Special Issue "Lithium-Ion Batteries Aging Mechanisms II"

A special issue of Batteries (ISSN 2313-0105). This special issue belongs to the section "Battery Performance, Ageing, Reliability and Safety".

Deadline for manuscript submissions: 12 January 2023 | Viewed by 13210

Special Issue Editor

Dr. Mauro Francesco Sgroi
E-Mail Website
Guest Editor
Materials Engineering, Methods and Tools, Centro Ricerche FIAT, Strada Torino 50, 10043 Orbassano, Italy
Interests: Li-ion batteries; nanomaterials; density functional theory; molecular dynamics; electrochemistry
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Lithium batteries (including lithium-ion, lithium–sulfur and lithium–air cells) are considered enabling technology for important industrial sectors including electrified vehicles, consumer electronics and stationary energy storage. The calendar and cycle life are key performances to guarantee the penetration in the market of energy storage systems (ESS) based on lithium batteries. The understanding of chemical and physical mechanisms of battery degradation is the first step to develop more reliable and durable systems. Moreover, the monitoring of the battery during its life through different types of sensors to determine the state of health (SOH) and the use of self-healing materials is becoming a more and more popular solution to improve the reliability and durability of Li-ion batteries.

In this Special Issue, we are looking for contributions helping to:

  • Understand aging mechanisms through in situ and ex situ postmortem chemical analysis of cell components;
  • Simulate the degradation of materials through multiscale modeling;
  • Develop new in situ and online sensing principles and approaches to monitor the degradation phenomena;
  • Implement new accelerated aging protocols and state estimation methods (e.g., artificial neural networks, machine learning);
  • Improve the control strategies of the ESS to prolong the lifetime of lithium cells;
  • Develop new self-healing materials able to recover the original functionality after damage;
  • Determine the impact of the aging on the safety of the ESS.

Topics of interest include but are not limited to:

  • Chemical analysis of materials and postmortem analysis;
  • Innovative accelerated protocols for battery aging;
  • Multiscale modeling of aging processes;
  • State-of-health (SOH) estimation;
  • Sensors for in situ and online cell monitoring;
  • Self-healing functionalities;
  • Influence of aging on cost and environmental analyses of ESS;
  • Control logics of ESS;
  • Life Cycle assessment (LCA).

Dr. Mauro Francesco Sgroi
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.

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. Batteries is an international peer-reviewed open access monthly 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 1600 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

  • aging mechanisms
  • aging modeling
  • lifecycle assessment
  • lifetime prediction
  • state of health
  • lithium batteries
  • self-healing
  • postmortem analysis
  • in situ analysis
  • machine learning

Published Papers (9 papers)

