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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "D2: Electrochem: Batteries, Fuel Cells, Capacitors".

Deadline for manuscript submissions: closed (11 April 2024) | Viewed by 7841

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Dr. Jun Young Cheong

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Bavarian Center for Battery Technology (Baybatt) and Department of Chemistry, University of Bayreuth, 95447 Bayreuth, Germany
Interests: lithium-ion batteries; other metal-ion batteries; supercapacitors and pseudocapacitors; metal–air/gas batteries; metal–sulfur and metal–dichalcogenide batteries

Special Issue Information

Dear Colleagues,

With the increase in the global population and energy consumption, the demands for sustainable and rechargeable energy storage systems have recently gained much attention. Since their initial commercialization in the early 1990s and the recent reception of the Nobel Prize in Chemistry, lithium-ion batteries (LIBs) have undergone significant development, and mobile electronics as well as electric vehicles make full use of LIBs. To further improve the energy density and power density of LIBs, many advanced forms of batteries and energy storage systems (Na,K-ion batteries, supercapacitors, pseudocapacitors, metal–air batteries, metal–sulfur/dichalcogenide batteries) are currently being researched, with significant advances made over the last two decades. It is important to further push the limit of the current state-of-the-art lithium-ion batteries, as lithium is scarce and the demand for rechargeable batteries is constantly increasing. Additionally, the safety issues of lithium-ion batteries need to be solved, which calls for more alternative energy storage systems based on an aqueous electrolyte (examples of which are supercapacitors, pseudocapacitors, and Zn-ion batteries).

In this Special Issue, we welcome the submission of works related to Advances in Batteries and Electrochemical Energy Storage. The topics of interests include:

Advanced research on lithium-ion batteries;
Advanced research on sodium/magnesium/potassium/aluminum-ion batteries;
Advanced research on supercapacitors, pseudocapacitors, and hybrid capacitors;
Advanced research on lithium/sodium–air batteries and lithium/sodium–CO₂batteries;
Advanced research on lithium/sodium–sulfur batteries and lithium/sodium–selenium, telluride batteries;
Advanced materials and techniques for analyzing dynamical changes within the batteries and supercapacitors;
Advanced processing methods for the batteries and other energy storage systems.

Dr. Jun Young Cheong
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 100 words) can be sent to the Editorial Office for announcement on this website.

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Keywords

lithium-ion batteries
other metal-ion batteries
supercapacitors and pseudocapacitors
metal–air/gas batteries
metal–sulfur and metal–dichalcogenide batteries

Published Papers (4 papers)

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Research

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29 pages, 13658 KiB

Open AccessArticle

Optimization Approaches for Cost and Lifetime Improvements of Lithium-Ion Batteries in Electric Vehicle Powertrains

by Aissam Riad Meddour, Nassim Rizoug, Patrick Leserf, Christopher Vagg, Richard Burke and Cherif Larouci

Energies 2023, 16(18), 6535; https://doi.org/10.3390/en16186535 - 11 Sep 2023

Cited by 2 | Viewed by 1096

Abstract

With the increasing adoption of electric vehicles (EVs), optimizing lithium-ion battery capacity is critical for overall powertrain performance. Recent studies have optimized battery capacity in isolation without considering interactions with other powertrain components. Furthermore, even when the battery is considered within the full powertrain, most works have only modeled the electrical behavior without examining thermal or ageing dynamics. However, this fails to capture systemic impacts on overall performance. This study takes a holistic approach to investigate the effects of battery capacity optimization on convergence of the full EV powertrain. A battery multiphysics model was developed in MATLAB/Simulink, incorporating experimental data on electrical, thermal, and ageing dynamics and interactions with other components. The model was evaluated using real-world WLTP and Artemis driving cycles to simulate realistic conditions lacking in prior works. The findings reveal significant impacts of battery optimization on total powertrain performance unaccounted for in previous isolated studies. By adopting a system-level perspective and realistic driving cycles, this work provides enhanced understanding of interdependent trade-offs to inform integrated EV design. Full article

(This article belongs to the Special Issue Advances in Batteries and Electrochemical Energy Storage)

