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 1381

Special Issue Editors

School of Mechanical Engineering, Sichuan University of Science and Engineering, No. 519, Huixing Road, Zigong 643000, China
Interests: electric vehicles; energy management strategy; battery management systems; energy storage
Special Issues, Collections and Topics in MDPI journals
School of Vehicle Engineering, Chongqing University of Technology, Chongqing 400054, China
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

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Guest Editor
College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400044, China
Interests: transport electrification; energy storage; intelligent and connected vehicles; battery management systems; optimization and control
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

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. 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

Published Papers (1 paper)

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Research

17 pages, 5326 KiB  
Article
Human–Machine Redundant Braking System for Aftermarket Low-Speed Electric Vehicle: Design and Validation
by Shulei Sun, Wei Qu, Xiaorong Huang, Guoying Tian, Pengyi Deng, Kunfan Liu, Yan Tang, Liang Chen and Chongfeng Wei
Processes 2023, 11(7), 2180; https://doi.org/10.3390/pr11072180 - 21 Jul 2023
Viewed by 1138
Abstract
This paper presents the design and experimental validation of a novel human–machine redundant braking system (HMRBS) for aftermarket low-speed electric vehicles (LSEVs) to realise the backup redundancy ability and improve active safety. First, the HMRBS is designed by connecting the electro-hydraulic braking (EHB) [...] Read more.
This paper presents the design and experimental validation of a novel human–machine redundant braking system (HMRBS) for aftermarket low-speed electric vehicles (LSEVs) to realise the backup redundancy ability and improve active safety. First, the HMRBS is designed by connecting the electro-hydraulic braking (EHB) unit oil pipelines in parallel with the manual braking (MB) unit through two three-way shuttle valves. Then, the mathematical model of the EHB subsystem is built, and a master cylinder pressure controller with adaptive fuzzy proportion integration differentiation (PID) and a servo motor speed controller with double-closed-loop proportion integration (PI) are proposed to improve the system response performance. Following this, the co-simulation model of the proposed closed-loop system is established based on AMESim and MATLAB/Simulink to validate the feasibility of the proposed control strategy. Finally, the effectiveness of the HMRBS is also validated by test rig and vehicle experiments. The results imply that the modified LSEV with the HMRBS meets the requirements of vehicle active braking ability and manual braking redundancy. Furthermore, the proposed controller can significantly enhance pressure control accuracy compared to the classical PID controller. The deceleration fluctuation and braking distance in the active braking mode are smaller than those in the manual braking mode, indicating that the proposed system makes the braking effect more stable and safer. Full article
(This article belongs to the Special Issue Control and Intelligent Management of Energy Storage Systems)
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