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Energy storage systems with Li-ion batteries are increasingly deployed to maintain a robust and resilient grid and facilitate the integration of renewable energy resources. However, appropriate selection of cells for different applications is difficult due to limited public data comparing the most commonly used off-the-shelf Li-ion chemistries unde...
Contexts in source publication
Context 1
... three batteries were selected because they included common electrode formulations and were manufactured by reputable companies. Table 1 provides additional specifications for each cell, including the manufacturer-recommended operating bounds. ...Context 2
... NCA cathode is likely Ni0.81Co0.14Al0.05. A description of the ICP-OES procedure is provided below and the raw data is given in Table S1. ...Context 3
... to analysis, samples of the active material on the Al current collector were digested using a Mars 6 (CEM Corporation) extraction system. Microwave 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t ...Context 4
... round of cycling consisted of a capacity check, some number of cycles at the designated conditions for that cell, and another capacity check at the end (Scheme 1). The capacity check consisted of three charge/discharge cycles from 0-100% SOC at 0.5C (a rate of 1C corresponds to the current that will discharge the full capacity of a battery in one Journal of The Electrochemical Society 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t ...Context 5
... value was calculated by summing the energy from each individual discharge of the cell. The performance differences between the three chemistries were minimized once the analysis factored in the lower capacity and voltage of the LFP cells (see Table 1). ...Context 6
... decrease in RTE across all cycling conditions as the cells reach 80% capacity is attributed to the increase in cell resistance as the SEI layer grows. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t ...Context 7
... example, previous reports on cycle aging of LFP cells indicate a tipping point at temperatures of 5-10°C, with degradation rates increasing both above and below this temperature. 26 Studies of LFP cells that 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t ...Context 8
... Newly-formed cracks enable further reaction between the electrolyte and Li, leading to more SEI formation, loss of Li inventory, and capacity fade. Some studies have shown that only the width of the 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t ...Context 9
... In Fig. 3g-h, the discharge rate dependence for NMC and LFP cells appears low. However, for NCA cells, capacity fade decreased with increasing discharge rate (Fig. 3i) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t ...Context 10
... of the four factors (cell chemistry, discharge rate, and SOC range) were found to be significant in explaining variability in % capacity. The p values from ANOVA, 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t 5 shows the main effects and interactions plot for all four factors, demonstrating the importance of not drawing general conclusions about variable dependence for different chemistries. ...Context 11
... variations in materials, such as electrolyte composition, can substantially impact battery lifetime (though that level of detail would not be available to a system installer relying on a basic battery specification sheet). Empirical battery degradation models would benefit from the incorporation of larger 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t ...Context 12
... results illustrate the value of varying multiple temperatures within a normal operating range rather than looking solely at extreme temperatures. The gap in preferred conditions for LFP 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t ...Context 13
... Contributions: The Electrochemical Society 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t ...Context 14
... authors participated in discussion of the results, as well as the preparation of the paper. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t 40-60%, 25°C, 0.5C 0-100%, 15°C, 1C 0-100%, 15°C, 2C 40-60%, 25°C, 3C ...Context 15
... Journal of The Electrochemical Society 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t The Electrochemical Society 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t Figure 2. (a) Equivalent full cycle (EFC) count at 80% capacity for all cells and cycling conditions. Each bar represents the average EFC for all cells cycled at that condition. ...Context 16
... Journal of The Electrochemical Society 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t The Electrochemical Society 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t Figure 2. (a) Equivalent full cycle (EFC) count at 80% capacity for all cells and cycling conditions. Each bar represents the average EFC for all cells cycled at that condition. ...Context 17
... Journal of The Electrochemical Society 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t The Electrochemical Society 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t Figure 2. (a) Equivalent full cycle (EFC) count at 80% capacity for all cells and cycling conditions. Each bar represents the average EFC for all cells cycled at that condition. ...Context 18
