Special Issue "Battery Systems and Energy Storage beyond 2020"

A special issue of Batteries (ISSN 2313-0105).

Deadline for manuscript submissions: closed (31 July 2021) | Viewed by 24289

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editors

Prof. Dr. Kai Peter Birke
E-Mail Website
Guest Editor
Chair for Electrical Energy Storage Systems, Institute for Photovoltaics, University of Stuttgart, Pfaffenwaldring 47, 70569 Stuttgart, Germany
Interests: battery cell research; battery system technology; battery block building kits; modeling of battery cells and battery systems; battery state estimation (state of charge, state of health, state of function); implementation of artificial intelligence for detrmination of battery cell parameters with enhanced accuracy; digital twins for battery cells and battery systems; high boiling point safety enhanced electrolytes; double layer capacitors; pseudo 3D-capacitors; power to X (X = gas, liquid, solid)
Special Issues, Collections and Topics in MDPI journals
Dr. Duygu Karabelli
E-Mail Website
Guest Editor
Center for Battery Cell Manufacturing, Fraunhofer Institute for Manufacturing Engineering and Automation IPA, Nobelstraße 12, 70569 Stuttgart, Germany
Interests: Li-ion batteries; next generation Li-S and Li-air batteries; solid-state batteries; polymer electrolytes; battery production; industry 4.0

Special Issue Information

Dear Colleagues,

Nowadays, the transformation from the combustion engine to electrified vehicles is a matter of fact and tremendously drives the demand for compact, high energy-density rechargeable lithium ion batteries as well for large stationary batteries to buffer solar and wind energy. The future challenges, e.g., decarbonization of the CO2 intensive transportation sector, will push the need for such batteries even more.

The cost of lithium ion batteries has become competitive in the last few years, and lithium ion batteries are expected to dominate the battery market in the next decade. However, despite remarkable progress, there is still a strong need for improvements in lithium ion batteries’ performance. Further improvements are not only expected in the field of electrochemistry but can also be distinctly pushed by improved manufacturing methods, diagnostic algorithms, lifetime prediction methods, implementation of artificial intelligence, and digital twins. Therefore, this Special Issue addresses the progress in battery and energy storage development by pushing a missing focus on digitalization, advanced cell production, modeling, and prediction aspects in concordance with progresses in new materials and pack design solutions.

Potential topics include but are not limited to:

  • Electrical, thermal, and electrochemical modeling;
  • Lifetime estimation of battery cells;
  • Accuracy enhancement methods for battery states and life time estimation;
  • Implementation of artificial intelligence in battery diagnostics;
  • Digital Twins for battery cells;
  • Digital Twins for battery systems;
  • Digital Twins in advanced battery productions;
  • New materials and advanced manufacturing methods in battery cell production;
  • Cell size optimization for advanced Li-ion batteries;
  • Battery cell and pack design;
  • Advanced electrolytes for Li-based batteries;
  • Advances in battery cell manufacturing technologies;
  • Life cycle assessment.

Prof. Dr.-Ing. Kai Peter Birke
Dr.-Ing. Duygu Kaus
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. 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.

Published Papers (18 papers)

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Research

Article
Lithium-Ion Battery Thermal Management Systems: A Survey and New CFD Results
Batteries 2021, 7(4), 86; https://doi.org/10.3390/batteries7040086 - 14 Dec 2021
Cited by 1 | Viewed by 1297
Abstract
The environment has gained significant importance in recent years, and companies involved in several technology fields are moving in the direction of eco-friendly solutions. One of the most discussed topics in the automotive field is lithium-ion battery packs for electric vehicles and their [...] Read more.
