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Electronics
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Technology and Approaches of Battery Energy Storage System
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Technology and Approaches of Battery Energy Storage System

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Power Electronics".

Deadline for manuscript submissions: 30 September 2025 | Viewed by 1936

Special Issue Editors

Dr. Xinyu Huang

E-Mail
Guest Editor
School of Human Settlements and Civil Engineering, Xi’an Jiaotong University, Xi’an 710049, China
Interests: thermal energy storage; phase change material; nanoparticle; enhanced heat transfer; optimal design; flow battery
Dr. Juan Fang

E-Mail Website
Guest Editor
School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
Interests: energy storage; solar energy; energy systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the popularity of renewable energy and the rapid development of electric vehicles, battery energy storage systems are becoming a key technology in improving the instability of energy storage and supply systems. For each type of battery technology, there are advantages and disadvantages in their application potentials. This Special Issue focuses on the design and optimization of battery components, control strategies and battery thermal management, battery modularization, management systems, and system integration, all of which are important for improving the performance and reliability of the system. Key technologies, such as battery charging control strategies, energy management systems, and intelligent control technologies, are also important areas in achieving efficient operation and management of battery energy storage systems. In addition, this Special Issue will also focus on battery thermal management system design and optimization methods, including thermal design, liquid/air cooling systems, and phase change materials technology, to effectively control the battery temperature and improve the stability and safety of the system.

Therefore, scholars are encouraged to submit manuscripts for this Special Issue on these themes, including design experiments for battery systems, simulation optimization studies for control strategies and system integration, and novel research on battery thermal management. Authors are also encouraged to consider submitting performance studies for thermal runaway batteries to address potential future challenges.

This Special Issue welcomes contributions that present experience of dealing with such challenges or identifying new ones. The subjects to be covered in this Special Issue include, but are not limited to, the following:

  • The design, modeling, and optimization of battery energy storage systems;
  • Thermal management techniques and thermal stability improvements;
  • Battery thermal effect analysis and control strategies;
  • The reliability, safety, and durability of battery system;
  • Novel materials, designs, and applications of battery thermal management systems;
  • Forecasting, monitoring, and coping strategies for thermal runaway events.

Dr. Xinyu Huang
Dr. Juan Fang
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

  • thermal management
  • control strategy
  • machine learning
  • novel battery material
  • design optimization

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Published Papers (2 papers)

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Research

17 pages, 3547 KiB  
Article
Optimization of Passive Damping for LCL-Filtered AC Grid-Connected PV-Storage Integrated Systems
by Yue Zhang, Chenchen Song, Tao Wang and Kai Wang
Electronics 2025, 14(4), 801; https://doi.org/10.3390/electronics14040801 - 19 Feb 2025
Viewed by 488
Abstract
This paper conducts an in-depth study on the application of inductor-capacitor-inductor (LCL) filters in grid-connected photovoltaic (PV) inverters. First, the resonance issues associated with LCL filters are analyzed, and solutions are discussed, with a focus on the implementation of passive damping strategies. Various [...] Read more.
This paper conducts an in-depth study on the application of inductor-capacitor-inductor (LCL) filters in grid-connected photovoltaic (PV) inverters. First, the resonance issues associated with LCL filters are analyzed, and solutions are discussed, with a focus on the implementation of passive damping strategies. Various passive damping schemes, based on the placement of resistors (R), are compared and analyzed, ultimately selecting the capacitor branch series resistor as the optimal solution. During the design process, multiple parameters, such as total inductance, inverter-side inductance, grid-side inductance, capacitance, and damping resistors, are considered in light of their mutual constraints. Detailed analysis and optimization of these parameters are performed based on steady-state operation, current ripple, and power loss limitations. Finally, it is concluded that the passive damping solution using a series resistor in the capacitor branch meets the requirements for stable operation and efficient filtering. The optimal solutions are identified as R1 = 0, R2 = ∞, R3 ≠ 0, and R4 = ∞, providing a reliable and effective filtering solution for grid-connected PV inverter systems. Full article
(This article belongs to the Special Issue Technology and Approaches of Battery Energy Storage System)
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15 pages, 3062 KiB  
Article
Robust Estimation of Lithium Battery State of Charge with Random Missing Current Measurement Data
by Xi Li, Zongsheng Zheng, Jinhao Meng and Qinling Wang
Electronics 2024, 13(22), 4436; https://doi.org/10.3390/electronics13224436 - 12 Nov 2024
Viewed by 927
Abstract
The precise estimation of the state of charge (SOC) in lithium batteries is crucial for enhancing their operational lifespan. To address the issue of reduced accuracy in SOC estimation caused by the random missing values of lithium battery current measurements, a joint estimation [...] Read more.
The precise estimation of the state of charge (SOC) in lithium batteries is crucial for enhancing their operational lifespan. To address the issue of reduced accuracy in SOC estimation caused by the random missing values of lithium battery current measurements, a joint estimation method which combines recursive least squares with missing input data (MIDRLS) and the unscented Kalman filter (UKF) algorithm is proposed, called the MIDRLS-UKF algorithm. Firstly, the equivalent circuit model of a Thevenin battery is formulated. Then, the current imputation model is designed to interpolate the missing data, based on which the MIDRLS algorithm is derived by solving the unbiased estimation of the gradient of the objective function, thus realizing the online high-precision identification of the circuit model parameters. Furthermore, the proposed algorithm is combined with the UKF algorithm to facilitate the online precise estimation of SOC. The simulation results indicate a marked decrease in the SOC estimation error when employing the proposed joint algorithm, as opposed to the conventional forgetting factor recursive least squares (FFRLS) algorithm combined with the UKF joint estimation algorithm, which verifies the precision and effectiveness of the proposed joint algorithm. Full article
(This article belongs to the Special Issue Technology and Approaches of Battery Energy Storage System)
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