... not yet reached 80% capacity. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t The Electrochemical Society 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t Table 3. Summary of studies examining temperature, depth of discharge, and discharge rate dependence in commercial cells (cylindrical format, unless otherwise noted). 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t Cycling conditions held constant listed in the order of: temperature, depth of discharge given as SOC or voltage range, and charge/discharge rate. 2 Better performance corresponds to a lower degradation rate. ...Context 19
... not yet reached 80% capacity. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t The Electrochemical Society 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t Table 3. Summary of studies examining temperature, depth of discharge, and discharge rate dependence in commercial cells (cylindrical format, unless otherwise noted). 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t Cycling conditions held constant listed in the order of: temperature, depth of discharge given as SOC or voltage range, and charge/discharge rate. 2 Better performance corresponds to a lower degradation rate. ...Context 20
... not yet reached 80% capacity. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t The Electrochemical Society 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t Table 3. Summary of studies examining temperature, depth of discharge, and discharge rate dependence in commercial cells (cylindrical format, unless otherwise noted). 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t Cycling conditions held constant listed in the order of: temperature, depth of discharge given as SOC or voltage range, and charge/discharge rate. 2 Better performance corresponds to a lower degradation rate. ...Context 21
... Journal of The Electrochemical Society 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t discharge rate is shown in red for NMC cells and blue for LFP cells. Figure 5. Main effects (a-d) and interactions (e-g) plots for model fit at 200 EFC. ...Context 22
... Journal of The Electrochemical Society 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t given as DOD, temperature, and charge/discharge rate, are noted for each plot. For each data set, the year of publication, cell manufacturer, cell capacity, and number of cells cycled under the specified conditions are noted (when provided in the original publication). ...Context 23
... Journal of The Electrochemical Society 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t ...Context 24
... Journal of The Electrochemical Society 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t ...Similar publications
We studied the photocatalytic degradation of 2-chloroethyl ethyl sulfide (CEES) by three kinds of MOFs (ZIF-8, NTU-9 and MOF-525). Among the three kinds of MOFs, NTU-9 and MOF-525 can selectively photocatalytic oxidize CEES to 2-chloroethyl ethyl sulfoxide (CEESO). And MOF-525 showed higher catalytic activity.
![Figure 1.-Normal regions and anomalies data, [3]](publication/343860624/figure/fig1/AS:934099288080395@1599718033468/Normal-regions-and-anomalies-data-3_Q320.jpg)
This paper aimed to validate a working tool, component of the Predictive Maintenance Toolbox ™, produced by Matlab (MathWorks), in the case of a procedure for monitoring the operation of mechanical systems, in order to diagnose a failure of the process and to estimate the remaining useful life (RUL). This toolbox provides toolsets, materialized in...
Citations
... Battery system integrators are interested in understanding the useful cycle life of cells through a quick estimate with reasonable accuracy. Relevant literature (Diao, Saxena, and Pecht 2019;Preger et al. 2020) shows that in the range of temperature and discharge rates tested, the capacity fade trend can be fitted to a linear approximation. Therefore, a linear approximation was used for the predictions. ...
A cell’s ability to store energy, and produce power is limited by its capacity fading with age. This paper presents the findings on the performance characteristics of prismatic Lithium-iron phosphate (LiFePO4) cells under different ambient temperature conditions, discharge rates, and depth of discharge. The accelerated life cycle testing results depicted a linear degradation pattern of up to 300 cycles. Linear extrapolation reveals that at 25°C temperature, an increase in the discharge rate from 0.5 C to 0.8 C reduces the cycle life significantly by 52.9%. On the other hand, at a constant discharge rate, an increase in temperature reduced predicted cycle life in the range of 23.2–41.36%. Lithium-ion cells’ reliability modeling and analysis was carried out using an exponential distribution showing the increasing failure rate with age, with the temperature significantly reducing the expected life of the cells.
... 19,23,24 For this approach, a linearization of the aging rate is assumed. 18 However, many factors such as the C-Rate, 23,25,26 electrode thickness or energy density 23,25,26 and the cell chemistry 27 impact the dominant aging mechanism, which then dictates the temperature dependency. [25][26][27] Furthermore, the dominant aging mechanism can change over the lifetime. ...