The environment has gained significant importance in recent years, and companies involved in several technology fields are moving in the direction of eco-friendly solutions. One of the most discussed topics in the automotive field is lithium-ion battery packs for electric vehicles and their battery thermal management systems (BTMSs). This work aims to show the most used lithium-ion battery pack cooling methods and technologies with best working temperature ranges together with the best performances. Different cooling methods are presented and discussed, with a focus on the comparison between air-cooling systems and liquid-cooling systems. In this context, a BTMS for cylindrical cells is presented, where the cells are arranged in staggered lines embedded in a solid structure and cooled through forced convection within channels. The thermal behavior of this BTMS is simulated by employing a computational fluid dynamics (CFD) approach. The effect of the geometry of the BTMS on the cell temperature distribution is obtained. It is shown that the use of materials with additives for the solid structure enhances the performance of the system, giving lower temperatures to the cells. The system is tested with air-cooling and water-cooling, showing that the best performances are obtained with water-cooling in terms of cell packing density and lowest cell temperatures. Full article
(This article belongs to the Special Issue Battery Systems and Energy Storage beyond 2020)
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Article
Impedance Based Temperature Estimation of Lithium Ion Cells Using Artificial Neural Networks
Batteries 2021, 7(4), 85; https://doi.org/10.3390/batteries7040085 - 12 Dec 2021
Cited by 1 | Viewed by 876
Abstract
Tracking the cell temperature is critical for battery safety and cell durability. It is not feasible to equip every cell with a temperature sensor in large battery systems such as those in electric vehicles. Apart from this, temperature sensors are usually mounted on [...] Read more.
Tracking the cell temperature is critical for battery safety and cell durability. It is not feasible to equip every cell with a temperature sensor in large battery systems such as those in electric vehicles. Apart from this, temperature sensors are usually mounted on the cell surface and do not detect the core temperature, which can mean detecting an offset due to the temperature gradient. Many sensorless methods require great computational effort for solving partial differential equations or require error-prone parameterization. This paper presents a sensorless temperature estimation method for lithium ion cells using data from electrochemical impedance spectroscopy in combination with artificial neural networks (ANNs). By training an ANN with data of 28 cells and estimating the cell temperatures of eight more cells of the same cell type, the neural network (a simple feed forward ANN with only one hidden layer) was able to achieve an estimation accuracy of ΔT= 1 K (10 C <T< 60 C) with low computational effort. The temperature estimations were investigated for different cell types at various states of charge (SoCs) with different superimposed direct currents. Our method is easy to use and can be completely automated, since there is no significant offset in monitoring temperature. In addition, the prospect of using the above mentioned approach to estimate additional battery states such as SoC and state of health (SoH) is discussed. Full article
(This article belongs to the Special Issue Battery Systems and Energy Storage beyond 2020)
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Article
Implementation of Battery Digital Twin: Approach, Functionalities and Benefits
Batteries 2021, 7(4), 78; https://doi.org/10.3390/batteries7040078 - 16 Nov 2021
Viewed by 1233
Abstract
The concept of Digital Twin (DT) is widely explored in literature for different application fields because it promises to reduce design time, enable design and operation optimization, improve after-sales services and reduce overall expenses. While the perceived benefits strongly encourage the use of [...] Read more.
The concept of Digital Twin (DT) is widely explored in literature for different application fields because it promises to reduce design time, enable design and operation optimization, improve after-sales services and reduce overall expenses. While the perceived benefits strongly encourage the use of DT, in the battery industry a consistent implementation approach and quantitative assessment of adapting a battery DT is missing. This paper is a part of an ongoing study that investigates the DT functionalities and quantifies the DT-attributes across the life cycles phases of a battery system. The critical question is whether battery DT is a practical and realistic solution to meeting the growing challenges of the battery industry, such as degradation evaluation, usage optimization, manufacturing inconsistencies or second-life application possibility. Within the scope of this paper, a consistent approach of DT implementation for battery cells is presented, and the main functions of the approach are tested on a Doyle-Fuller-Newman model. In essence, a battery DT can offer improved representation, performance estimation, and behavioral predictions based on real-world data along with the integration of battery life cycle attributes. Hence, this paper identifies the efforts for implementing a battery DT and provides the quantification attribute for future academic or industrial research. Full article
(This article belongs to the Special Issue Battery Systems and Energy Storage beyond 2020)
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Article
A Method for Monitoring State-of-Charge of Lithium-Ion Cells Using Multi-Sine Signal Excitation
Batteries 2021, 7(4), 76; https://doi.org/10.3390/batteries7040076 - 09 Nov 2021
Cited by 2 | Viewed by 923
Abstract
In this paper, a method for monitoring SoC of a lithium-ion battery cell through continuous impedance measurement during cell operation is introduced. A multi-sine signal is applied to the cell operating current, and the cell SoH and SoC can be simultaneously monitored via [...] Read more.