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Research

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Article
Development of an Innovative Procedure for Lithium Plating Limitation and Characterization of 18650 Cycle Aged Cells for DCFC Automotive Applications
Batteries 2022, 8(8), 88; https://doi.org/10.3390/batteries8080088 - 14 Aug 2022
Viewed by 735
Abstract
Since lithium-ion batteries seem to be the most eligible technology to store energy for e-mobility applications, it is fundamental to focus attention on kilometric ranges and charging times. The optimization of the charging step can provide the appropriate tradeoff between time saving and [...] Read more.
Since lithium-ion batteries seem to be the most eligible technology to store energy for e-mobility applications, it is fundamental to focus attention on kilometric ranges and charging times. The optimization of the charging step can provide the appropriate tradeoff between time saving and preserving cell performance over the life cycle. The implementation of new multistage constant current profiles and related performances after 1000 cycles are presented and compared with respect to a reference profile. A physicochemical (SEM, XRD, particle size analysis, etc.) and electrochemical (incremental capacity analysis, internal resistance measurements) characterization of the aged cells is shown and their possible implementation on board is discussed. Full article
(This article belongs to the Special Issue Lithium-Ion Batteries Aging Mechanisms II)
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Article
Influence of the Ambient Storage of LiNi0.8Mn0.1Co0.1O2 Powder and Electrodes on the Electrochemical Performance in Li-ion Technology
Batteries 2022, 8(8), 79; https://doi.org/10.3390/batteries8080079 - 28 Jul 2022
Cited by 1 | Viewed by 928
Abstract
Nickel-rich LiNi0.8Mn0.1Co0.1O2 (NMC811) is one of the most promising Li-ion battery cathode materials and has attracted the interest of the automotive industry. Nevertheless, storage conditions can affect its properties and performance. In this work, both NMC811 [...] Read more.
Nickel-rich LiNi0.8Mn0.1Co0.1O2 (NMC811) is one of the most promising Li-ion battery cathode materials and has attracted the interest of the automotive industry. Nevertheless, storage conditions can affect its properties and performance. In this work, both NMC811 powder and electrodes were storage-aged for one year under room conditions. The aged powder was used to prepare electrodes, and the performance of these two aged samples was compared with reference fresh NMC811 electrodes in full Li-ion coin cells using graphite as a negative electrode. The cells were subjected to electrochemical as well as ante- and postmortem characterization. The performance of the electrodes from aged NM811 was beyond expectations: the cycling performance was high, and the power capability was the highest among the samples analyzed. Materials characterization revealed modifications in the crystal structure and the surface layer of the NMC811 during the storage and electrode processing steps. Differences between aged and fresh electrodes were explained by the formation of a resistive layer at the surface of the former. However, the ageing of NMC811 powder was significantly mitigated during the electrode processing step. These novel results are of interest to cell manufacturers for the widespread implementation of NMC811 as a state-of-the-art cathode material in Li-ion batteries. Full article
(This article belongs to the Special Issue Lithium-Ion Batteries Aging Mechanisms II)
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Article
Method for In-Operando Contamination of Lithium Ion Batteries for Prediction of Impurity-Induced Non-Obvious Cell Damage
Batteries 2022, 8(4), 35; https://doi.org/10.3390/batteries8040035 - 14 Apr 2022
Cited by 1 | Viewed by 1117
Abstract
The safety of lithium-ion batteries within electrified vehicles plays an important role. Hazards can arise from contaminated batteries resulting from non-obvious damages or insufficient production processes. A systematic examination requires experimental methods to provoke a defined contamination. Two prerequisites were required: First, the [...] Read more.
The safety of lithium-ion batteries within electrified vehicles plays an important role. Hazards can arise from contaminated batteries resulting from non-obvious damages or insufficient production processes. A systematic examination requires experimental methods to provoke a defined contamination. Two prerequisites were required: First, the extent and type of contamination should be determinable to exclude randomness. Second, specimens should work properly before the contamination, enabling realistic behavior. In this study, two experimental methods were developed to allow for the first time a controlled and reproducible application of water or oxygen into 11 single-layer full cells (Li4Ti5O12/LiCoO2) used as specimens during electrical cycling. Electrochemical impedance spectroscopy was used to continuously monitor the specimens and to fit the parameters of an equivalent circuit model (ECM). For the first time, these parameters were used to calibrate a machine-learning algorithm which was able to predict the contamination state. A decision tree was calibrated with the ECM parameters of eight specimens (training data) and was validated by predicting the contamination state of the three remaining specimens (test data). The prediction quality proved the usability of classification algorithms to monitor for contaminations or non-obvious battery damage after manufacturing and during use. It can be an integral part of battery management systems that increases vehicle safety. Full article
(This article belongs to the Special Issue Lithium-Ion Batteries Aging Mechanisms II)
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Article
The Battery Life Estimation of a Battery under Different Stress Conditions
Batteries 2021, 7(4), 88; https://doi.org/10.3390/batteries7040088 - 18 Dec 2021
Cited by 1 | Viewed by 1176
Abstract
The prediction of capacity degradation, and more generally of the behaviors related to battery aging, is useful in the design and use phases of a battery to help improve the efficiency and reliability of energy systems. In this paper, a stochastic model for [...] Read more.
The prediction of capacity degradation, and more generally of the behaviors related to battery aging, is useful in the design and use phases of a battery to help improve the efficiency and reliability of energy systems. In this paper, a stochastic model for the prediction of battery cell degradation is presented. The proposed model takes its cue from an approach based on Markov chains, although it is not comparable to a Markov process, as the transition probabilities vary with the number of cycles that the cell has performed. The proposed model can reproduce the abrupt decrease in the capacity that occurs near the end of life condition (80% of the nominal value of the capacity) for the cells analyzed. Furthermore, we illustrate the ability of this model to predict the capacity trend for a lithium-ion cell with nickel manganese cobalt (NMC) at the cathode and graphite at the anode, subjected to a life cycle in which there are different aging factors, using the results obtained for cells subjected to single aging factors. Full article
(This article belongs to the Special Issue Lithium-Ion Batteries Aging Mechanisms II)
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Article
Identification of Degradation Mechanisms by Post-Mortem Analysis for High Power and High Energy Commercial Li-Ion Cells after Electric Vehicle Aging