... 18 However, many factors such as the C-Rate, 23,25,26 electrode thickness or energy density 23,25,26 and the cell chemistry 27 impact the dominant aging mechanism, which then dictates the temperature dependency. [25][26][27] Furthermore, the dominant aging mechanism can change over the lifetime. 28,29 For nonlinear capacity fade Kucinskis et al. 25 have proposed linearization of certain State of Health (SoH) regions, which can be visualized in a 2D aging color map. ...
In semi-empirical aging modeling of lithium ion-batteries an Arrhenius approach is commonly applied to describe the temperature dependency of a linear capacity loss. However, this dependency can change with degradation modes which was also observed in this cyclic aging study on NMC111-LMO graphite pouch cells in a temperature range of 4 °C to 48 °C. By means of differential voltage analysis and post-mortem analysis we correlated different regimes in capacity loss to degradation modes and aging mechanisms. In the first regime, a power dependency of time was observed. A second accelerated linear regime which followed an increase in loss of active material of the positive electrode was seen for medium (∼19 °C to 25 °C) to high aging temperatures. Transition metal dissolution was suggested to cause accelerated SEI growth. An activation energy could be estimated to 0.83 eV (± 0.17 eV, 95% CI). Finally, at aging temperatures around 45 °C we propose decreased charge transfer kinetics to result in mossy dendrites on the negative electrode which cause a final knee in aging trajectory. The findings highlight the necessity of sufficient aging temperatures and testing time.
... Li-ion battery packs are typically considered to reach their end-of-life when 20% of their initial capacity is lost. As LFP/G cells lifetime corresponds to around 7000 cycles, with a minimal state of charge of 10% (Preger et al. 2020;Harlow et al. 2019), it is assumed that the packs need to be replaced every 10 years. ...
... As NMC/G cells perform around 4000 cycles (from 1000 to 9000 cycles in (Preger et al. 2020;Harlow et al. 2019), a replacement of the packs every 5 years is considered as base case in this work. As for NMC/LTO packs, their lifetime can advantageously extend to around 27,000 cycles (Jaiswal 2017); therefore, it is assumed no replacement is needed over 20 years of service. ...
... In contrast, Munzke et al. (2021) investigated nine different home stationary storage systems and found an average maximum round-trip efficiency of 81.5% (Jasper et al. 2022). The Min and Max values for cell density and the number of cycles for each battery chemistry are based on literature when available (Preger et al. 2020;Harlow et al. 2019;CEA-Liten 2023;Battery University s.d.;Ha et al. 2021;Jaiswal 2017); if no value is found, authors run the sensitivity analysis with a 10% variation from the base value. Figure 7 presents the sensitivity analysis carried out for the three parameters in Table 2: (a) the batteries' number of cycles during its lifetime (and its associated replacing factor), (b) the cell energetic density as well as (c) the roundtrip efficiency. ...
Purpose
Along with the harvesting of renewable energy sources to decrease the environmental footprint of the energy sector, energy storage systems appear as a relevant solution to ensure a reliable and flexible electricity supply network. Lithium-ion (Li-ion) batteries are so far, the most widespread operational electrochemical storage system. The aim of this study is to address the lack of comprehensive cradle-to-grave environmental impact evaluation for stationary Li-ion batteries.
Materials and methods
Three stationary Li-ion batteries are assessed here: a prototype lithium iron phosphate/graphite (LFP/G) battery and two alternatives (with nickel manganese cobalt (NMC) positive electrodes and graphite (G) or lithium titanate oxide (LTO) negative electrodes). Midpoint to endpoint environmental indicators are estimated and compared using the life cycle assessment methodology. With the help of literature data, the modelling includes all auxiliary equipment (container, power electronics, etc.) and considers end-of-life (EoL) processes that are as specific as possible for each component. The evaluation accounts for two full charge equivalent per day for a 20-year period.