In this paper, a method for monitoring SoC of a lithium-ion battery cell through continuous impedance measurement during cell operation is introduced. A multi-sine signal is applied to the cell operating current, and the cell SoH and SoC can be simultaneously monitored via impedance at each frequency. Unlike existing studies in which cell impedance measurement is performed ex situ through EIS equipment, cell state estimation is performed in situ. The measured impedance takes into account cell temperature and cell SoH, enabling accurate SoC estimation. The measurement system configured for the experiment and considerations for the selection of measurement parameters are described, and the accuracy of cell SoC estimation is presented. Full article
(This article belongs to the Special Issue Battery Systems and Energy Storage beyond 2020)
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Article
Optimization of Disassembly Strategies for Electric Vehicle Batteries
Batteries 2021, 7(4), 74; https://doi.org/10.3390/batteries7040074 - 07 Nov 2021
Cited by 1 | Viewed by 1237
Abstract
Various studies show that electrification, integrated into a circular economy, is crucial to reach sustainable mobility solutions. In this context, the circular use of electric vehicle batteries (EVBs) is particularly relevant because of the resource intensity during manufacturing. After reaching the end-of-life phase, [...] Read more.
Various studies show that electrification, integrated into a circular economy, is crucial to reach sustainable mobility solutions. In this context, the circular use of electric vehicle batteries (EVBs) is particularly relevant because of the resource intensity during manufacturing. After reaching the end-of-life phase, EVBs can be subjected to various circular economy strategies, all of which require the previous disassembly. Today, disassembly is carried out manually and represents a bottleneck process. At the same time, extremely high return volumes have been forecast for the next few years, and manual disassembly is associated with safety risks. That is why automated disassembly is identified as being a key enabler of highly efficient circularity. However, several challenges need to be addressed to ensure secure, economic, and ecological disassembly processes. One of these is ensuring that optimal disassembly strategies are determined, considering the uncertainties during disassembly. This paper introduces our design for an adaptive disassembly planner with an integrated disassembly strategy optimizer. Furthermore, we present our optimization method for obtaining optimal disassembly strategies as a combination of three decisions: (1) the optimal disassembly sequence, (2) the optimal disassembly depth, and (3) the optimal circular economy strategy at the component level. Finally, we apply the proposed method to derive optimal disassembly strategies for one selected battery system for two condition scenarios. The results show that the optimization of disassembly strategies must also be used as a tool in the design phase of battery systems to boost the disassembly automation and thus contribute to achieving profitable circular economy solutions for EVBs. Full article
(This article belongs to the Special Issue Battery Systems and Energy Storage beyond 2020)
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Article
Investigation of a Novel Ecofriendly Electrolyte-Solvent for Lithium-Ion Batteries with Increased Thermal Stability
Batteries 2021, 7(4), 72; https://doi.org/10.3390/batteries7040072 - 28 Oct 2021
Viewed by 823
Abstract
This study presents tributyl acetylcitrate (TBAC) as a novel ecofriendly high flash point and high boiling point solvent for electrolytes in lithium-ion batteries. The flash point (TFP=217C) and the boiling point (TBP=331 [...] Read more.
