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Modeling, Diagnosis and Protection for Li-Ion Battery Energy Storage System—2nd...
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Modeling, Diagnosis and Protection for Li-Ion Battery Energy Storage System—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: closed (2 October 2024) | Viewed by 3949

Special Issue Editors

Prof. Dr. Bingxiang Sun

E-Mail Website
Guest Editor
National Active Distribution Network Technology Research Center (NANTEC), Beijing Jiaotong University, Beijing 100044, China
Interests: battery energy storage system; battery management system; time-frequency domain modeling; electrochemical model; virtual battery; low-temperature heating
Special Issues, Collections and Topics in MDPI journals
Dr. Liye Wang

E-Mail Website
Guest Editor
Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing 100190, China
Interests: battery energy storage system; battery management system; battery modeling; wireless charging technology
Special Issues, Collections and Topics in MDPI journals
Dr. Linfeng Zheng

E-Mail Website
Guest Editor
Institute of Rail Transportation, Jinan University, Zhuhai 519070, China
Interests: battery management; embedded system; modeling and simulation; optimization and control; battery energy storage system
Special Issues, Collections and Topics in MDPI journals
Dr. Haijun Ruan

E-Mail Website
Guest Editor
Dyson School of Design Engineering, Imperial College London, London SW7 2BX, UK
Interests: lithium-ion batteries; battery management system; machine learning; optimization and control; energy storage system
Special Issues, Collections and Topics in MDPI journals
Dr. Dongsheng Ren

E-Mail
Guest Editor
Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing 100084, China
Interests: battery energy storage system; thermal failure mechanism and multiscale modeling of lithium-ion battery/solid-state batteries
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Lithium-ion batteries are often connected in series and parallel to formulate a lithium-ion battery system (pack) for meeting the high-voltage and high-capacity requirements of energy storage systems. It is particularly important to accurately model the behaviors, estimate the states, diagnose the degradation and faults of the battery energy storage system, and further take necessary measures to prevent any potential safety hazards. However, with an appreciable number of batteries available worldwide, it is challenging to capture the performance, monitor the states, and identify the faults of each battery. Emerging techniques, such as big data mining, artificial intelligence, digital twin, and block chain, bring the potential of addressing these issues through developing new models, state estimation methods, and diagnostic approaches; thus, enabling a promising candidate able to achieve an early fault and safety warning. Furthermore, in order to allow for the application of battery energy storage systems to be safer and more reliable, increasing research has been aimed at optimizing the design and control technologies of battery systems. This Special Issue expects to explore research innovation within the battery system engineering challenge that incorporates modeling, state estimation, diagnostics, prognostics, control engineering, system design, and safety engineering; thus, promoting the mass commercialization and popularity of the Li-ion battery energy storage system. Manuscripts from cross-disciplinary fields, theoretical and practical studies and novel methods are strongly encouraged and welcome.

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

  • Accurate modeling and fast simulation of Li-ion battery systems;
  • Application of digital twin for lithium-ion battery systems;
  • The estimation of battery states, such as SOC, SOH, SOF, SOP, and temperature;
  • Fast charging and charging optimization methods;
  • Wireless charging technology;
  • Battery thermal management;
  • Design and application of battery virtualization equipment;
  • Reliability optimization techniques for lithium-ion battery systems;
  • State parameter prognosis and fault diagnosis of lithium-ion battery systems;
  • Thermal runaway and thermal failure mechanism;
  • Safety protection technology of lithium-ion battery pack;
  • Battery management system (BMS) optimization design technology.

Prof. Dr. Bingxiang Sun
Dr. Liye Wang
Dr. Linfeng Zheng
Dr. Haijun Ruan
Dr. Dongsheng Ren
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

  • lithium-ion battery
  • modeling
  • digital twin
  • virtual battery
  • thermal management, state estimation and prognostics
  • faults diagnosis
  • safety protection
  • BMS

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Related Special Issue

Published Papers (3 papers)

