Electrochemical Impedance Spectroscopy With Practical Rest-Times for Battery Management Applications

Messing, Marvin; Shoa, Tina; Habibi, Saeid

doi:10.1109/access.2021.3077211

Cited by 18 publications

(4 citation statements)

References 34 publications

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“…Recent advances in online EIS applications show that rest times can be considerably reduced to 5–30 min without impacting a stable response of the battery, using a methodology combining drift compensation and a Voight circuit used as a filter. [ 45 ] Alternatively, researchers have proposed different architectures for EIS data fitting to integrate complex measurement features into the battery cell, for instance, using a system composed of a vector impedance analyzer and state parameter estimation. These ongoing efforts prove that the EIS implementation challenges will be efficiently tackled in time, clearing the road for integrating our MPSM‐EIS model in the BMS of the vehicle.…”

Section: Resultsmentioning

confidence: 99%

Battery Health Diagnosis Approach Integrating Physics‐Based Modeling with Electrochemical Impedance Spectroscopy

et al. 2022

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Herein, a battery health diagnosis approach that combines electrochemical performance aging and lumped thermal models with electrochemical impedance spectroscopy and voltage monitoring is proposed, allowing the segregation and quantification of ohmic, chemical, and diffusion‐mechanical related losses. This approach accurately identifies battery lifetime thresholds such as first‐life, second‐life, and turnaround points, by combining the use of a capacity indicator and overpotentials as battery health indicators. This approach, which is demonstrated at the cell level, is scalable to module and pack levels and applicable to different cell chemistries and battery configurations. This battery health diagnosis approach is validated with performance and degradation data from lithium iron phosphate and nickel–manganese–cobalt cells, showing good agreement when comparing the predicted capacity fade against measured values.

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Section: Resultsmentioning

confidence: 99%

Battery Health Diagnosis Approach Integrating Physics‐Based Modeling with Electrochemical Impedance Spectroscopy

et al. 2022

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“…Results impact with temperature and remaining battery life. [36][37][38] Adaptive methods determine the SoH using parameters that are sensitive to battery cell degradation. These parameters must be measurable throughout battery operation.…”

Section: Advantages Disadvantages Referencesmentioning

confidence: 99%

Recurrent Neural Networks for Estimating the State of Health of Lithium-Ion Batteries

Teixeira,

Calili,

Almeida

et al. 2024

Batteries

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Rapid technological changes and disruptive innovations have resulted in a significant shift in people’s behavior and requirements. Electronic gadgets, including smartphones, notebooks, and other devices, are indispensable to everyday routines. Consequently, the demand for high-capacity batteries has surged, which has enabled extended device autonomy. An alternative approach to address this demand is battery swapping, which can potentially extend the battery life of electronic devices. Although battery sharing in electric vehicles has been well studied, smartphone applications still need to be explored. Crucially, assessing the batteries’ state of health (SoH) presents a challenge, necessitating consensus on the best estimation methods to develop effective battery swap strategies. This paper proposes a model for estimating the SoH curve of lithium-ion batteries using the state of charge curve. The model was designed for smartphone battery swap applications utilizing Gated Recurrent Unit (GRU) neural networks. To validate the model, a system was developed to conduct destructive tests on batteries and study their behavior over their lifetimes. The results demonstrated the high precision of the model in estimating the SoH of batteries under various charge and discharge parameters. The proposed approach exhibits low computational complexity, low cost, and easily measurable input parameters, making it an attractive solution for smartphone battery swap applications.

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“…To generate the current response signal, a sinusoidal voltage signal is injected into the electrode [30][31] . The impedance of the battery at that frequency can be determined by calculating the ratio of excitation voltage to response current.…”

Section: A Electrochemical Impedance Spectroscopymentioning

confidence: 99%

Technologies for Energy Storage Power Stations Safety Operation: Battery State Evaluation Survey and a Critical Analysis

Xia,

Yue,

Guo

et al. 2024

IEEE Access

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As large-scale lithium-ion battery energy storage power facilities are built, the issues of safety operations become more complex. The existing difficulties revolve around effective battery health evaluation, cell-to-cell variation evaluation, circulation, and resonance suppression, and more. Based on this, this paper first reviews battery health evaluation methods based on various methods and summarizes the selection of existing health factors in data-driven methods. Secondly, the paper discusses the new research hotspots in the existing battery state evaluation technologies from the perspectives of state evaluation using data fragments and edge computing. Thirdly, we focus and discuss on the safety operation technologies of energy storage stations, including the issues of inconsistency, balancing, circulation, and resonance. To address these issues, we present an intelligent inspection robot, enabling real-time data interaction with the EMS and fulfilling rapid inspection and real-time diagnosis. Above all, we focus on the safety operation challenges for energy storage power stations and give our views and validate them with practical engineering applications, building the foundation of the next-generation techniques that support the development of new power systems.INDEX TERMS health factor, state of health, remaining useful life; cell-to-cell variation; entropy; safety operation

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Electrochemical Impedance Spectroscopy With Practical Rest-Times for Battery Management Applications

Cited by 18 publications

References 34 publications

Battery Health Diagnosis Approach Integrating Physics‐Based Modeling with Electrochemical Impedance Spectroscopy

Battery Health Diagnosis Approach Integrating Physics‐Based Modeling with Electrochemical Impedance Spectroscopy

Recurrent Neural Networks for Estimating the State of Health of Lithium-Ion Batteries

Technologies for Energy Storage Power Stations Safety Operation: Battery State Evaluation Survey and a Critical Analysis

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