This study presents tributyl acetylcitrate (TBAC) as a novel ecofriendly high flash point and high boiling point solvent for electrolytes in lithium-ion batteries. The flash point (TFP=217C) and the boiling point (TBP=331C) of TBAC are approximately 200 K greater than that of conventional linear carbonate components, such as ethyl methyl carbonate (EMC) or diethyl carbonate (DEC). The melting point (TMP=80C) is more than 100 K lower than that of ethylene carbonate (EC). Furthermore, TBAC is known as an ecofriendly solvent from other industrial sectors. A life cycle test of a graphite/NCM cell with 1 M lithium hexafluorophosphate (LiPF6) in TBAC:EC:EMC:DEC (60:15:5:20 wt) achieved a coulombic efficiency of above 99% and the remaining capacity resulted in 90 percent after 100 cycles (C/4) of testing. As a result, TBAC is considered a viable option for improving the thermal stability of lithium-ion batteries. Full article
(This article belongs to the Special Issue Battery Systems and Energy Storage beyond 2020)
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Article
Thermal Runaway Modelling of Li-Ion Cells at Various States of Ageing with a Semi-Empirical Model Based on a Kinetic Equation
Batteries 2021, 7(4), 68; https://doi.org/10.3390/batteries7040068 - 18 Oct 2021
Cited by 1 | Viewed by 970
Abstract
The thermal runaway model used is a semi-empirical model based on a kinetic equation, parametrised by three parameters (m,n,p). It is believed that this kinetic equation can describe any reaction. The choice of parameters is often [...] Read more.
The thermal runaway model used is a semi-empirical model based on a kinetic equation, parametrised by three parameters (m,n,p). It is believed that this kinetic equation can describe any reaction. The choice of parameters is often made without justifications. We assumed it necessary to develop a method to select the parameters. The method proposed is based on data coming from an accelerating rate calorimeter (ARC) test. The method has been applied on data obtained for cells aged on different conditions. Thanks to a post-mortem analysis and simulations carried out using the parameters obtained, we have shown that the ageing mechanisms have a major impact on the parameters. Full article
(This article belongs to the Special Issue Battery Systems and Energy Storage beyond 2020)
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Article
Influence of Temperature and Electrolyte Composition on the Performance of Lithium Metal Anodes
Batteries 2021, 7(4), 67; https://doi.org/10.3390/batteries7040067 - 14 Oct 2021
Viewed by 1082
Abstract
Lithium metal anodes have again attracted widespread attention due to the continuously growing demand of cells with higher energy density. However, the lithium deposition mechanism and the affecting process of influencing factors, such as temperature, cycling current density, and electrolyte composition are not [...] Read more.
Lithium metal anodes have again attracted widespread attention due to the continuously growing demand of cells with higher energy density. However, the lithium deposition mechanism and the affecting process of influencing factors, such as temperature, cycling current density, and electrolyte composition are not fully understood and require further investigation. In this article, the behavior of lithium metal anode at different temperatures (25, 40, and 60 C), lithium salts, electrolyte concentrations (1 and 2 M), and the applied cell current (equivalent to 0.5 C, 1 C, and 2 C). is investigated. Two different salts were evaluated: lithium bis(fluorosulfonyl)imide (LiFSI) and lithium bis(trifluoromethanesul-fonyl)imide (LiTFSI). The cells at a medium temperature (40 C) show the highest Coulombic efficiency (CE). However, shorter cycle life is observed compared to the experiments at room temperature (25 C). Regardless of electrolyte type and C-rate, the higher temperature of 60 C provides the worst Coulombic efficiency and cycle life among those at the examined temperatures. A higher C-rate has a positive effect on the stability over the cycle life of the lithium cells. The best performance in terms of long cycle life and relatively good Coulombic efficiency is achieved by fast charging the cell with high concentration LiFSI in 1,2-dimethoxyethane (DME) electrolyte at a temperature of 25 C. The cell has an average Coulombic efficiency of 0.987 over 223 cycles. In addition to galvanostatic experiments, Electrochemical Impedance Spectroscopy (EIS) measurements were performed to study the evolution of the interface under different conditions during cycling. Full article
(This article belongs to the Special Issue Battery Systems and Energy Storage beyond 2020)
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Article
Power and Energy Rating Considerations in Integration of Flow Battery with Solar PV and Residential Load
Batteries 2021, 7(3), 62; https://doi.org/10.3390/batteries7030062 - 08 Sep 2021
Cited by 2 | Viewed by 754
Abstract
Integration of renewable energy sources such as solar photovoltaic (PV) generation with variable power demand systems like residential electricity consumption requires the use of a high efficiency electrical energy system such as a battery. In the present study, such integration has been studied [...] Read more.