Results
The endpoint analysis does not enable to determine which of the NMC/G and LFP/G batteries has the lesser environmental impacts. A more detailed examination of the midpoint indicators is essential for making a choice between the two, as both present pros and cons. However, for both endpoint and midpoint indicators, the NMC/LTO battery is less impactful than the other batteries, particularly for critical categories (human toxicity, freshwater ecotoxicity and eutrophication) as it does not need any pack replacement and contains less copper. Auxiliary equipment does not contribute significantly to most of the cradle-to-grave environmental indicators, except for steel container recycling, which induces human carcinogenic toxicity. In all other categories, the screened EoL processes indicated potential net negative impacts, especially through the recycling of lithium compounds in LFP and LTO electrodes with adapted processes. Recovering the aluminium cell containers and electrode foils from dismantled cells is also significantly beneficial.
Discussions
This work provides a consistent comparison between three different battery storage systems including all auxiliary components and all life cycle stages. Reliability of the findings hinges on the selected inventories and parameters’ assumptions, most of which are derived from the literature. Sensitivity analysis has shown the significance of certain parameters, such as the battery pack’s lifespan, in determining the least impactful battery. Primary data on the battery use phase (lifespan, round-trip efficiency, depth-of-discharge) as well as a more detailed modelling of both auxiliary equipment and EoL processes would provide a more accurate picture of the associated environmental impacts. Finally, to make a choice, other criteria such as economic aspects, pack safety or criticality risks of materials should be considered.
Graphical Abstract
... Lithium-ion batteries are widely used because of their high energy density, low self-discharge, and long cycling life. However, batteries have limitations in charging/discharging C-rates, and lifespan, that is sensitive to temperature extremes [5], [6]. Additionally, its material sourcing and disposal pose environmental challenges [7]. ...
... To bridge this gap, hybrid solutions combining lithium-ion batteries and EDLCs, such as hybrid supercapacitors, have been developed to leverage the strengths of both technologies. Additionally, supercapacitors generally offer fast charging and discharging, up to 1,000,000 charge cycles, and a wide range of operating temperatures [5], [6], as summarized in Table 1-1. As presented in Table 1-1, EDLC supercapacitors outperform lithium-ion batteries in terms of power density and life cycles. ...
... The emerging market for Second-Life LiBs in energy storage has also potentially gained massive traction due to the clean energy transition [68]. However, in outdoor/off-grid settings, LiBs encounter performance-degradation limitations, especially when exposed to temperature fluctuations and subzero conditions [6], [69]. Additionally, the performance of LiBs degrades over time, leading to the need for over-sizing battery storage to compensate for capacity loss during the system's operational life [22], [70]. ...
Photovoltaic (PV) panels are the most used renewable source in both industrial and residential applications. Renewable sources such as solar and wind are intermittent, fluctuating power output, and it does not necessarily meet the consumption profile. Solving the intermittency issue comes by using energy storage (ES) for the generated electrical energy coming from the PV panels. Integrating ES directly into the PV panel offers benefits such as simplified system design and enhanced system flexibility. LiB is the most common and mature ES technology. Using Batteries as ES are known to have a shorter lifetime compared to solar panels and the power electronics lifetime, which makes the batteries the weakest link in the chain. Also using LiBs in outdoor conditions accelerates its degradation. For such outdoor applications requiring ES, supercapacitors emerge as a solution for making ES with a much longer cycling life, higher power density, and better safety when compared to LiB. While LiB is much affected by lower temperatures as the capacity drops and equivalent series resistance (ESR) increase and in higher temperatures the degradation of the LiB is accelerated, supercapacitors appear to be more tolerant to climatic variables. Supercapacitors such as Electrostatic double-layer capacitors (EDLCs) store energy in the form of an electric field, which is not dependent on chemical properties, or temperature and less suffering from material degradation. Using graphene-based electrodes EDLCs appear very promising but still lag the LiB in terms of energy density. On the other hand, Hybrid supercapacitors are halfway between EDLCs and LiBs and were developed to combine the advantages of EDLC such as temperature stability, high-power density, higher life cycles, and the advantages