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Advanced Energy Storage Technologies and Applications (AESAs), 2nd Edition
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Advanced Energy Storage Technologies and Applications (AESAs), 2nd Edition

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

Deadline for manuscript submissions: 25 June 2025 | Viewed by 3405

Special Issue Editors

Dr. Chun Wang

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Guest Editor
School of Mechanical Engineering, Sichuan University of Science & Engineering, Zigong 643000, China
Interests: multi-power-integrated management and optimal control of new energy vehicles; artificial intelligence management and control of advanced energy storage systems; optimized control of intelligent connected vehicles
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Quanqing Yu

E-Mail Website
Guest Editor
School of Automotive Engineering, Harbin Institute of Technology, Weihai 264209, China
Interests: battery reliability analysis; battery health management; battery state estimation
Special Issues, Collections and Topics in MDPI journals
Dr. Aihua Tang

E-Mail Website
Guest Editor
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
Dr. Yongzhi Zhang

E-Mail Website
Guest Editor
College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400044, China
Interests: modeling; health prediction; management of lithium-ion battery degradation
Special Issues, Collections and Topics in MDPI journals
Dr. Jiahuan Lu

E-Mail Website
Guest Editor
College of Engineering, South China Agricultural University, Guangzhou 510642, China
Interests: battery management and cascade utilization; engineering applications of artificial intelligence

Special Issue Information

Dear Colleagues,

As the global demand for energy continues to rise, the development of advanced energy storage technologies and intelligent transportation systems has become critical in addressing the pressing challenges of decarbonization and sustainable development. Energy storage, in particular, plays a pivotal role in integrating renewable energy sources, enhancing grid stability, and facilitating the electrification of the transport sector. Ongoing innovation in these areas not only contributes to a reduction in carbon emissions but also ensures the efficient and resilient operation of future energy systems.

This Special Issue aims to highlight cutting-edge research and technological advancements in energy storage and intelligent transportation. We invite contributions that explore novel materials, systems, and methods that push the boundaries of our current capabilities. Submissions may include theoretical, experimental, and review papers that provide valuable insights into the latest trends and future directions in these fields.

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

  • Energy storage;
  • Power and energy systems;
  • Electrified/intelligent transportation;
  • Batteries and management;
  • Motor and control;
  • Power electronics;
  • AI and big data applications.

Dr. Chun Wang
Dr. Quanqing Yu
Dr. Aihua Tang
Dr. Yongzhi Zhang
Dr. Jiahuan Lu
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

  • energy storage
  • power and energy systems
  • electrified/intelligent transportation
  • batteries and management
  • motor and control
  • power electronics
  • AI and big data applications

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Related Special Issue

Published Papers (4 papers)