Integration of renewable energy sources such as solar photovoltaic (PV) generation with variable power demand systems like residential electricity consumption requires the use of a high efficiency electrical energy system such as a battery. In the present study, such integration has been studied using vanadium redox flow battery (VRFB) as the energy storage system with specific focus on the sizing of the power and energy storage capacities of the system components. Experiments have been carried out with a seven-day simulated solar insolation and residential load characteristics using a 1 kW VRFB stack and variable amounts of electrolyte volume. Several scenarios have been simulated using power and energy scale factors. Battery response, in terms of its power, state of charge and efficiency, has been monitored in each run. Results show that the stack power rating should be based on peak charging characteristics while the volume of electrolyte should be based on the expected daily energy discharge through the battery. The PV source itself should be sized at about 25% more energy rating than the average daily load. The ability to design a VRFB with a high power-to-energy ratio makes it particularly attractive for PV-load integration. Full article
(This article belongs to the Special Issue Battery Systems and Energy Storage beyond 2020)
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Article
Non-Uniform Circumferential Expansion of Cylindrical Li-Ion Cells—The Potato Effect
Batteries 2021, 7(3), 61; https://doi.org/10.3390/batteries7030061 - 06 Sep 2021
Cited by 2 | Viewed by 1233
Abstract
This paper presents the non-uniform change in cell thickness of cylindrical Lithium (Li)-ion cells due to the change of State of Charge (SoC). Using optical measurement methods, with the aid of a laser light band micrometer, the expansion and contraction are determined over [...] Read more.
This paper presents the non-uniform change in cell thickness of cylindrical Lithium (Li)-ion cells due to the change of State of Charge (SoC). Using optical measurement methods, with the aid of a laser light band micrometer, the expansion and contraction are determined over a complete charge and discharge cycle. The cell is rotated around its own axis by an angle of α=10° in each step, so that the different positions can be compared with each other over the circumference. The experimental data show that, contrary to the assumption based on the physical properties of electrode growth due to lithium intercalation in the graphite, the cell does not expand uniformly. Depending on the position and orientation of the cell coil, there are different zones of expansion and contraction. In order to confirm the non-uniform expansion around the circumference of the cell in 3D, X-ray computed tomography (CT) scans of the cells are performed at low and at high SoC. Comparison of the high resolution 3D reconstructed volumes clearly visualizes a sinusoidal pattern for non-uniform expansion. From the 3D volume, it can be confirmed that the thickness variation does not vary significantly over the height of the battery cell due to the observed mechanisms. However, a slight decrease in the volume change towards the poles of the battery cells due to the higher stiffness can be monitored. Full article
(This article belongs to the Special Issue Battery Systems and Energy Storage beyond 2020)
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Article
Versatile AC Current Control Technique for a Battery Using Power Converters
Batteries 2021, 7(3), 47; https://doi.org/10.3390/batteries7030047 - 15 Jul 2021
Viewed by 969
Abstract
Although a battery is a DC device, AC current is often necessary for testing, preheating, impedance spectroscopy, and advanced charging. This paper presents a versatile control technique to inject AC current to a battery. Synchronous buck and H-bridge topologies are operated in bidirectional [...] Read more.
Although a battery is a DC device, AC current is often necessary for testing, preheating, impedance spectroscopy, and advanced charging. This paper presents a versatile control technique to inject AC current to a battery. Synchronous buck and H-bridge topologies are operated in bidirectional mode and controlled by uni-polar and bi-polar pulse width modulation techniques for the AC current injection. The input and output passive circuits are specially designed considering AC current and the properties of the battery. A controller is proposed considering a small internal impedance, small AC ripple voltage, and variable DC offset voltage of a battery. The controller is capable of maintaining stable operation of AC current injection in two power quadrant within a small DC voltage boundary of a battery. The controller is comprised of a feedback compensator, a feedforward term, and an estimator. The feedback gain is designed considering the internal impedance. The feedforward gain is designed based on estimated open circuit battery voltage and input voltage. The open circuit voltage estimator is designed based on filters and battery model. For validation, AC current is injected to a Valence U-12XP battery. The battery is rated for 40 Ah nominal capacity and 13.8 V nominal voltage The controller successfully injected AC current to a battery with +10 A, 0 A and −10 A DC currents. The magnitude and frequency of the AC current was up to 5 A and 2 kHz respectively. Full article
(This article belongs to the Special Issue Battery Systems and Energy Storage beyond 2020)
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Article
Comparison of Aqueous- and Non-Aqueous-Based Binder Polymers and the Mixing Ratios for Zn//MnO2 Batteries with Mildly Acidic Aqueous Electrolytes
Batteries 2021, 7(2), 40; https://doi.org/10.3390/batteries7020040 - 18 Jun 2021
Cited by 3 | Viewed by 1343
Abstract
Considering the literature for aqueous rechargeable Zn//MnO2 batteries with acidic electrolytes using the doctor blade coating of the active material (AM), carbon black (CB), and binder polymer (BP) for the positive electrode fabrication, different binder types with (non-)aqueous solvents were introduced so [...] Read more.
