Challenges of second-life concepts for retired electric vehicle batteries

Börner, Martin F.; Frieges, Moritz; Späth, Benedikt; Spütz, Kathrin; Heimes, Heiner Hans; Sauer, Dirk Uwe; Li, Weihan

doi:10.1016/j.xcrp.2022.101095

Cited by 38 publications

(19 citation statements)

References 49 publications

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“…Usually, 80% SoH is considered end‐of‐life for first‐life applications of commercial cells. [ 26–27 ] Nonetheless, NMC811||AG+20% SiO x pouch cells operating in a voltage range between 4.5 V to 2.8 V with BE already fail at 92% SoH, as shown in Figure 2e. Moreover, only a maximum of 43 Wh g −1 accumulated specific energy can be drawn from the cells containing BE until 80% SoH.…”

Section: Resultsmentioning

confidence: 98%

Mechanistic Understanding of Additive Reductive Degradation and SEI Formation in High‐Voltage NMC811||SiO_x‐Containing Cells via Operando ATR‐FTIR Spectroscopy

Weiling,

Lechtenfeld,

Pfeiffer

et al. 2023

Advanced Energy Materials

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The implementation of silicon (Si)‐containing negative electrodes is widely discussed as an approach to increase the specific capacity of lithium‐ion batteries. However, challenges caused by severe volume changes and continuous (re‐)formation of the solid‐electrolyte interphase (SEI) on Si need to be overcome. The volume changes lead to electrolyte consumption and active lithium loss, decaying the cell performance and cycle life. Herein, the additive 2‐sulfobenzoic acid anhydride (2‐SBA) is utilized as an SEI‐forming electrolyte additive for SiOx‐containing anodes. The addition of 2‐SBA to a state‐of‐the‐art carbonate‐based electrolyte in high‐voltage LiNi0.8Mn0.1Co0.1O2, NMC811||artificial graphite +20% SiOx pouch cells leads to improved electrochemical performance, resulting in a doubled cell cycle life. The origin of the enhanced cell performance is mechanistically investigated by developing an advanced experimental technique based on operando attenuated total reflection Fourier‐transform infrared (ATR‐FTIR) spectroscopy. The operando ATR‐FTIR spectroscopy results elucidate the degradation mechanism via anhydride ring‐opening reactions after electrochemical reduction on the anode surface. Additionally, ion chromatography conductivity detection mass spectrometry, scanning electron microscopy, energy dispersive X‐ray analysis, and quantum chemistry calculations are employed to further elucidate the working mechanisms of the additive and its degradation products.

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Section: Resultsmentioning

confidence: 98%

Mechanistic Understanding of Additive Reductive Degradation and SEI Formation in High‐Voltage NMC811||SiO_x‐Containing Cells via Operando ATR‐FTIR Spectroscopy

Weiling,

Lechtenfeld,

Pfeiffer

et al. 2023

Advanced Energy Materials

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“…1 With the increasing use of LIBs, diagnostic techniques to evaluate state of health (SOH) of these batteries are required to predict and prevent abnormal battery operation. [2][3][4] lots of non-invasive methods to evaluate SOH of LIBs have been studied, such as pseudo open circuit voltage (pOCV), incremental capacity-differential voltage (IC-DV), 5,6 differential thermal voltammetry measurements (DTV), [7][8][9] and electrochemical impedance spectroscopy (EIS). 10 Commercial LIBs are complex systems, typically consist of a cathode, an anode, current collectors, a separator, and all wetted by the electrolyte.…”

Section: List Of Symbolsmentioning

confidence: 99%

Degradation Diagnosis of Li(Ni_0.5Mn_0.2Co_0.3)O₂/Li Half-cell by Identifying Physical Parameter Evolution Profile Using Impedance Spectra During Cycling

