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Batteries
Special Issues
Battery Aging Diagnosis and Prognosis
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Battery Aging Diagnosis and Prognosis

A special issue of Batteries (ISSN 2313-0105). This special issue belongs to the section "Battery Performance, Ageing, Reliability and Safety".

Deadline for manuscript submissions: closed (20 April 2024) | Viewed by 17974

Special Issue Editor

Dr. Xiaolei Bian

E-Mail Website
Guest Editor
Department of Electrical Engineering, Chalmers University of Technology, 41296 Gothenburg, Sweden
Interests: energy storage; lithium-ion batteries; battery modeling; advanced sensing; battery health and safety; intelligent and smart BMS; battery fast charging

Special Issue Information

Dear Colleagues,

Batteries have become vital in our tech-driven world, powering everything from portable electronics and electrical vehicles to massive grid storage systems. Yet, as they become more common, the challenge of battery aging becomes more urgent. This Special Issue is devoted to exploring the multifaceted aspects of battery lifespan and degradation. It seeks to explore the underlying mechanisms of aging, showcase advanced diagnostic methodologies, and reveal predictive techniques that can anticipate a battery’s future health trajectory. By emphasizing both diagnostic and prognostic methodologies, this Special Issue aims to bring forth innovative strategies that extend the lifespan of batteries, and enhance their safety and efficiency. By considering research with various practical applications, it aims to present a comprehensive overview that could shape the next wave of advancements in battery technology and management.

Potential topics include, but are not limited to, the following:

  • Advanced diagnostic techniques for battery aging assessment.
  • Machine learning and AI for battery lifetime or aging knee prediction.
  • State of health, state of charge, state of power, and state of energy estimation.
  • Novel sensors for battery aging monitoring and prediction.
  • Case studies about battery aging or aging patterns in real applications, e.g., electric vehicles and grid storage systems.
  • Battery management strategies to mitigate battery aging.
  • The socio-economic impact of battery lifespan extension.
  • Solid-state batteries: aging behavior and diagnostics.
  • Battery aging in fast-charging scenarios.
  • Mechanisms of battery degradation.

Dr. Xiaolei Bian
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Batteries is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • aging diagnostic techniques
  • lifetime and aging knee prediction
  • machine learning and AI
  • battery state estimation
  • novel sensors
  • battery aging mechanisms
  • solid-state batteries
  • fast charging
  • socio-economic impact

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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Research