Considering the literature for aqueous rechargeable Zn//MnO2 batteries with acidic electrolytes using the doctor blade coating of the active material (AM), carbon black (CB), and binder polymer (BP) for the positive electrode fabrication, different binder types with (non-)aqueous solvents were introduced so far. Furthermore, in most of the cases, relatively high passive material (CB+BP) shares ~30 wt% were applied. The first part of this work focuses on different selected BPs: polyacrylonitrile (PAN), carboxymethyl cellulose (CMC), styrene butadiene rubber (SBR), cellulose acetate (CA), and nitrile butadiene rubber (NBR). They were used together with (non-)aqueous solvents: DI-water, methyl ethyl ketone (MEK), and dimethyl sulfoxide (DMSO). By performing mechanical, electrochemical and optical characterizations, a better overall performance of the BPs using aqueous solvents was found in aqueous 2 M ZnSO4 + 0.1 M MnSO4 electrolyte (i.e., BP LA133: 150 mAh·g−1 and 189 mWh·g−1 @ 160 mA·g−1). The second part focuses on the mixing ratio of the electrode components, aiming at the decrease of the commonly used passive material share of ~30 wt% for an industrial-oriented electrode fabrication, while still maintaining the electrochemical performance. Here, the absolute CB share and the CB/BP ratio are found to be important parameters for an application-oriented electrode fabrication (i.e., high energy/power applications). Full article
(This article belongs to the Special Issue Battery Systems and Energy Storage beyond 2020)
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Article
Methodology for Determining Time-Dependent Lead Battery Failure Rates from Field Data
Batteries 2021, 7(2), 39; https://doi.org/10.3390/batteries7020039 - 15 Jun 2021
Cited by 3 | Viewed by 1006
Abstract
The safety requirements in vehicles continuously increase due to more automated functions using electronic components. Besides the reliability of the components themselves, a reliable power supply is crucial for a safe overall system. Different architectures for a safe power supply consider the lead [...] Read more.
The safety requirements in vehicles continuously increase due to more automated functions using electronic components. Besides the reliability of the components themselves, a reliable power supply is crucial for a safe overall system. Different architectures for a safe power supply consider the lead battery as a backup solution for safety-critical applications. Various ageing mechanisms influence the performance of the battery and have an impact on its reliability. In order to qualify the battery with its specific failure modes for use in safety-critical applications, it is necessary to prove this reliability by failure rates. Previous investigations determine the fixed failure rates of lead batteries using data from teardown analyses to identify the battery failure modes but did not include the lifetime of these batteries examined. Alternatively, lifetime values of battery replacements in workshops without knowing the reason for failure were used to determine the overall time-dependent failure rate. This study presents a method for determining reliability models of lead batteries by investigating individual failure modes. Since batteries are subject to ageing, the analysis of lifetime values of different failure modes results in time-dependent failure rates of different magnitudes. The failure rates of the individual failure modes develop with different shapes over time, which allows their ageing behaviour to be evaluated. Full article
(This article belongs to the Special Issue Battery Systems and Energy Storage beyond 2020)
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Article
Determination of the Distribution of Relaxation Times by Means of Pulse Evaluation for Offline and Online Diagnosis of Lithium-Ion Batteries
Batteries 2021, 7(2), 36; https://doi.org/10.3390/batteries7020036 - 01 Jun 2021
Cited by 3 | Viewed by 1803
Abstract
The distribution of relaxation times (DRT) analysis of impedance spectra is a proven method to determine the number of occurring polarization processes in lithium-ion batteries (LIBs), their polarization contributions and characteristic time constants. Direct measurement of a spectrum by means of electrochemical impedance [...] Read more.
