries. The proposed framework involves the coupling of a physico-chemical capacity-fade model that considers the cyclic aging mechanisms of the LiMn 2 O 4 /graphite cell, with a physics-based porous-composite electrode model to predict cycling performance at different temperatures. A one-dimensional simple empirical life model is then developed from the coupled physico-chemical capacityfade model and the physics-based porous-composite electrode model predictions. An accelerated cyclic aging analysis based on the principle of time-temperature superposition is performed using the developed one-dimensional simple life empirical model. The proposed framework is used to predict the maximum number of cycles and the highest temperature required for accelerated cyclic aging analysis of LiMn 2 O 4 /graphite cells. The efficacy of the proposed framework is validated with experimental cycle-performance data obtained from LiMn 2 O 4 /graphite coin cells at 25 and 60°C.

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Section: Introductionsupporting

confidence: 71%

Time‐Effective Accelerated Cyclic Aging Analysis of Lithium‐Ion Batteries

et al. 2019

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“…A number of publications discuss the need to quantify the energy capacity within a battery cell [31][32][33][34] as a fundamental stage of assessing the appropriate EOL strategy for the battery, as discussed within the previous section, or for defining the battery SOC or SOH as part of the on-line 13 management of the battery system within an automotive [35] or grid storage application [36]. the challenge of measuring capacity retention is discussed within the context of cells subject to cyclic electrical loading [32] and those that experience capacity fade due to extended periods of storage [31].…”

Section: Review Of Academic Literaturementioning

confidence: 99%

“…the challenge of measuring capacity retention is discussed within the context of cells subject to cyclic electrical loading [32] and those that experience capacity fade due to extended periods of storage [31]. Within [37] the authors highlight the different terms often employed for describing battery capacity, they include: nominal capacity, initial capacity or actual capacity.…”

Section: Review Of Academic Literaturementioning

confidence: 99%

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Accelerated energy capacity measurement of lithium-ion cells to support future circular economy strategies for electric vehicles

Groenewald

Grandjean

Marco

2017

Renewable and Sustainable Energy Reviews

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Within the academic and industrial communities there has been an increasing desire to better understand the sustainability of producing vehicles that contain embedded electrochemical energy storage. Underpinning a number of studies that evaluate different circular economy strategies for the electric vehicle (EV) or Hybrid electric vehicle (HEV) battery system are implicit assumptions about the retained capacity or State of Health (SOH) of the battery. International standards and best-practice guides exist that address the performance evaluation of both EV and HEV battery systems. However, a common theme is that the test duration can be excessive and last for a number of hours. The aim of this research is to assess whether energy capacity measurements of Li-ion cells can be accelerated; reducing the test duration to a value that may facilitate further EOL options. Experimental results are presented that highlight it is possible to significantly reduce the duration of the battery characterisation test by 70% -90% while still retaining levels of measurement accuracy for retained energy capacity in the order of 1% for cell temperatures equal to 25 0 C. Even at elevated temperatures of 40 0 C, the peak measurement error was found to be only 3%. Based on these experimental results, a simple cost-function is formulated to highlight the flexibility of the proposed test framework. This approach would allow different organizations to prioritize the relative importance of test accuracy verses experimental test time when grading used Li-ion cells for different end-of-life (EOL) applications.

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“…Due to their unique advantages in energy/power density and cycle life, rechargeable lithium-ion batteries (LIBs) are preferred in energy storage devices for most applications in portable electronics, electric vehicles (EV) and grid energy storage [1][2][3]. In order to ensure the reliable and safe operation of LIBs, accurate online estimation of battery states, including state of charge (SOC) [4][5][6], state of health (SOH) [7][8][9] and state of energy (SOE) [10][11][12], is the most crucial task for a battery management system (BMS).…”

Section: Introductionmentioning

confidence: 99%

Rapid Prediction of the Open-Circuit-Voltage of Lithium Ion Batteries Based on an Effective Voltage Relaxation Model

Yang

Wang³

et al. 2018

Energies

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The open circuit voltage of lithium ion batteries in equilibrium state, as a vital thermodynamic characteristic parameter, is extensively studied for battery state estimation and management. However, the time-consuming relaxation process, usually for several hours or more, seriously hinders the widespread application of open circuit voltage. In this paper, a novel voltage relaxation model is proposed to predict the final open circuit voltage when the lithium ion batteries are in equilibrium state with a small amount of sample data in the first few minutes, based on the concentration polarization theory. The Nernst equation is introduced to describe the evolution of relaxation voltage. The accuracy and effectiveness of the model are verified using experimental data on lithium ion batteries with different kinds of electrodes (LiCoO2/mesocarbon-microbead and LiFePO4/graphite) under different working conditions. The validation results show that the presented model can fit the experimental results very well and the predicted values are quite accurate by taking only 5 min or less. The satisfying results suggest that the introduction of concentration polarization theory might provide researchers an alternative model form to establish voltage relaxation models.

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Correlation between capacity and impedance of lithium-ion cells during calendar and cycle life

Cited by 97 publications

References 48 publications

Time‐Effective Accelerated Cyclic Aging Analysis of Lithium‐Ion Batteries

Time‐Effective Accelerated Cyclic Aging Analysis of Lithium‐Ion Batteries

Accelerated energy capacity measurement of lithium-ion cells to support future circular economy strategies for electric vehicles

Rapid Prediction of the Open-Circuit-Voltage of Lithium Ion Batteries Based on an Effective Voltage Relaxation Model

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