of LiBs such as higher energy density. Hybrid supercapacitors differ from EDLCs in being asymmetric, they use a carbon-based material only for the negative electrode and a battery electrode on the positive side. The selected Hybrid supercapacitor cells for this work were commercially available, high-energy density Li-ion capacitor (LiC) cells. Characterization tests were performed on the LiC by testing its parameters in different temperature conditions and charging/discharging currents. Extensive laboratory characterization test results are used to model the behavior of the LiC in the outdoor situation as ES for PV systems. Using ES outdoors exposes the cells to variable temperatures, which affect the performance (i.e., capacity, power capability etc.) of the ES. The integrated ES of the PV system is exposed to the temperature variations outdoors and sized for the case of LiC ES and LiB ES. As the LiB capacity drops in the lower temperatures, LiB is oversized to overcome this capacity drop. LiC’s capacity is less affected by temperature, thus the LiC is not oversized compared to the LiB. Defining the optimal ES size is not only dependent on the current capacity of the storage cells but also on the capacity of the cells after a number of cycles and considering the effect of the operating in environmental conditions on aging. For this reason, aging tests were required to develop such an aging model for the LiC. A 3x3 test matrix with two axes representing temperature and current was used for cycling five LiC test cells in different conditions; extrapolation was considered to determine the capacity and ESR of the LiCs for the untested conditions. Green Hydrogen production is an alternative method of storing the energy produced from PV panels. Also, Green Hydrogen is an alternative to natural gas and can be used in applications such as heating and transportation. Green hydrogen is produced in a process called electrolysis using a Proton Exchange Membrane (PEM) electrolyzer. But even in the application of green hydrogen production, an electric ES is required to keep the PEM electrolyzer in the production mode even after sunset or in idle mode to avoid complete shutdown and restart, which reduces the lifetime of the electrolyzer. To manage the green hydrogen production from PV throughout the day and from ES at night, a basic energy management system (EMS) is used. The ES is optimized for different scenarios using LiC and LiB. A sensitivity analysis of LiC and LiB ES is performed for the PV green hydrogen production system considering local irradiance and temperature conditions in the Australian climate. The study considers tradeoff scenarios between ES size and hydrogen production, suggests the best ES technology for PV green hydrogen production in Australia, and the suggests an energy management strategy for this application.
... With further optimizations regarding the voltage matching by either improving the OSC stability or by choosing a different battery chemistry like, for example, lithium iron phosphate (LFP) with a nominal voltage of 3.3 V versus Li/Li þ , a safe upper cut-off voltage of 3.6 V vs Li/Li þ and an improved cycling stability if compared to NMC-based chemistries and adjusting the size of the battery pack to better support peak current demands for example an ESP32 board (increasing the battery capacity to 50 mAh is enough to provide 120 mA current peaks for 3-8 s, while not exceeding a discharge current rate of 2.4 C) the presented mode II photo-battery can be readily applied to more or less any outdoor sensing demand. [57,58] Further the amount of battery materials required can be reduced by a factor of 30 resulting in a more reliable, cheaper, easier to operate and less resource consuming technology, compared to using oversized battery packages in order to facilitate true remote sensing. ...
Integrated local energy harvesting and storage is a critical prerequisite for energy autonomy of distributed sensing arrays required for the implementation of the internet of things (IoT). In this context, the monolithic integration of solar cells with metallic lithium‐based batteries into stacked high voltage photo‐batteries allows to provide said energy autonomy, with the smallest possible footprint and the highest resource efficiency. However current photo‐battery designs require additional electronics to control and match power output like maximum power point (MPP) tracking and overcharge protection. Herein a novel and compact monolithic photo‐battery design is provided, advantageously combining an organic solar cell with a NMC 622 versus metallic lithium‐based battery, matched in terms of VOC and cut‐off voltage, thereby achieving photo‐charging without any control electronics and energy release on demand at a very compact footprint of only 2.5 cm × 2.5 cm × 0.2 cm. Additionally, by applying a power profile simulating a temperature and humidity sensor over the course of a 24 h light and dark cycle, real world applicability of the photo‐battery in this type of applications is demonstrated.
