In Situ and In Operando Techniques to Study Li-Ion and Solid-State Batteries: Micro to Atomic Level

Golozar, Maryam; Gauvin, Raynald; Zaghib, Karim

doi:10.3390/inorganics9110085

Cited by 7 publications

(2 citation statements)

References 56 publications

(114 reference statements)

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“…• Crystallographic analysis using electron backscatter diffraction. • Minimal sample manipulation [207].…”

Section: X-ray Computed Tomographymentioning

confidence: 99%

Battery Reliability Assessment in Electric Vehicles: A State-of-the-Art

Omakor,

Miah,

Chaoui

2024

IEEE Access

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Lithium-ion (Li-ion) batteries are being used in electric vehicles to reduce the reliance on fossil fuels due to their high energy density, design flexibility, and efficiency compared to other battery technologies. However, they undergo complex nonlinear degradation and performance declines when abused, making their reliability crucial for effective electric vehicle performance. This survey paper presents a comprehensive review of state-of-the-art battery reliability assessments for electric vehicles. First, the operating principle of Li-ion batteries, their degradation patterns, and degradation models are briefly discussed. Afterwards, the reliability assessments of Li-ion batteries are detailed in qualitative and quantitative approaches. The qualitative approach encompasses failure modes mechanisms and effects analysis, X-ray computed tomography, and scanning electron microscopy. In contrast, quantitative approaches involve multiphysics modelling, electrochemical impedance spectroscopy, incremental capacity and differential voltage analysis, machine learning, and transfer learning. Each technique is examined in terms of its principles, advantages, limitations, and applicability in Li-ion batteries for electric vehicles. Comparative analysis reveals that qualitative methods are primarily used in early design stages to assess potential risks and in post-mortem battery analysis in the laboratory, while quantitative techniques such as machine learning and transfer learning offer real-time prognostic health management and anomaly prevention. Also, the quantitative techniques tend to be more cost-effective compared to their counterparts. The potential for consolidating reliability methods through standardization of testing protocols, real-world data integration, controller area network use, and policy regulation are highlighted to guide further research.INDEX TERMS Capacity fade, causes of failure, data-driven, degradation trajectory, electric vehicle, electrochemical impedance spectroscopy, failure modes mechanisms and effects analysis, incremental capacity and differential voltage analysis, Li-ion batteries, machine learning, model-based, power fade, qualitative analysis, quantitative analysis, remaining useful life, reliability, state of health, state of charge, transfer learning, X-ray computed tomography.

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“…• Crystallographic analysis using electron backscatter diffraction. • Minimal sample manipulation [207].…”

Section: X-ray Computed Tomographymentioning

confidence: 99%

Battery Reliability Assessment in Electric Vehicles: A State-of-the-Art

Omakor,

Miah,

Chaoui

2024

IEEE Access

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“…Currently, common detection methods for lithium-ion batteries include disassembly characterization methods and in-situ characterization methods. Disassembly methods, such as scanning electron microscopy (SEM) 7 , 8 , provide rich information about battery material properties. However, they may alter the internal structure during disassembly, leading to less accurate information.…”

Section: Introductionmentioning

confidence: 99%

Three-dimensional electrochemical-magnetic-thermal coupling model for lithium-ion batteries and its application in battery health monitoring and fault diagnosis

Bai,

Peng,

Chen

et al. 2024

Sci Rep

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Storage batteries with elevated energy density, superior safety and economic costs continues to escalate. Batteries can pose safety hazards due to internal short circuits, open circuits and other malfunctions during usage, hence real-time surveillance and error diagnosis of the battery’s operational state is imperative. In this paper, a three-dimensional model of electrochemical-magnetic field-thermal coupling is formulated with lithium-ion pouch cells as the research focus, and the spatial distribution pattern of the physical field such as magnetic field and temperature when the battery is operational is acquired. Furthermore, this manuscript also investigates the diagnostic methodology for defective batteries with internal short circuits and fissures, that is, the operational state of the battery is evaluated and diagnosed by the distribution of the magnetic field surrounding the battery. To substantiate the method’s practical viability, the present study extends its examination to the 18650-battery pack. We obtained the magnetic field images of the normal operation of the battery pack and the failure state of some batteries and analyzed the relationship between the magnetic field distribution characteristics and the performance of the battery pack, providing a new method for the health monitoring and fault diagnosis of the battery pack. This non-contact method incurs no damage to the battery, concurrently exhibiting elevated sensitivity and extremely rapid response time. Meanwhile, it provides an effective means for non-destructive research on the batteries and can be applied to areas such as battery safety screening and non-destructive testing. This research not only helps to facilitate our understanding of the battery’s operating mechanism, but also provides robust support for safe operation and optimal battery design.

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Sustainable Graphene Quantum Dots (GQDs) as an Electrolyte Additive for Zinc-Air Battery System

Brindha

Ramakrishna

2023

Mater Circ Econ

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In Situ and In Operando Techniques to Study Li-Ion and Solid-State Batteries: Micro to Atomic Level

Cited by 7 publications

References 56 publications

Battery Reliability Assessment in Electric Vehicles: A State-of-the-Art

Battery Reliability Assessment in Electric Vehicles: A State-of-the-Art

Three-dimensional electrochemical-magnetic-thermal coupling model for lithium-ion batteries and its application in battery health monitoring and fault diagnosis

Sustainable Graphene Quantum Dots (GQDs) as an Electrolyte Additive for Zinc-Air Battery System

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