Batteries 2021, 7(3), 48; https://doi.org/10.3390/batteries7030048 - 16 Jul 2021
Cited by 3 | Viewed by 2083
Abstract
Driven by the rise of the electric automotive industry, the Li-ion battery market is in strong expansion. This technology does not only fulfill the requirements of electric mobility, but is also found in most portable electric devices. Even though Li-ion batteries are known [...] Read more.
Driven by the rise of the electric automotive industry, the Li-ion battery market is in strong expansion. This technology does not only fulfill the requirements of electric mobility, but is also found in most portable electric devices. Even though Li-ion batteries are known for their numerous advantages, they undergo serious performance degradation during their aging, and more particularly when used in specific conditions such as at low temperature or high charging current rates. Depending on the operational conditions, different aging mechanisms are favored and can induce physical and chemical modifications of the internal components, leading to performance decay. In this article, the identification of the degradation mechanisms was carried out thanks to an in-depth ante- and post mortem study on three high power and high energy commercial 18,650 cells. Li-ion cells were aged using a battery electric vehicle (BEV) aging profile at −20 °C, 0 °C, 25 °C, and 45 °C in accordance with the international standard IEC 62-660, and in calendar aging mode at 45 °C and SOC 100%. Internal components recovered from fresh and aged cells were investigated through different electrochemical (half-coin cell), chemical (EDX, GD-OES, NMR), and topological (SEM) characterization techniques. The influence of power and energy cells’ internal design and Si content in the negative electrode on cell aging has been highlighted vis-à-vis the capacity and power fade. Full article
(This article belongs to the Special Issue Lithium-Ion Batteries Aging Mechanisms II)
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Article
Detection of Lithium Plating in Li-Ion Cell Anodes Using Realistic Automotive Fast-Charge Profiles
Batteries 2021, 7(3), 46; https://doi.org/10.3390/batteries7030046 - 07 Jul 2021
Cited by 6 | Viewed by 2203
Abstract
The widespread use of electric vehicles is nowadays limited by the “range anxiety” of the customers. The drivers’ main concerns are related to the kilometric range of the vehicle and to the charging time. An optimized fast-charge profile can help to decrease the [...] Read more.
The widespread use of electric vehicles is nowadays limited by the “range anxiety” of the customers. The drivers’ main concerns are related to the kilometric range of the vehicle and to the charging time. An optimized fast-charge profile can help to decrease the charging time, without degrading the cell performance and reducing the cycle life. One of the main reasons for battery capacity fade is linked to the Lithium plating phenomenon. This work investigates two methodologies, i.e., three-electrode cell measurement and internal resistance evolution during charging, for detecting the Lithium plating conditions. From this preliminary analysis, it was possible to develop new Multi-Stage Constant-Current profiles, designed to improve the performance in terms of charging time and cells capacity retention with respect to a reference profile. Four new profiles were tested and compared to a reference. The results coming from the new profiles demonstrate a simultaneous improvement in terms of charging time and cycling life, showing the reliability of the implemented methodology in preventing Lithium plating. Full article
(This article belongs to the Special Issue Lithium-Ion Batteries Aging Mechanisms II)
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Article
An ASIC-Based Miniaturized System for Online Multi-Measurand Monitoring of Lithium-Ion Batteries
Batteries 2021, 7(3), 45; https://doi.org/10.3390/batteries7030045 - 05 Jul 2021
Cited by 3 | Viewed by 1699
Abstract
To better asses the ageing and to reduce the hazards involved in the use of Lithium-Ion Batteries, multi-measurand monitoring units and strategies are urged. In this paper, a Cell Management Unit, based on the SENSIPLUS chip, a recently introduced multichannel, multi-mode sensor interface, [...] Read more.
To better asses the ageing and to reduce the hazards involved in the use of Lithium-Ion Batteries, multi-measurand monitoring units and strategies are urged. In this paper, a Cell Management Unit, based on the SENSIPLUS chip, a recently introduced multichannel, multi-mode sensor interface, is described. SENSIPLUS is a single System on a Chip combined with a reduced number of external components, resulting in a highly miniaturized device, built on 20 × 8 mm2 printed circuit board. Thanks to SENSIPLUS’ versatility, the proposed system is capable of performing direct measurements (EIS, cell voltage) on the cell it is applied to, and reading different kinds of sensors. The SENSIPLUS versatile digital communication interface, combined with a digital isolator, enable connection of several devices to a single bus for parallel monitoring a large number of cells connected in series. Experiments performed by connecting the proposed system to a commercial Lithium-Ion Battery and to capacitive and resistive sensors are described. In particular, the capability of measuring the cell internal impedance with a resolution of 120 μΩ is demonstrated. Full article
(This article belongs to the Special Issue Lithium-Ion Batteries Aging Mechanisms II)
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Article
Thermal Conductivity in Aged Li-Ion Cells under Various Compression Conditions and State-of-Charge
Batteries 2021, 7(3), 42; https://doi.org/10.3390/batteries7030042 - 25 Jun 2021
Cited by 4 | Viewed by 1663
Abstract
Thermal conductivity (TC) is a parameter, which significantly influences the spatial temperature gradients of lithium ion batteries in operative or abuse conditions. It affects the dissipation of the generated heat by the cell during normal operation or during thermal runaway propagation from one [...] Read more.
Thermal conductivity (TC) is a parameter, which significantly influences the spatial temperature gradients of lithium ion batteries in operative or abuse conditions. It affects the dissipation of the generated heat by the cell during normal operation or during thermal runaway propagation from one cell to the next after an external short circuit. Hence, the thermal conductivity is a parameter of great importance, which concurs to assess the safety of a Li-ion battery. In this work, an already validated, non-destructive measurement procedure was adopted for the determination of the evolution of the through-plane thermal conductivity of 41 Ah commercially available Li-ion pouch cells (LiNiMnCoO2-LiMn2O4/Graphite) as function of battery lifetime and state of charge (SOC). Results show a negative parabolic behaviour of the thermal conductivity over the battery SOC-range. In addition, an average decrease of TC in thickness direction of around 4% and 23% was measured for cells cycled at 60 °C with and without compression, respectively. It was shown that pretension force during cycling reduces battery degradation and thus minimises the effect of ageing on the thermal parameter deterioration. Nevertheless, this study highlights the need of adjustment of the battery pack cooling system due to the deterioration of thermal conductivity after certain battery lifetime with the aim of reducing the risk of battery overheating after certain product life. Full article
(This article belongs to the Special Issue Lithium-Ion Batteries Aging Mechanisms II)
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Review