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Research

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19 pages, 4037 KiB  
Article
Modeling and Characterization of Li-Ion 18650 Nickel–Cobalt–Alumina Battery Jellyroll Subjected to Static and Dynamic Compression Loading
by Sigit Puji Santosa and Hafiz Fadillah
Energies 2024, 17(19), 4967; https://doi.org/10.3390/en17194967 - 4 Oct 2024
Viewed by 562
Abstract
This study presents a comprehensive experimental investigation of the mechanical response of the jellyroll and complete Li-ion 18650 Nickel–Cobalt–Alumina (NCA) battery under axial compression, highlighting the effects of strain rate and state-of-charge (SOC). The jellyroll was subjected to both static (1 mm/min) and [...] Read more.
This study presents a comprehensive experimental investigation of the mechanical response of the jellyroll and complete Li-ion 18650 Nickel–Cobalt–Alumina (NCA) battery under axial compression, highlighting the effects of strain rate and state-of-charge (SOC). The jellyroll was subjected to both static (1 mm/min) and dynamic (10–30 m/s) axial compression using a Split-Hopkinson Pressure Bar (SHPB). A key innovation of this work is the investigation of the role of electrolytes under both static and dynamic conditions, revealing their significant impact on stress and strain behavior due to hydrostatic pressure. Additionally, the complete NCA battery was tested under various SOC levels (0–75%) using flat plate compression. The results demonstrate the jellyroll’s sensitivity to strain rate, with increased stress responses at higher loading speeds. Furthermore, the inclusion of electrolytes markedly amplified the stress and strain response. The Fu-Chang model was successfully employed to numerically replicate the observed static and dynamic behaviors. Critically, the full battery tests revealed a negative correlation between voltage cutoff and SOC, with the risk of fire and explosion increasing at higher SOC levels. This research provides novel insights into the safety and mechanical resilience of Li-ion batteries under compression. Full article
(This article belongs to the Special Issue Modeling, Diagnosis and Protection for Li-Ion Battery Energy Storage System—2nd Edition)
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17 pages, 5365 KiB  
Article
The Impact of Wide Discharge C-Rates on the Voltage Plateau Performance of Cylindrical Ternary Lithium-Ion Batteries
by Xingxing Wang, Yuhang Chen, Linfei Chen, Shengren Liu, Yu Zhu and Yelin Deng
Energies 2024, 17(14), 3488; https://doi.org/10.3390/en17143488 - 16 Jul 2024
Cited by 1 | Viewed by 1231
Abstract
Battery voltage plateau characteristics are crucial for designing and controlling battery management systems. Utilising the plateau period attributes to their fullest extent can enable optimal battery control, enhance battery performance, and prolong battery lifespan. This research aimed to investigate the performance of cylindrical [...] Read more.
Battery voltage plateau characteristics are crucial for designing and controlling battery management systems. Utilising the plateau period attributes to their fullest extent can enable optimal battery control, enhance battery performance, and prolong battery lifespan. This research aimed to investigate the performance of cylindrical ternary lithium batteries at various discharge rates, focusing on the variations in terminal voltage, capacity, and temperature. The battery performance at different discharge rates was meticulously examined through cyclic charge/discharge experiments. The convexity of the voltage curve was used to analyse the voltage plateau characteristics at different rates. The findings revealed significant differences in battery performance under varying discharge rates. Higher discharge rates resulted in shorter discharge times and lower battery voltages at corresponding residual capacities. The discharge time, capacity, and voltage during the plateau phase decreased as the discharge rate increased. At discharge rates of 1 C, 3 C, 5 C, 7 C, 9 C, and 11 C, the proportion of discharged battery capacity ranged from 86.45% to 78.42%. At the same time, voltage and temperature variations during the plateau period decreased significantly compared to those before and after discharge. This research provides a crucial reference point for advancing battery design and thermal management systems. Full article
(This article belongs to the Special Issue Modeling, Diagnosis and Protection for Li-Ion Battery Energy Storage System—2nd Edition)
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Review

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15 pages, 6055 KiB  
Review
Advancing Smart Lithium-Ion Batteries: A Review on Multi-Physical Sensing Technologies for Lithium-Ion Batteries
by Wenwei Wang, Shuaibang Liu, Xiao-Ying Ma, Jiuchun Jiang and Xiao-Guang Yang
Energies 2024, 17(10), 2273; https://doi.org/10.3390/en17102273 - 8 May 2024
Viewed by 1638
Abstract
Traditional battery management systems (BMS) encounter significant challenges, including low precision in predicting battery states and complexities in managing batteries, primarily due to the scarcity of collected signals. The advancement towards a “smart battery”, equipped with diverse sensor types, promises to mitigate these [...] Read more.
Traditional battery management systems (BMS) encounter significant challenges, including low precision in predicting battery states and complexities in managing batteries, primarily due to the scarcity of collected signals. The advancement towards a “smart battery”, equipped with diverse sensor types, promises to mitigate these issues. This review highlights the latest developments in smart sensing technologies for batteries, encompassing electrical, thermal, mechanical, acoustic, and gas sensors. Specifically, we address how these different signals are perceived and how these varied signals could enhance our comprehension of battery aging, failure, and thermal runaway mechanisms, contributing to the creation of BMS that are safer and more reliable. Moreover, we analyze the limitations and challenges faced by different sensor applications and discuss the advantages and disadvantages of each sensing technology. Conclusively, we present a perspective on overcoming future hurdles in smart battery development, focusing on appropriate sensor design, optimized integration processes, efficient signal transmission, and advanced management systems. Full article
(This article belongs to the Special Issue Modeling, Diagnosis and Protection for Li-Ion Battery Energy Storage System—2nd Edition)
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