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12 pages, 17295 KiB

Open AccessArticle

Optimization of the Electrochemical Discharge of Spent Li-Ion Batteries from Electric Vehicles for Direct Recycling

by Hyunseok Lee, Yu-Tack Kim and Seung-Woo Lee

Energies 2023, 16(6), 2759; https://doi.org/10.3390/en16062759 - 16 Mar 2023

Viewed by 2156

Abstract

Numerous studies have been conducted on spent lithium-ion batteries (LIBs) recycled from electric vehicles. Research on pre-processing techniques to safely disassemble spent LIB packs has mainly focused on water-based discharge methods, such as salt-water discharge. However, salt-water discharge corrodes the electrodes and case, causing internal contamination. Therefore, we propose an electrical discharge process that is suitable for the direct recycling and safe disassembly of spent Li-ion batteries. Spent LIBs from electric vehicles (EV) that were scrapped after EV operation were recovered and electrochemically discharged to voltages of 0, 1, 2, and 2.5 V. These discharged spent LIBs were analyzed through X-ray diffraction, scanning electron microscopy, and electrochemical impedance spectroscopy. The spent LIB with a state-of-health (SoH) of 66.8% exhibited significantly increased swelling and bulging when over-discharged. Notably, the discharging of the spent battery to 0 V increased the thickness of the cell by 115%, which could result in a fire and/or explosion. After being discharged to 0 V, the voltage was able to recover to 2.689 V. The appropriate voltage for the discharge process was estimated to be 2.5 V. The proposed electrical discharge process will be suitable for the direct recycling of spent LIBs in the form of pouch cells. Full article

(This article belongs to the Special Issue Advances in Batteries and Electrochemical Energy Storage)

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17 pages, 3862 KiB

Open AccessArticle

Temperature-Based State-of-Charge Estimation Using Neural Networks, Gradient Boosting Machine and a Jetson Nano Device for Batteries

by Donghun Wang, Jihwan Hwang, Jonghyun Lee, Minchan Kim and Insoo Lee

Energies 2023, 16(6), 2639; https://doi.org/10.3390/en16062639 - 10 Mar 2023

Cited by 1 | Viewed by 1358

Abstract

Lithium-ion batteries are commonly used in electric vehicles, mobile phones, and laptops because of their environmentally friendly nature, high energy density, and long lifespan. Despite these advantages, lithium-ion batteries may experience overcharging or discharging if they are not continuously monitored, leading to fire and explosion risks, in cases of overcharging, and decreased capacity and lifespan, in cases of overdischarging. Another factor that can decrease the capacity of these batteries is their internal resistance, which varies with temperature. This study proposes an estimation method for the state of charge (SOC) using a neural network (NN) model that is highly applicable to the external temperatures of batteries. Data from a vehicle-driving simulator were used to collect battery data at temperatures of 25 °C, 30 °C, 35 °C, and 40 °C, including voltage, current, temperature, and time data. These data were used as inputs to generate the NN models. The NNs used to generate the model included the multilayer neural network (MNN), long short-term memory (LSTM), gated recurrent unit (GRU), and gradient boosting machine (GBM). The SOC of the battery was estimated using the model generated with a suitable temperature parameter and another model generated using all the data, regardless of the temperature parameter. The performance of the proposed method was confirmed, and the SOC-estimation results demonstrated that the average absolute errors of the proposed method were superior to those of the conventional technique. In the estimation of the battery’s state of charge in real time using a Jetson Nano device, an average error of 2.26% was obtained when using the GRU-based model. This method can optimize battery performance, extend battery life, and maintain a high level of safety. It is expected to have a considerable impact on multiple environments and industries, such as electric vehicles, mobile phones, and laptops, by taking advantage of the lightweight and miniaturized form of the Jetson Nano device. Full article

(This article belongs to the Special Issue Advances in Batteries and Electrochemical Energy Storage)

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Review

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28 pages, 6841 KiB

Open AccessReview

Electrochemical Failure Results Inevitable Capacity Degradation in Li-Ion Batteries—A Review

by Wei Li, Hang Li, Zheng He, Weijie Ji, Jing Zeng, Xue Li, Yiyong Zhang, Peng Zhang and Jinbao Zhao

Energies 2022, 15(23), 9165; https://doi.org/10.3390/en15239165 - 2 Dec 2022

Cited by 5 | Viewed by 2784

Abstract

Lithium-ion batteries (LIBs) have been widely used in mobile devices, energy storage power stations, medical equipment, and other fields, became an indispensable technological product in modern society. However, the capacity degradation of LIBs limits their long-term deployment, which is not conducive to saving resources. What is more, it will lead to safety problems when the capacity of the battery is degraded. Failure of the battery is a key issue in the research and application of LIBs. Faced with the problem of capacity degradation, various aspects of LIBs have been studied. This paper reviews the electrochemical degradation mechanism of LIBs’ life fade, detection technologies for battery failure, methods to regulate battery capacity degradation, and battery lifetime prognostics. Finally, the development trend and potential challenges of battery capacity degradation research are prospected. All the key insights from this review are expected to advance the research on capacity fading and lifetime prediction techniques for LIBs. Full article

(This article belongs to the Special Issue Advances in Batteries and Electrochemical Energy Storage)

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