The distribution of relaxation times (DRT) analysis of impedance spectra is a proven method to determine the number of occurring polarization processes in lithium-ion batteries (LIBs), their polarization contributions and characteristic time constants. Direct measurement of a spectrum by means of electrochemical impedance spectroscopy (EIS), however, suffers from a high expenditure of time for low-frequency impedances and a lack of general availability in most online applications. In this study, a method is presented to derive the DRT by evaluating the relaxation voltage after a current pulse. The method was experimentally validated using both EIS and the proposed pulse evaluation to determine the DRT of automotive pouch-cells and an aging study was carried out. The DRT derived from time domain data provided improved resolution of processes with large time constants and therefore enabled changes in low-frequency impedance and the correlated degradation mechanisms to be identified. One of the polarization contributions identified could be determined as an indicator for the potential risk of plating. The novel, general approach for batteries was tested with a sampling rate of 10 Hz and only requires relaxation periods. Therefore, the method is applicable in battery management systems and contributes to improving the reliability and safety of LIBs. Full article
(This article belongs to the Special Issue Battery Systems and Energy Storage beyond 2020)
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Article
Advanced Monitoring and Prediction of the Thermal State of Intelligent Battery Cells in Electric Vehicles by Physics-Based and Data-Driven Modeling
Batteries 2021, 7(2), 31; https://doi.org/10.3390/batteries7020031 - 11 May 2021
Cited by 6 | Viewed by 1797
Abstract
Novel intelligent battery systems are gaining importance with functional hardware on the cell level. Cell-level hardware allows for advanced battery state monitoring and thermal management, but also leads to additional thermal interactions. In this work, an electro-thermal framework for the modeling of these [...] Read more.
Novel intelligent battery systems are gaining importance with functional hardware on the cell level. Cell-level hardware allows for advanced battery state monitoring and thermal management, but also leads to additional thermal interactions. In this work, an electro-thermal framework for the modeling of these novel intelligent battery cells is provided. Thereby, a lumped thermal model, as well as a novel neural network, are implemented in the framework as thermal submodels. For the first time, a direct comparison of a physics-based and a data-driven thermal battery model is performed in the same framework. The models are compared in terms of temperature estimation with regard to accuracy. Both models are very well suited to represent the thermal behavior in novel intelligent battery cells. In terms of accuracy and computation time, however, the data-driven neural network approach with a Nonlinear AutoregRessive network with eXogeneous input (NARX) shows slight advantages. Finally, novel applications of temperature prediction in battery electric vehicles are presented and the applicability of the models is illustrated. Thereby, the conventional prediction of the state of power is extended by simultaneous temperature prediction. Additionally, temperature forecasting is used for pre-conditioning by advanced cooling system regulation to enable energy efficiency and fast charging. Full article
(This article belongs to the Special Issue Battery Systems and Energy Storage beyond 2020)
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Article
Global Warming Potential of a New Waterjet-Based Recycling Process for Cathode Materials of Lithium-Ion Batteries
Batteries 2021, 7(2), 29; https://doi.org/10.3390/batteries7020029 - 01 May 2021
Viewed by 1499
Abstract
Due to the increasing demand for battery electric vehicles (BEVs), the need for vehicle battery raw materials is increasing. The traction battery (TB) of an electric vehicle, usually a lithium-ion battery (LIB), represents the largest share of a BEV’s CO2 footprint. To [...] Read more.
