Advances in Thermal Energy Storage in Fire Prevention and Control

A special issue of Fire (ISSN 2571-6255).

Deadline for manuscript submissions: 31 December 2024 | Viewed by 1836

Special Issue Editor


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Guest Editor
Facultatea de Inginerie, Universitatea "Constantin Brâncuşi" din Târgu Jiu, Târgu Jiu, Romania
Interests: spontaneous heating; lignite; stock pile; energy services company; energy efficiency project; calorific value; storage period

Special Issue Information

Dear Colleagues,

Thermal energy storage in fire protection is a relatively new research direction with a limited number of applications, such as the prevention of thermal runaway in Li-ion batteries. Thermal energy storage limits the temperature increase which occurs during the fire inception period. This has the potential to reduce the exposure of materials to high temperatures and delays fire propagation. The attenuation of temperature spikes achieved by employing thermal energy storage can contribute even more considerably to fire protection, preventing the material from reaching the ignition point. In applications with temperature fluctuations and spikes, thermal energy storage offers more flexibility in the system design parameters.

Although thermal storage plays a limited role in fire protection, it can be regarded as a complimentary fire protection measure, which, in some instances, can make the difference between failure to prevent a fire from igniting and propagating and preventing it.

This Special Issue welcomes submissions which feature recent studies on thermal energy storage in any form (sensible, latent heat, thermo-chemical storage) with applicability to fire protection. The range of applications is not limited, but submissions related to electrical vehicles technology, fire protection in buildings, and in critical industrial applications are especially encouraged. In parallel, studies related to improving the fire retardance of thermal energy storage materials are welcomed.

  • Fire protection for construction materials integrating thermal energy storage in various forms.
  • Li-ion batteries thermal runaway control and protection.
  • Fire control in critical (industrial/civil) infrastructures employing thermal energy storage.
  • Materials for thermal energy storage: flammability, degradation under exposure to fire, fire retardance.

Research articles are especially encouraged for this Special Issue. Comprehensive reviews on recent and emerging topics are also welcome. Non-conventional and modern approaches such as AI systems will be prioritized.

Prof. Dr. Bogdan Diaconu
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. Fire 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 2400 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

  • thermal energy storage
  • phase change material
  • flame retardance
  • fire protection
  • fire propagation
  • fire suppression
  • thermal runaway
  • electrical vehicle
  • critical infrastructure

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Published Papers (1 paper)

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Research

21 pages, 4122 KiB  
Article
Enhancing Fire Protection in Electric Vehicle Batteries Based on Thermal Energy Storage Systems Using Machine Learning and Feature Engineering
by Mahmoud M. Kiasari and Hamed H. Aly
Fire 2024, 7(9), 296; https://doi.org/10.3390/fire7090296 - 23 Aug 2024
Cited by 1 | Viewed by 1391
Abstract
Thermal Energy Storage (TES) plays a pivotal role in the fire protection of Li-ion batteries, especially for the high-voltage (HV) battery systems in Electrical Vehicles (EVs). This study covers the application of TES in mitigating thermal runaway risks during different battery charging/discharging conditions [...] Read more.
Thermal Energy Storage (TES) plays a pivotal role in the fire protection of Li-ion batteries, especially for the high-voltage (HV) battery systems in Electrical Vehicles (EVs). This study covers the application of TES in mitigating thermal runaway risks during different battery charging/discharging conditions known as Vehicle-to-grid (V2G) and Grid-to-vehicle (G2V). Through controlled simulations in Simulink, this research models real-world scenarios to analyze the effectiveness of TES in controlling battery conditions under various environmental conditions. This study also integrates Machine Learning (ML) techniques to utilize the produced data by the simulation model and to predict any probable thermal spikes and enhance the system reliability, focusing on crucial factors like battery temperature, current, or State of charge (SoC). Feature engineering is also employed to identify the key parameters among all features that are considered for this study. For a broad comparison among different models, three different ML techniques, logistic regression, support vector machine (SVM), and Naïve Bayes, have been used alongside their hybrid combination to determine the most accurate one for the related topic. This study concludes that SoC is the most significant factor affecting thermal management while grid power consumption has the least impact. Additionally, the findings demonstrate that logistic regression outperforms other methods, with the improving feature to be used in the hybrid models as it can increase their efficiency due to its linearity capture capability. Full article
(This article belongs to the Special Issue Advances in Thermal Energy Storage in Fire Prevention and Control)
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