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Lithium-Ion and Lithium-Sulfur Batteries for Vehicular Applications

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

Deadline for manuscript submissions: 15 October 2025 | Viewed by 214

Special Issue Editors


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Guest Editor
1. Electrochemical Innovation Laboratory, Department of Chemical Engineering, University College London, London WC1E 7JE, UK
2. ZERO Institute, Holywell House, Osney Mead, University of Oxford, Oxford OX2 0ES, UK
Interests: imaging; X-ray CT; electrochemical characterization; synchrotron; energy; engineering materials; energy storage devices; lithium-ion batteries
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Engineering Science, University of Oxford, Oxford OX1 3PJ, UK
Interests: sustainable transportation; SEM; X-ray CT; battery characterization; drive cycles; lithium-ion batteries
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Engineering Science, University of Oxford, Oxford OX1 3PJ, UK
Interests: imaging; fuel cell X-ray CT; electrochemical characterization; synchrotron; fuel cells; electrocatalyst; energy storage materials; lithium-ion batteries
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Guest Editors invite submissions to a Special Issue of Energies entitled “Lithium-Ion and Lithium–Sulfur Batteries for Vehicular Applications”. Batteries have been proven to be a highly viable solution in the age of electrochemical transportation. This Special Issue will deal with all advances and reviews related to lithium-ion and lithium–sulfur batteries for automotive purposes, which include ground vehicles (e.g., cars, HGVs), rail, aviation, unmanned aerial vehicles, and personal electric vehicles (PEVs). Topics of interest for publication include, but are not limited to, the following:

  • Battery cycling;
  • Battery characterization;
  • Battery modeling;
  • Battery vehicle powertrain modeling;
  • Battery materials;
  • Battery degradation;
  • Energy management systems;
  • Battery electric vehicles;
  • Hardware-in-the-loop and software-in-the-loop testing;
  • Imaging of batteries or battery materials;
  • Sizing of vehicle power systems;
  • Drive cycle testing for batteries.

Dr. Wenjia Du
Dr. Jia Di (Ed) Yang
Dr. Juntao Li
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. 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

  • lithium-ion battery
  • lithium-sulfur battery
  • batteries
  • automobile
  • transport
  • sustainable transport
  • hybrid vehicles
  • vehicle powertrain
  • batteries X-ray CT
  • scanning electron microscope (SEM)
  • drive cycles
  • energy management systems
  • battery electric vehicles
  • energy

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Published Papers (1 paper)

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Research

13 pages, 949 KiB  
Article
Applicability Evaluation of an Online Parameter Identification Method: From Lithium-Ion to Lithium–Sulfur Batteries
by Ning Gao, You Gong, Xiaobei Yang, Disai Yang, Yao Yang, Bingyu Wang and Haifei Long
Energies 2025, 18(17), 4493; https://doi.org/10.3390/en18174493 (registering DOI) - 23 Aug 2025
Abstract
While Forgetting Factor Recursive Least Square (FFRLS) algorithms with evaluation mechanisms have been developed to address SOC-dependent parameter mapping shifts and their efficacy has been proven in Li-ion batteries, their applicability to lithium–sulfur (Li-S) batteries remains uncertain due to different electrochemical characteristics. This [...] Read more.
While Forgetting Factor Recursive Least Square (FFRLS) algorithms with evaluation mechanisms have been developed to address SOC-dependent parameter mapping shifts and their efficacy has been proven in Li-ion batteries, their applicability to lithium–sulfur (Li-S) batteries remains uncertain due to different electrochemical characteristics. This study critically evaluates the applicability of a Fisher information matrix-constrained FFRLS framework for online parameter identification in Li-S battery equivalent circuit network (ECN) models. Experimental validation using distinct drive cycles showed that the identification results of polarization-related parameters are significantly biased between different current excitations, and root mean square error (RMSE) variations diverge by 100%, with terminal voltage estimation errors more than 0.05 V. The parametric uncertainty under variable excitation profiles and voltage plateau estimation deficiencies confirms the inadequacy of such approaches, constraining model-based online identification viability for Li-S automotive applications. Future research should therefore prioritize hybrid estimation architectures integrating electrochemical knowledge with data-driven observers, alongside excitation capturing specifically optimized for Li-S online parameter observability requirements and cell nonuniformity and aging condition consideration. Full article
(This article belongs to the Special Issue Lithium-Ion and Lithium-Sulfur Batteries for Vehicular Applications)
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