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Advances in Battery Modelling, Applications, and Technology

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "D: Energy Storage and Application".

Deadline for manuscript submissions: 20 April 2026 | Viewed by 242

Special Issue Editors


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Guest Editor
Department of Electronics, Information and Bioengineering, Politecnico di Milano, 20133 Milan, Italy
Interests: circuits and systems; theory and applications; power electronic converters and energy storage systems
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Electronics, Information and Bioengineering, Politecnico di Milano, 20133 Milan, Italy
Interests: electric engineering; electro-thermal circuit modeling and simulation; electromagnetic simulation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Batteries, among various energy storage systems, have garnered attention not only in stationary applications but also in a wide range of mobile applications, spanning from small devices such as smartphones, notebooks, and tablets to larger ones such as electric vehicles and railway traction systems. Over the years, different technologies, such as lead–acid and lithium–ion technologies, have been developed, and ongoing research explores novel technologies. Enhancing the lifecycle involves exploring innovative technologies in battery construction and/or optimizing their operational conditions. Achieving this requires a profound understanding of battery modelling and parameter estimation. Battery modelling can encompass various aspects, including chemical, electrical, thermal, or aging factors, or a combination of these. These models can be implemented in battery management systems, which can properly control the battery operating conditions, ensuring batteries work inside their safe and optimal operating range, limit their degradation, and increase their performance. In particular, the management of the thermal aspect of batteries is crucial for preventing overtemperatures, limiting temperature degradation and possible consequential thermal runaway. The latter can be very dangerous as it can lead to combustion and explosions. Moreover, the thermal battery management system can be useful for balancing the temperature among different battery cells or modules. This way, it is possible to equalize the thermal stress among cells/modules, ensuring the uniform degradation and efficiency of the individual cells/modules.

In light of the above, the scope of this Special Issue is to collect both original research works and review articles on battery models, with a particular focus on the thermal aspect, and their optimized control through battery management systems.

Dr. Simone Barcellona
Prof. Dr. Lorenzo Codecasa
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 250 words) can be sent to the Editorial Office for assessment.

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. Energies is an international peer-reviewed open access semimonthly 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 2600 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

  • energy storage systems
  • battery technologies
  • battery applications
  • battery modelling (chemical, electrical, thermal, aging models)
  • parameter estimation techniques

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Published Papers (1 paper)

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Research

12 pages, 3631 KB  
Article
A Study on the Lithium-Ion Battery Fire Prevention Diagnostic Technique Based on Time-Resolved Partial Discharge Algorithm
by Wen-Cheng Jin, Chang-Won Kang, Soon-Hyung Lee, Kyung-Min Lee and Yong-Sung Choi
Energies 2025, 18(24), 6510; https://doi.org/10.3390/en18246510 - 12 Dec 2025
Viewed by 158
Abstract
Lithium-ion batteries are extensively employed in electric vehicles (EVs) and energy storage systems (ESSs) owing to their high energy density, long cyclability, and cost-effectiveness. However, the use of flammable electrolytes makes them inherently susceptible to thermal runaway (TR), which can lead to ignition, [...] Read more.
Lithium-ion batteries are extensively employed in electric vehicles (EVs) and energy storage systems (ESSs) owing to their high energy density, long cyclability, and cost-effectiveness. However, the use of flammable electrolytes makes them inherently susceptible to thermal runaway (TR), which can lead to ignition, explosion, and large-scale fires. Accordingly, early detection of defect internal conditions that precede thermal events is essential for ensuring battery safety. This study proposes a time-resolved partial discharge (TRPD)-based diagnostic method for identifying early electrical precursors of fire hazards in lithium-ion batteries. Both destructive (ex situ) and non-destructive (in situ) experiments were performed to collect defect signal data under physical deformation and accelerated degradation conditions. Through fast fourier transform (FFT) analysis of the acquired signals, specific frequency-domain characteristics associated with micro internal short circuits (MISC) were identified, particularly within the 3.9 MHz, 11.9 MHz, and 19 MHz bands. Defect signals were clearly distinguishable from background common-mode voltage (CMV) noise, confirming the diagnostic sensitivity of the proposed approach. The results demonstrate that the TRPD-based technique enables early recognition of latent insulation degradation and internal short-circuit phenomena before thermal runaway occurs. This work bridges the gap between conventional insulation monitoring and battery safety diagnostics, providing a scalable framework for integrating high-frequency signal analysis into EV and ESS battery management systems for fire prevention. Full article
(This article belongs to the Special Issue Advances in Battery Modelling, Applications, and Technology)
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