... Additionally, we collected battery data used in prior studies including CLO [3], CALCE [11ś13], HNEI [14], UL-PUR [15], RWTH [16] and SNL [10]. By combining these batteries with MATR-1, MATR-2 and HUST, we obtained a total collection of 401 batteries and developed two datasets MIX-100 and MIX-20. ...
... Visualization of datasets. a: The coverage of the dataset employed in this work significantly surpasses that of previous undertakings, namely the NE[1], CLO[3], SNL[10], HUST[5], and CALCE[11ś13]. b: A visualization of the capacity degradation with respect to the cycles for all the cells. ...
Accurately predicting the lifetime of battery cells in early cycles holds tremendous value for battery research and development as well as numerous downstream applications. This task is rather challenging because diverse conditions, such as electrode materials, operating conditions, and working environments, collectively determine complex capacity-degradation behaviors. However, current prediction methods are developed and validated under limited aging conditions, resulting in questionable adaptability to varied aging conditions and an inability to fully benefit from historical data collected under different conditions. Here we introduce a universal deep learning approach that is capable of accommodating various aging conditions and facilitating effective learning under low-resource conditions by leveraging data from rich conditions. Our key finding is that incorporating inter-cell feature differences, rather than solely considering single-cell characteristics, significantly increases the accuracy of battery lifetime prediction and its cross-condition robustness. Accordingly, we develop a holistic learning framework accommodating both single-cell and inter-cell modeling. A comprehensive benchmark is built for evaluation, encompassing 401 battery cells utilizing 5 prevalent electrode materials across 168 cycling conditions. We demonstrate remarkable capabilities in learning across diverse aging conditions, exclusively achieving 10\% prediction error using the first 100 cycles, and in facilitating low-resource learning, almost halving the error of single-cell modeling in many cases. More broadly, by breaking the learning boundaries among different aging conditions, our approach could significantly accelerate the development and optimization of lithium-ion batteries.
... Degradation of NMC Li-ion batteries under different SoC ranges[37]. ...
This study focuses on the feasibility of electric aircraft operations between the Caribbean islands of Aruba, Bonaire, and Curaçao. It explores the technical characteristics of two different future electric aircraft types (i.e., Alice and ES-19) and compares their operational requirements with those of three conventional types currently in operation in the region. Flight operations are investigated from the standpoint of battery performance, capacity, and consumption, while their operational viability is verified. In addition, the CO2 emissions of electric operations are calculated based on the present energy mix, revealing moderate improvements. The payload and capacity are also studied, revealing a feasible transition to the new types. The impact of the local climate is discussed for several critical components, while the required legislation for safe operations is explored. Moreover, the maintenance requirements and costs of electric aircraft are explored per component, while charging infrastructure in the hub airport of Aruba is proposed and discussed. Overall, this study offers a thorough overview of the opportunities and challenges that electric aircraft operations can offer within the context of this specific islandic topology.
... The exploration of renewable energy and development of energy storage technologies are in great demand, of which Li-ion batteries (LIBs) attract much attention owing to their high energy density. [1][2][3] However, the intrinsic flammability of organic electrolytes leads to severe safety concerns in conventional LIBs, 4,5 as evidenced by fire accidents of electric vehicles and consumer electronics. Aqueous Liion batteries (ALIBs) are regarded as an alternative approach to tackle the safety issue. ...
Aqueous Li-ion batteries (ALIBs) are an important class of battery chemistries owing to the intrinsic non-flammability of aqueous electrolytes. However, water is detrimental to most cathode materials and could result in rapid cell failure. Identifying the degradation mechanisms and evaluating the pros and cons of different cathode materials are crucial to guide the materials selection and maximize their electrochemical performance in ALIBs. In this study, we investigate the stability of LiFePO4 (LFP), LiMn2O4 (LMO) and LiNi0.8Mn0.1Co0.1O2 (NMC) cathodes, without protective coating, in three different aqueous electrolytes, i.e., salt-in-water, water-in-salt, and molecular crowding electrolytes. The latter two are the widely-reported “water-deficient electrolyte”. LFP cycled in molecular crowding electrolyte exhibits the best cycle life in both symmetric and full cells owing to the stable crystal structure. Mn dissolution and surface reduction accelerate the capacity decay of LMO in water-rich electrolyte. On the other hand, the bulk structural collapse leads to the degradation of NMC cathodes. LMO demonstrates better full-cell performance than NMC in water-deficient aqueous electrolytes. This work reveals the degradation mechanisms of olivine, spinel, and layered cathodes in different aqueous electrolytes and yields insights into improving electrode materials and electrolytes for ALIBs.
