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Intelligent Energy Management Systems and Control for Electrified Vehicles

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "E: Electric Vehicles".

Deadline for manuscript submissions: 20 September 2026 | Viewed by 526

Editor

Hubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of Technology, Wuhan 430070, China
Interests: energy management control of vehicle systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The rapid adaption of electric vehicles (EVs) has become a cornerstone of the global transition toward sustainable transportation. However, the efficient management of energy in EVs remains a critical challenge, directly impacting their performance, range and overall sustainability. Optimized energy management technologies are essential to maximize the utilization of energy resources, enhance battery life and improve the overall efficiency of EV systems.

Building upon the success of the previous Special Issue, “Optimized Energy Management Technology for Electric Vehicle”, this new Special Issue, entitled "Intelligent Energy Management Systems and Control for Electrified Vehicles",aims to showcase the latest advancements in energy management strategies, technologies and methodologies tailored for electric vehicles. We invite contributions that address the design, modeling, optimization and implementation of energy management systems (EMS) for EVs, as well as their integration with renewable energy sources, smart grids and other emerging technologies.

Topics of interest for publication include, but are not limited to, the following:

  • Advanced energy management strategies for EVs
  • Optimization of battery performance and thermal management
  • Integration of EVs with renewable energy systems and smart grids
  • Machine-learning and AI-based approaches for energy management
  • Power electronics and control techniques for EV energy systems
  • Intelligent energy management for fuel cell vehicles
  • Novel energy-storage technologies for EVs
  • Real-time monitoring and fault diagnosis in EV energy systems
  • Intelligent energy-saving control for electric vehicles

We encourage researchers and practitioners to submit their original research, reviews and case studies that contribute to the advancement of optimized energy management technologies for electric vehicles.

Dr. Bin Huang
Guest Editor

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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized 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

  • electric vehicles (EVs)
  • energy management
  • optimization techniques
  • battery optimization

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Published Papers (1 paper)

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Research

16 pages, 8760 KB  
Article
Study on Multi-Parameter Evolution Characteristics of 314 Ah High-Capacity LiFePO4 Batteries During Thermal Runaway Under Various Abuse Conditions
by Chuihui Zeng, Yan Gan, Jun Wu, Baolei Li, Jia Chen, Xiangde Sun, Nuo Chen and Yaqi Fang
Energies 2026, 19(11), 2536; https://doi.org/10.3390/en19112536 - 25 May 2026
Viewed by 277
Abstract
High-capacity energy storage batteries contain complex physicochemical systems. The thermal runaway within batteries pose significant challenges to widespread application in energy storage systems. To better investigate the safety warning thresholds of battery energy storage systems, it is necessary to study the thermal runaway [...] Read more.
High-capacity energy storage batteries contain complex physicochemical systems. The thermal runaway within batteries pose significant challenges to widespread application in energy storage systems. To better investigate the safety warning thresholds of battery energy storage systems, it is necessary to study the thermal runaway characteristics and behavioral patterns of batteries under various abusive conditions. This study focuses primarily on energy storage batteries in actual operation and on simulating real-world operating conditions. A multi-parameter experimental monitoring platform based on temperature, voltage, expansion force, and particulate matter concentration was established to investigate the multi-parameter variation patterns and distinctive characteristics of thermal runaway in energy storage cells under electrothermal coupling and overcharging abuse conditions. The results show that under electrothermal coupling conditions, the initial critical moment of thermal runaway occurs 530 s earlier than under overcharging conditions, with a maximum temperature reaching 457.2 °C; however, under overcharging conditions, the thermal runaway process is more severe, with a maximum temperature reaching 580.9 °C. A comparative analysis of the early warning thresholds for multiple parameters revealed that the threshold based on mechanical signals appears the earliest. Under electrothermal coupling conditions, the force signal preceded the injection valve signal, voltage signal, and temperature signal by 121 s, 305 s, and 732 s, respectively, with a maximum expansion force of 6836 N; under electrical abuse conditions, the force signal preceded the aforementioned signals by 458 s, 711 s, and 1733 s, respectively, with a maximum expansion force reaching 7566 N. This study provides a basis for the thermal management design and safety control of energy storage batteries. This study offers insights for safeguarding the proper operation of battery energy storage systems. Full article
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