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16 pages, 5755 KiB  
Article
Evaluating Frequency Domain Reflectometry as a Tool for Lithium-Ion Battery Health Prognosis
by Ama Baduba Asiedu-Asante, Volker Pickert, Mohamed Mamlouk and Charalampos Tsimenidis
Batteries 2024, 10(6), 185; https://doi.org/10.3390/batteries10060185 - 28 May 2024
Cited by 1 | Viewed by 1558
Abstract
Monitoring battery aging is crucial for maintaining reliability and performance. This study investigates Frequency Domain Reflectometry (FDR) as a tool for monitoring lithium-ion battery State-of-Health (SoH). While FDR has been applied in battery research, the existing literature fails to address SoH assessment and [...] Read more.
Monitoring battery aging is crucial for maintaining reliability and performance. This study investigates Frequency Domain Reflectometry (FDR) as a tool for monitoring lithium-ion battery State-of-Health (SoH). While FDR has been applied in battery research, the existing literature fails to address SoH assessment and lacks studies on larger battery samples to provide more meaningful results. In this work, nineteen cells initially underwent Electrochemical Impedance Spectroscopy (EIS) to assess their degradation levels during cyclic aging. This work evaluates FDR’s effectiveness in monitoring battery health indicators, such as capacity and equivalent series resistance (ESR), by correlating these with FDR-measured impedance between 300 kHz and 1 GHz. Analytical comparison between impedance measured before and after de-embedding processes were presented. The results show FDR reactance within 300 kHz–40 MHz correlates with EIS-measured ESR, suggesting its potential as a SoH indicator. However, reduced sensitivity and accuracy, particularly after de-embedding, may limit practical applicability. Additionally, resonance-based analysis was conducted to explore the relationship between changes in circuit resonance and cell dielectric permittivity. Despite having the lowest sensitivity, the method showed that the resonance frequencies of cells remain relatively constant, mirroring behaviours associated with changes in resistive properties. Overall, this study provides insights into FDR’s potential for battery diagnostics while highlighting avenues for future research to enhance effectiveness in real-world scenarios. Full article
(This article belongs to the Special Issue Battery Aging Diagnosis and Prognosis)
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12 pages, 2463 KiB  
Article
Study of 10 kW Vanadium Flow Battery Discharge Characteristics at Different Load Powers
by Ilia Rashitov, Aleksandr Voropay, Grigoriy Tsepilov, Ivan Kuzmin, Alexey Loskutov, Evgeny Osetrov, Andrey Kurkin and Ivan Lipuzhin
Batteries 2024, 10(6), 175; https://doi.org/10.3390/batteries10060175 - 24 May 2024
Cited by 1 | Viewed by 1631
Abstract
Vanadium redox flow batteries are promising energy storage devices and are already ahead of lead–acid batteries in terms of installed capacity in energy systems due to their long service life and possibility of recycling. One of the crucial tasks today is the development [...] Read more.
Vanadium redox flow batteries are promising energy storage devices and are already ahead of lead–acid batteries in terms of installed capacity in energy systems due to their long service life and possibility of recycling. One of the crucial tasks today is the development of models for assessing battery performance and its residual resource based on the battery’s present state. A promising method for estimating battery capacity is based on analyzing present voltage and current values under various load conditions. This paper analyzes the discharge characteristics of a 10 kW all-vanadium redox flow battery at fixed load powers from 6 to 12 kW. A linear dependence of operating voltage and initial discharge voltage on load power is established. It is also determined that the slope of the discharge curve linear section does not increase linearly in absolute value, and the Box–Lucas model can be used to describe it. Models for predicting current VRFB capacity based on different curve fitting functions are proposed. These models can be used to roughly estimate battery capacity at different load powers. Full article
(This article belongs to the Special Issue Battery Aging Diagnosis and Prognosis)
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Review

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34 pages, 4228 KiB  
Review
Exploring Lithium-Ion Battery Degradation: A Concise Review of Critical Factors, Impacts, Data-Driven Degradation Estimation Techniques, and Sustainable Directions for Energy Storage Systems
by Tuhibur Rahman and Talal Alharbi
Batteries 2024, 10(7), 220; https://doi.org/10.3390/batteries10070220 - 22 Jun 2024
Cited by 28 | Viewed by 14088
Abstract
Batteries play a crucial role in the domain of energy storage systems and electric vehicles by enabling energy resilience, promoting renewable integration, and driving the advancement of eco-friendly mobility. However, the degradation of batteries over time remains a significant challenge. This paper presents [...] Read more.
Batteries play a crucial role in the domain of energy storage systems and electric vehicles by enabling energy resilience, promoting renewable integration, and driving the advancement of eco-friendly mobility. However, the degradation of batteries over time remains a significant challenge. This paper presents a comprehensive review aimed at investigating the intricate phenomenon of battery degradation within the realm of sustainable energy storage systems and electric vehicles (EVs). This review consolidates current knowledge on the diverse array of factors influencing battery degradation mechanisms, encompassing thermal stresses, cycling patterns, chemical reactions, and environmental conditions. The key degradation factors of lithium-ion batteries such as electrolyte breakdown, cycling, temperature, calendar aging, and depth of discharge are thoroughly discussed. Along with the key degradation factor, the impacts of these factors on lithium-ion batteries including capacity fade, reduction in energy density, increase in internal resistance, and reduction in overall efficiency have also been highlighted throughout the paper. Additionally, the data-driven approaches of battery degradation estimation have taken into consideration. Furthermore, this paper delves into the multifaceted impacts of battery degradation on the performance, longevity, and overall sustainability of energy storage systems and EVs. Finally, the main drawbacks, issues and challenges related to the lifespan of batteries are addressed. Recommendations, best practices, and future directions are also provided to overcome the battery degradation issues towards sustainable energy storage system. Full article
(This article belongs to the Special Issue Battery Aging Diagnosis and Prognosis)
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