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Research

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16 pages, 10218 KiB  
Article
Combined State-of-Charge Estimation Method for Lithium-Ion Batteries Using Long Short-Term Memory Network and Unscented Kalman Filter
by Long Pu and Chun Wang
Energies 2025, 18(5), 1106; https://doi.org/10.3390/en18051106 - 24 Feb 2025
Viewed by 513
Abstract
The state of charge (SOC) of lithium-ion batteries (LIBs) is a pivotal metric within the battery management system (BMS) of electric vehicles (EVs). An accurate SOC is crucial to ensuring both the safety and the operational efficiency of a battery. The unscented Kalman [...] Read more.
The state of charge (SOC) of lithium-ion batteries (LIBs) is a pivotal metric within the battery management system (BMS) of electric vehicles (EVs). An accurate SOC is crucial to ensuring both the safety and the operational efficiency of a battery. The unscented Kalman filter (UKF) is a classic and commonly used method among the various SOC estimation algorithms. However, an unscented transform (UT) utilized in the algorithm struggles to completely simulate the probability density function of actual data. Additionally, inaccuracies in the identification of battery model parameters can lead to performance degradation or even the divergence of the algorithm in SOC estimation. To address these challenges, this study introduces a combined UKF-LSTM algorithm that integrates a long short-term memory (LSTM) network with the UKF for the precise SOC estimation of LIBs. Firstly, the particle swarm optimization (PSO) algorithm was utilized to accurately identify the parameters of the battery model. Secondly, feature parameters that exhibited a high correlation with the estimation error of the UKF were selected to train an LSTM network, which was then combined with the UKF to establish the joint algorithm. Lastly, the effectiveness of the UKF-LSTM was confirmed under various conditions. The outcomes demonstrate that the average absolute error (MAE) and the root mean square error (RMSE) for the SOC estimation by the algorithm were less than 0.7%, indicating remarkable estimation accuracy and robustness. Full article
(This article belongs to the Special Issue Advanced Energy Storage Technologies and Applications (AESAs), 2nd Edition)
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13 pages, 2634 KiB  
Article
Fault Gouge Permeability Under Confined Conditions: An Investigation for CO2 Storage Applications
by Aigerim Sekerbayeva, Ali Mortazavi, Randy D. Hazlett and Bahman Bohloli
Energies 2025, 18(1), 9; https://doi.org/10.3390/en18010009 - 24 Dec 2024
Viewed by 601
Abstract
This investigation provides an in-depth experimental analysis of the prepared artificial fault gouge material on permeability characteristics as a function of the confining pressures and injection flow rate pertinent to both CO2 storage and subsurface fluid flow that addresses an ultimate challenge [...] Read more.
This investigation provides an in-depth experimental analysis of the prepared artificial fault gouge material on permeability characteristics as a function of the confining pressures and injection flow rate pertinent to both CO2 storage and subsurface fluid flow that addresses an ultimate challenge in CO2 storage. The purpose of the research is to gain a better understanding of the role of fault gouge material in structuring fluid flow patterns within geological media and improving the safety and efficiency of subsurface storage systems. In order to ensure the reproducibility of the experimental program, fault gouge material that resembled the size distribution and material type observed in the field and reported within the literature was purposefully designed and prepared. A set of core-flooding experiments were conducted to evaluate the relationships between permeability, confining pressure, and fluid flow rates. The subsequently obtained results showed that lower permeability is always the result of increasing confining pressure, highlighting the significance of fault gouge material for controlling fluid flow in fractured rock formations. These conclusions provide novel insights and can be applicable in practice when evaluating the integrity of CO2 storage sites, which calls for knowledge of permeability behavior under high-stress conditions. Full article
(This article belongs to the Special Issue Advanced Energy Storage Technologies and Applications (AESAs), 2nd Edition)
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15 pages, 3474 KiB  
Article
Application of Discrete Variable-Gain-Based Self-Immunity Control to Flywheel Energy Storage Systems
by Jian Sun, Pengju Yin and Xiangliu Song
Energies 2024, 17(21), 5373; https://doi.org/10.3390/en17215373 - 29 Oct 2024
Viewed by 753
Abstract
For the study of the trade-off between steady-state error and transient response in control systems for flywheel energy storage, a controller with a discrete variable gain is proposed. This controller aims to adapt to changes in the system state by dynamically adjusting the [...] Read more.
For the study of the trade-off between steady-state error and transient response in control systems for flywheel energy storage, a controller with a discrete variable gain is proposed. This controller aims to adapt to changes in the system state by dynamically adjusting the controller gain to optimize the system’s anti-disturbance performance. Theoretical analysis and mathematical derivation demonstrate that increasing the observer gain can significantly enhance the system’s anti-disturbance capability. However, this increase also results in overshooting, which highlights the limitations of traditional control methods in achieving both system stability and anti-disturbance performance. A discrete variable-gain extended state observer is designed. The gain of this observer can be adaptively adjusted according to a system state value, enabling the effective control of both steady-state error and transient response. Additionally, the stability of the proposed control method was analyzed and verified, ensuring its effectiveness and reliability for practical applications. Finally, the effectiveness of the proposed method in improving system performance is demonstrated by simulation results. Full article
(This article belongs to the Special Issue Advanced Energy Storage Technologies and Applications (AESAs), 2nd Edition)
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Review

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44 pages, 3855 KiB  
Review
Grid Peak Shaving and Energy Efficiency Improvement: Advances in Gravity Energy Storage Technology and Research on Its Efficient Application
by Shaojun Wang, Hao Xiao, Zhaoquan Zhao, Dezhao Li, Dong Hu, Qi Hu, Chen Shen, Xingyu Zhang, Jiahao Hu, Cheng Chi, Xin Cheng, Wei Zhang, Erjun Bu, Chenxu Zhao, An Wang and Lu Wang
Energies 2025, 18(4), 996; https://doi.org/10.3390/en18040996 - 19 Feb 2025
Viewed by 877
Abstract
Global energy issues have spurred the development of energy storage technology, and gravity-based energy storage (GBES) technology has attracted much attention. This comprehensive review examines the principles, applications, and prospects of GBES technology, a promising solution for mitigating the intermittency of renewable energy [...] Read more.
Global energy issues have spurred the development of energy storage technology, and gravity-based energy storage (GBES) technology has attracted much attention. This comprehensive review examines the principles, applications, and prospects of GBES technology, a promising solution for mitigating the intermittency of renewable energy sources and enhancing grid stability. GBES harnesses potential energy by elevating solid or liquid mediums, offering distinct advantages over other energy storage technologies such as pumped hydro storage and batteries. The study examines various GBES configurations, emphasizing the importance of system design, control strategies, and efficiency. This review also evaluates the economic, environmental, and social benefits of GBES, emphasizing its cost-effectiveness and potential for local economic growth. The need for policy support, technological innovation, and a robust regulatory framework is highlighted to promote the widespread adoption of GBES, which holds significant potential for enhancing grid stability and supporting the integration of renewable energy. Full article
(This article belongs to the Special Issue Advanced Energy Storage Technologies and Applications (AESAs), 2nd Edition)
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