Control and Intelligent Management of Energy Storage Systems
A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Energy Systems".
Deadline for manuscript submissions: closed (30 October 2023) | Viewed by 1966
Special Issue Editors
Interests: electric vehicles; energy management strategy; battery management systems; energy storage
Special Issues, Collections and Topics in MDPI journals
Interests: battery system modeling; state estimation and life prediction; battery system fault diagnosis and health status estimation under big data
Special Issues, Collections and Topics in MDPI journals
Interests: modeling; health prediction; management of lithium-ion battery degradation
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The development of energy storage system is an important path in the decarbonization of the transportation sector. In recent years, the advanced energy storage technologies have attracted the attention of many scholars. It is both an opportunity and a challenge. Many institutions and scholars have focused on the energy storage system and related research directions. The intelligent management and control technology of energy storage system has achieved rapid development. However, there are still some key technologies to be breakthroughs. For example, such as battery state estimation in the whole lifetime, battery extreme fast charge, efficient active cell balance strategy, early warning of failures and thermal runaways, efficient heating and cooling technology, etc. This Special Issue aims to establish a platform for the most recent technologies related to the analyses, management and control of energy storage system. This Special Issue welcomes reviews and technical studies on intelligent management and control of energy storage system.
Potential topics include, but are not limited to:
- modeling and estimation
- early warning of failures and thermal runaways
- cell balancing strategies
- heating and cooling technology
- extreme fast charging technology
- battery aging and life prediction
- artificial intelligence for energy storage system.
Dr. Chun Wang
Dr. Aihua Tang
Dr. Yongzhi Zhang
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. Processes 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
- energy storage
- thermal runaway and management
- cell balancing
- energy management
- fast charging
- lifecycle management
- artificial intelligence
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