Due to the increasing demand for battery electric vehicles (BEVs), the need for vehicle battery raw materials is increasing. The traction battery (TB) of an electric vehicle, usually a lithium-ion battery (LIB), represents the largest share of a BEV’s CO2 footprint. To reduce this carbon footprint sustainably and to keep the raw materials within a closed loop economy, suitable and efficient recycling processes are essential. In this life cycle assessment (LCA), the ecological performance of a waterjet-based direct recycling process with minimal use of resources and energy is evaluated; only the recycling process is considered, waste treatment and credits for by-products are not part of the analysis. Primary data from a performing recycling company were mainly used for the modelling. The study concludes that the recycling of 1 kg of TB is associated with a global warming potential (GWP) of 158 g CO2 equivalents (CO2e). Mechanical removal using a water jet was identified as the main driver of the recycling process, followed by an air purification system. Compared to conventional hydro- or pyrometallurgical processes, this waterjet-based recycling process could be attributed an 8 to 26 times lower GWP. With 10% and 20% reuse of recyclate in new cells, the GWP of TBs could be reduced by 4% and 8%, respectively. It has been shown that this recycling approach can be classified as environmentally friendly. Full article
(This article belongs to the Special Issue Battery Systems and Energy Storage beyond 2020)
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Article
Effect of Vinylene Carbonate Electrolyte Additive on the Surface Chemistry and Pseudocapacitive Sodium-Ion Storage of TiO2 Nanosheet Anodes
Batteries 2021, 7(1), 1; https://doi.org/10.3390/batteries7010001 - 24 Dec 2020
Cited by 6 | Viewed by 1719
Abstract
Although titanium dioxide has gained much attention as a sodium-ion battery anode material, obtaining high specific capacity and cycling stability remains a challenge. Herein, we report significantly improved surface chemistry and pseudocapacitive Na-ion storage performance of TiO2 nanosheet anode in vinylene carbonate [...] Read more.
Although titanium dioxide has gained much attention as a sodium-ion battery anode material, obtaining high specific capacity and cycling stability remains a challenge. Herein, we report significantly improved surface chemistry and pseudocapacitive Na-ion storage performance of TiO2 nanosheet anode in vinylene carbonate (VC)-containing electrolyte solution. In addition to the excellent pseudocapacitance (~87%), the TiO2 anodes also exhibited increased high-specific capacity (219 mAh/g), rate performance (40 mAh/g @ 1 A/g), coulombic efficiency (~100%), and cycling stability (~90% after 750 cycles). Spectroscopic and microscopic studies confirmed polycarbonate based solid electrolyte interface (SEI) formation in VC-containing electrolyte solution. The superior electrochemical performance of the TiO2 nanosheet anode in VC-containing electrolyte solution is credited to the improved pseudocapacitive Na-ion diffusion through the polycarbonate based SEI (coefficients of 1.65 × 10−14 for PC-VC vs. 6.42 × 10−16 for PC). This study emphasizes the crucial role of the electrolyte solution and electrode–electrolyte interfaces in the improved pseudocapacitive Na-ion storage performance of TiO2 anodes. Full article
(This article belongs to the Special Issue Battery Systems and Energy Storage beyond 2020)
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Article
Optimal Siting and Sizing of Battery Energy Storage Systems for Distribution Network of Distribution System Operators
Batteries 2020, 6(4), 56; https://doi.org/10.3390/batteries6040056 - 19 Nov 2020
Cited by 10 | Viewed by 1723
Abstract
In this work, optimal siting and sizing of a battery energy storage system (BESS) in a distribution network with renewable energy sources (RESs) of distribution network operators (DNO) are presented to reduce the effect of RES fluctuations for power generation reliability and quality. [...] Read more.
In this work, optimal siting and sizing of a battery energy storage system (BESS) in a distribution network with renewable energy sources (RESs) of distribution network operators (DNO) are presented to reduce the effect of RES fluctuations for power generation reliability and quality. The optimal siting and sizing of the BESS are found by minimizing the costs caused by the voltage deviations, power losses, and peak demands in the distribution network for improving the performance of the distribution network. The simulation results of the BESS installation were evaluated in the IEEE 33-bus distribution network. Genetic algorithm (GA) and particle swarm optimization (PSO) were adopted to solve this optimization problem, and the results obtained from these two algorithms were compared. After the BESS installation in the distribution network, the voltage deviations, power losses, and peak demands were reduced when compared to those of the case without BESS installation. Full article
(This article belongs to the Special Issue Battery Systems and Energy Storage beyond 2020)
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