Enhancement of Lithium-Ion and Post-lithium Batteries Safety: Fundamentals, Materials and Applications

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: 20 December 2024 | Viewed by 3277

Special Issue Editors


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Guest Editor
Head of Institute for Applied Materials (IAM-AWP), Karlsruhe Institute for Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany
Interests: battery

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Guest Editor
Group Leader Batteries—Calorimetry and Safety, Institute for Applied Materials-Applied Materials Physics (IAM-AWP), Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany
Interests: lithium and post-lithium-ion batteries; battery calorimetry; thermal characterization of materials/cells/batteries; safety testing; thermal management; multiscale electric, electrochemical, and thermal modeling of cells and batteries
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Special Issue Information

Dear Colleagues,

Novel materials that are cheaper, safer and more sustainable for lithium batteries and their technology concepts are urgently required for the decarbonization of the energy system and the extensive market penetration of electric vehicles and stationary storage systems. Additionally, so-called post-lithium batteries based on, for example, sodium or magnesium ions, which no longer rely on lithium, are promising alternatives that offer significant potential. Therefore, the characterization of the electrochemical, thermal and safety properties of the cells and their individual active and passive materials are required to obtain quantitative and reliable data, which are needed to enhance our current understanding of this technology and design and develop superior and safer materials and cells. This Special Issue addresses all the techniques that are necessary for a holistic safety assessment of these batteries, from the materials to the cell and the application of lithium-ion and post-lithium batteries. We warmly invite you to submit your original research or review articles to this Special Issue. Potential topics include, but are not limited to, the following:

  • Electrochemical characterization techniques (galvanostatic cycling, PITT, GITT, CIT, CV, EIS, entropymetry);
  • Thermal characterization techniques (DSC, DTA, TG, drop solution calorimetry, battery calorimetry, laser flash, hot-plate, thermography,…) for materials and cells;
  • Safety testing (mechanical, electrical, thermal abuse);
  • Ageing studies;
  • Analysis of battery gases;
  • Development of safer materials and cell designs;
  • Thermodynamic modelling of materials (e.g., CALPHAD, ab initio, kinetic modelling) and database generation;
  • Modelling of cell venting, thermal runaway and thermal propagation.

Share your results in this Special Issue to provide a deeper understanding of the electrochemical and thermal processes taking place in these batteries under both normal use and abuse conditions. This will be an important milestone that sees an increase in their safety and the exploitation of their full potential.

Prof. Dr. Hans Jürgen Seifert
Dr. Carlos Ziebert
Guest Editors

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

  • lithium and post-lithium batteries safety
  • electrochemical and thermal characterization
  • battery calorimetry and safety testing
  • ageing studies
  • gas analysis
  • thermodynamic modelling
  • modelling of cell venting, thermal runaway and thermal propagation

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Published Papers (1 paper)

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Review

43 pages, 6707 KiB  
Review
Recent Progress of Deep Learning Methods for Health Monitoring of Lithium-Ion Batteries
by Seyed Saeed Madani, Carlos Ziebert, Parisa Vahdatkhah and Sayed Khatiboleslam Sadrnezhaad
Batteries 2024, 10(6), 204; https://doi.org/10.3390/batteries10060204 - 13 Jun 2024
Cited by 2 | Viewed by 2624
Abstract
In recent years, the rapid evolution of transportation electrification has been propelled by the widespread adoption of lithium-ion batteries (LIBs) as the primary energy storage solution. The critical need to ensure the safe and efficient operation of these LIBs has positioned battery management [...] Read more.
In recent years, the rapid evolution of transportation electrification has been propelled by the widespread adoption of lithium-ion batteries (LIBs) as the primary energy storage solution. The critical need to ensure the safe and efficient operation of these LIBs has positioned battery management systems (BMS) as pivotal components in this landscape. Among the various BMS functions, state and temperature monitoring emerge as paramount for intelligent LIB management. This review focuses on two key aspects of LIB health management: the accurate prediction of the state of health (SOH) and the estimation of remaining useful life (RUL). Achieving precise SOH predictions not only extends the lifespan of LIBs but also offers invaluable insights for optimizing battery usage. Additionally, accurate RUL estimation is essential for efficient battery management and state estimation, especially as the demand for electric vehicles continues to surge. The review highlights the significance of machine learning (ML) techniques in enhancing LIB state predictions while simultaneously reducing computational complexity. By delving into the current state of research in this field, the review aims to elucidate promising future avenues for leveraging ML in the context of LIBs. Notably, it underscores the increasing necessity for advanced RUL prediction techniques and their role in addressing the challenges associated with the burgeoning demand for electric vehicles. This comprehensive review identifies existing challenges and proposes a structured framework to overcome these obstacles, emphasizing the development of machine-learning applications tailored specifically for rechargeable LIBs. The integration of artificial intelligence (AI) technologies in this endeavor is pivotal, as researchers aspire to expedite advancements in battery performance and overcome present limitations associated with LIBs. In adopting a symmetrical approach, ML harmonizes with battery management, contributing significantly to the sustainable progress of transportation electrification. This study provides a concise overview of the literature, offering insights into the current state, future prospects, and challenges in utilizing ML techniques for lithium-ion battery health monitoring. Full article
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