Duan

Liu

Ağar

et al. 2023

J. Electrochem. Soc.

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Electrochemical impedance spectroscopy (EIS) is considered a quick and nondestructive diagnostic tool to characterize the degradation of lithium-ion batteries within a short testing timeframe. In this study, to obtain the relationship between EIS spectra and cell capacity degradation, our previously reported physics-based EIS model is further utilized to interpret EIS spectra of Li-NMC(5:2:3) half-cell measured under cycling. The EIS spectra show that the polarization impedance (Rp) increases with the number of cycles under different open circuit voltages (OCVs), especially in the mid-frequency range. After interpreting EIS spectra by the physics-based model, we found that the diffusion coefficient, ionic conductivity, and cathode reaction rate at different OCVs all decrease with the number of cycles. The impedance variation caused by the change of cathode reaction rate during cycles is much more significant than that caused by the other two parameters. Furthermore, the cell capacity degradation is linearly related to the resistance Rct caused by cathode/electrolyte interface reaction rate at specific OCVs and it could serve as the indicator of cell capacity fade beyond 10 cycles.

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“…Another shortcoming of the existing methods is that they do not address the MBSE approach: there is no link to the parameters of the functional architecture and requirements, and, therefore, the data are not centrally organized. However, to master the complexity of complex systems, such as a multi-life battery system, using MBSE is mandatory [27]. MBSE relies on three main pillars: method, language and tool.…”

Section: State Of the Artmentioning

confidence: 99%

Automated Identification of Valid Model Networks Using Model-Based Systems Engineering

Berges

Spütz

Jacobs

et al. 2022

Systems

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To handle increasing complexity in product development, model-based systems engineering (MBSE) approaches are well suited, in which the technical system is represented in a system model. To efficiently test requirements, domain models are integrated into the system model. For each purpose (e.g., battery lifetime calculation), there are typically several models at several fidelity levels. Since the model signatures (i.e., necessary inputs for the models and their outputs) differ depending on the fidelity level, not all models can be used in any development phase. In addition, due to the different model signatures, not all models can be combined arbitrarily to model networks. Currently, valid model networks in system models must be determined in a time-consuming, manual process. Therefore, this paper presents an approach that automates this task via the implementation of an algorithm that analyzes a system model and the model signatures and automatically returns all valid model networks. When input parameters, models or their signatures change, the algorithm updates automatically, and the user receives the valid model network without any manual effort. The approach is demonstrated with the running example of battery system development.

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Challenges of second-life concepts for retired electric vehicle batteries

Cited by 38 publications

References 49 publications

Mechanistic Understanding of Additive Reductive Degradation and SEI Formation in High‐Voltage NMC811||SiO_x‐Containing Cells via Operando ATR‐FTIR Spectroscopy

Mechanistic Understanding of Additive Reductive Degradation and SEI Formation in High‐Voltage NMC811||SiO_x‐Containing Cells via Operando ATR‐FTIR Spectroscopy

Degradation Diagnosis of Li(Ni_0.5Mn_0.2Co_0.3)O₂/Li Half-cell by Identifying Physical Parameter Evolution Profile Using Impedance Spectra During Cycling

Automated Identification of Valid Model Networks Using Model-Based Systems Engineering

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Challenges of second-life concepts for retired electric vehicle batteries

Cited by 38 publications

References 49 publications

Mechanistic Understanding of Additive Reductive Degradation and SEI Formation in High‐Voltage NMC811||SiOx‐Containing Cells via Operando ATR‐FTIR Spectroscopy

Mechanistic Understanding of Additive Reductive Degradation and SEI Formation in High‐Voltage NMC811||SiOx‐Containing Cells via Operando ATR‐FTIR Spectroscopy

Degradation Diagnosis of Li(Ni0.5Mn0.2Co0.3)O2/Li Half-cell by Identifying Physical Parameter Evolution Profile Using Impedance Spectra During Cycling

Automated Identification of Valid Model Networks Using Model-Based Systems Engineering

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Product

Resources

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Mechanistic Understanding of Additive Reductive Degradation and SEI Formation in High‐Voltage NMC811||SiO_x‐Containing Cells via Operando ATR‐FTIR Spectroscopy

Mechanistic Understanding of Additive Reductive Degradation and SEI Formation in High‐Voltage NMC811||SiO_x‐Containing Cells via Operando ATR‐FTIR Spectroscopy

Degradation Diagnosis of Li(Ni_0.5Mn_0.2Co_0.3)O₂/Li Half-cell by Identifying Physical Parameter Evolution Profile Using Impedance Spectra During Cycling