Batteries and Supercapacitors Aging III

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 (31 October 2025) | Viewed by 1335

Special Issue Editors


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Guest Editor
Department of the Ampère Laboratory, Claude Bernard University Lyon 1, 69100 Villeurbanne, France
Interests: characterization; modeling; reliability; aging and diagnosis of electric energy storage system (batter-ies, supercapacitors, capacitors)
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Guest Editor
LICIT-ECO7, Gustave Eiffel University, 69500 Bron, France
Interests: lithium-ion batteries; battery aging; battery characterization and modeling; electric vehicles; energy storage systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Electrochemical energy storage is a key element of systems in a wide range of sectors, such as electro-mobility, portable devices, or renewable energy. The energy storage systems (ESSs) considered here are batteries, supercapacitors, or hybrid components such as lithium-ion capacitors. The durability of ESSs determines the total cost of ownership and the environmental impacts (life cycle) in a large portion of these applications and thus their viability. Understanding the aging of ESSs is a key issue when it comes to optimizing their design and use according to each application. A better knowledge of ESS aging is also essential to improve their dependability (reliability, availability, maintainability, and safety). To achieve these goals, contributions from the scientific community are expected in a wide range of fields (physics, materials engineering, electrical engineering, mathematics, computer science, etc.).

Consequently, the purpose of this Special Issue is to promote research on ESS aging: from the study of aging mechanisms and factors, through the development of diagnostic and prognostic techniques, to the optimal design and management of ESSs in order to extend their lifespan.

Topics of interest include, but are not limited to:

  • Innovative measurement techniques of ESS aging;
  • ESS aging modeling;
  • ESS state-of-health (SOH) estimation;
  • ESS prognostic and health management;
  • Balancing circuits with consideration of the lifetime of ESSs;
  • Aging-aware energy management;
  • Influence of aging on cost and environmental impact of ESSs;
  • Multi-objective optimization strategies for ESSs, including aging consideration;
  • Optimal sizing and design of ESSs with respect to their lifetime. 

Prof. Dr. Pascal Venet
Dr. Eduardo Redondo-Iglesias
Guest Editors

Manuscript Submission Information

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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 mechanisms
  • aging modeling
  • component reliability
  • life cycle assessment
  • lifetime prediction
  • state of health
  • battery
  • supercapacitor
  • hybrid capacitor

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Published Papers (1 paper)

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Research

19 pages, 5943 KB  
Article
A Physics-Guided Transformer for Robust State of Charge Estimation in Aging Lithium-Ion Batteries
by Xiang Li, Guanru Wu, Fei Chang, Weidong Xia, Shaobin Sun and Yingjun Shen
Batteries 2025, 11(12), 446; https://doi.org/10.3390/batteries11120446 - 3 Dec 2025
Viewed by 356
Abstract
Accurate state of charge (SOC) estimation is a critical challenge for battery management systems (BMSs), hindered by the nonlinear electrochemistry of lithium-ion batteries, their sensitivity to temperature, and pervasive measurement noise. Crucially, battery aging significantly degrades estimation accuracy, posing a major hurdle for [...] Read more.
Accurate state of charge (SOC) estimation is a critical challenge for battery management systems (BMSs), hindered by the nonlinear electrochemistry of lithium-ion batteries, their sensitivity to temperature, and pervasive measurement noise. Crucially, battery aging significantly degrades estimation accuracy, posing a major hurdle for long-term system dependability. We propose the Physics-Informed Transformer (PI-Transformer), a novel framework that integrates high-fidelity electrochemical constraints from the PyBaMM (Version: 25.10.2) model directly into a Transformer architecture. This approach ensures physical consistency while leveraging the Transformer’s self-attention mechanism to model long-term temporal dependencies. The framework is specifically designed to be robust against the effects of battery aging, incorporating an attention-based noise modeling module to enhance resilience against sensor uncertainty and capacity fade. Evaluated on two public datasets under diverse conditions, including variable temperatures, fast-charging protocols, and multiple stages of battery degradation, the PI-Transformer consistently achieves state-of-the-art performance. It demonstrates exceptional robustness and maintains high accuracy under challenging low-temperature and severely aged battery scenarios, highlighting its strong potential for deployment in real-world ESS applications where aging is a primary concern. Full article
(This article belongs to the Special Issue Batteries and Supercapacitors Aging III)
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