... That said, it is clear that differences exist between cell types and cell chemistries. Different battery chemistries, for instance, have been observed to age at different rates due to their unique electrochemical properties [38]. Similarly, the design and manufacturing processes of different cell types can also influence their aging behavior. ...
This work introduces a comprehensive modeling framework designed to simulate the electrical, thermal, and aging behavior of battery cells connected in various parallel and series configurations. By utilizing Monte Carlo simulation techniques, the framework is used to investigate the inherent variability in cell attributes, including initial capacity, aging rate, and application profiles. Besides the estimation of expected battery life, this simulation environment enables the detailed investigation of failure distributions across different cell configurations and intensities of parameter variations. Results obtained from these simulations can be used, as an example, in the context of the automotive industry, where the insights of simulation in understanding the inherent variability of the aging process are particularly vital. As electric vehicles become more prevalent, understanding the performance and longevity of battery packs under various conditions is essential for effective design and management strategies, optimizing vehicle range, safety, and cost-effectiveness also on a fleet-level. Moreover, the ability to investigate failure distributions provides invaluable information for improving battery reliability and safety, key factors in the consumer acceptance of electric vehicles. Ultimately, the simulation environment provides a powerful tool for designing and optimizing efficient and durable battery technologies, with a focus on failure distribution analysis.
... Currently, Lithium-ion batteries (LiBs) are the dominant energy storage technology in the market, offering low self-discharge, a long cycle life, and a high energy density [2]. However, LiBs (i.e., LiB plural) exhibit some limitations in outdoor/off-grid applications, especially when subjected to temperature fluctuations and subzero temperatures [3]. Furthermore, their performance degrades over time, leading to the need for oversizing the battery storage to compensate for capacity loss during the system's operational life [4]. ...
... If 3 days of autonomy storage are required to operate outdoors in Aalborg for a guaranteed five-year lifetime of the system, then LiC size (3,5) = 121 Ah and LiB size (3, 5) = 137 Ah. Figure 17 illustrates the comparative sizing performance of the LiC and LiB across different scenarios: dynamic load and temperature, constant temperature, and constant load. ...
The intermittent nature of power generation from photovoltaics (PV) requires reliable energy storage solutions. Using the storage system outdoors exposes it to variable temperatures, affecting both its storage capacity and lifespan. Utilizing and optimizing energy storage considering climatic variations and new storage technologies is still a research gap. Therefore, this paper presents a modified sizing algorithm based on the Golden Section Search method, aimed at optimizing the number of cells in an energy storage unit, with a specific focus on the unique conditions of Denmark. The considered energy storage solutions are Lithium-ion capacitors (LiCs) and Lithium-ion batteries (LiBs), which are tested under different temperatures and C-rates rates. The algorithm aims to maximize the number of autonomy cycles—defined as periods during which the system operates independently of the grid, marked by intervals between two consecutive 0% State of Charge (SoC) occurrences. Testing scenarios include dynamic temperature and dynamic load, constant temperature at 25 °C, and constant load, considering irradiation and temperature effects and cell capacity fading over a decade. A comparative analysis reveals that, on average, the LiC storage is sized at 70–80% of the LiB storage across various scenarios. Notably, under a constant-temperature scenario, the degradation rate accelerates, particularly for LiBs. By leveraging the modified Golden Section Search algorithm, this study provides an efficient approach to the sizing problem, optimizing the number of cells and thus offering a potential solution for energy storage in off-grid PV systems.
