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Novel Battery Management Systems Using AI in Automotive Applications

This special issue belongs to the section “Power Electronics“.

Special Issue Information

Dear Colleagues,

In the automotive industry, increasing concerns about global warming as well as oil and resource depletion have created an incentive to focus efforts on alternative powertrain technologies. In this context, the development of novel battery systems has gained increasing attention due to their fundamental role in fully electric, hybrid and plug-in hybrid electric vehicles. Nevertheless, battery performance and health are severely affected by application and environmental factors such as temperature, charge/discharge rates, etc. Automotive batteries require constant and accurate monitoring to check their condition, specifically, the level of the remaining available energy and power capability, often indicated by the state of charge and state of health. An accurate and reliable knowledge of those parameter can significantly mitigate psychological factors such as the range anxiety associated with electric vehicles, while improving system performance and lifespan. However, the  battery state of charge and health cannot be directly measured, and these values can only be estimated from the measurement of other battery parameters via novel battery management systems.

The main aim of this Special Issue is to seek high-quality submissions that highlight emerging applications and address recent breakthroughs in the battery management systems using Artificial Intelligence for automotive applications. The topics of interest include, but are not limited to:

  • battery management systems in automotive applications with Artificial Intelligence
  • battery management systems for other applications with Artificial Intelligence
  • state of charge estimation with Artificial Intelligence
  • state of health estimation with Artificial Intelligence
  • prognostic and diagnostic of automotive batteries with Artificial Intelligence
  • application of Artificial Intelligence in novel battery management systems

Dr. Stefano Feraco
Dr. Angelo Bonfitto
Prof. Dr. Nicola Amati
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. Electronics 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 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

  • Automotive engineering
  • Electric and hybrid vehicles
  • Artificial intelligence
  • Battery management systems
  • State of charge
  • State of health
  • Virtual sensing

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Electronics - ISSN 2079-9292