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Review
Recent Health Diagnosis Methods for Lithium-Ion Batteries
Batteries 2022, 8(7), 72; https://doi.org/10.3390/batteries8070072 - 15 Jul 2022
Cited by 1 | Viewed by 735
Abstract
Lithium-ion batteries have good performance and environmentally friendly characteristics, so they have great potential. However, lithium-ion batteries will age to varying degrees during use, and the process is irreversible. There are many aging mechanisms of lithium batteries. In order to better verify the [...] Read more.
Lithium-ion batteries have good performance and environmentally friendly characteristics, so they have great potential. However, lithium-ion batteries will age to varying degrees during use, and the process is irreversible. There are many aging mechanisms of lithium batteries. In order to better verify the internal changes of lithium batteries when they are aging, post-mortem analysis has been greatly developed. In this article, we summarized the electrical properties analysis and post-mortem analysis of lithium batteries developed in recent years and compared the advantages of varieties of both destructive and non-destructive methods, for example, open-circuit-voltage curve-based analysis, scanning electron microscopy, transmission electron microscopy, atomic force microscopy, X-ray photoelectron spectroscopy and X-ray diffraction. On this basis, new ideas could be proposed for predicting and diagnosing the aging degree of lithium batteries, at the same time, further implementation of these technologies will support battery life control strategies and battery design. Full article
(This article belongs to the Special Issue Lithium-Ion Batteries Aging Mechanisms II)
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