5 Werkstofftechnik
Filtern
Dokumenttyp
- Vortrag (4)
- Posterpräsentation (4)
- Beitrag zu einem Tagungsband (3)
- Zeitschriftenartikel (2)
Sprache
- Englisch (13) (entfernen)
Schlagworte
- GD-OES (4)
- Lithium Ion Batteries (3)
- Creep (2)
- Depth-profiling (2)
- Distribution function (2)
- EDX (2)
- FIB (2)
- Li-ion battery (2)
- Long-term behavior (2)
- Metal seal (2)
- Monte-Carlo Simulation (2)
- SEM (2)
- Safety assessment (2)
- Weibull Distribution (2)
- Ageing (1)
- Aging mechanisms (1)
- Burst test (1)
- Composite pressure vessels (1)
- Degradation (1)
- End of life (1)
- FCH JU (1)
- Failure rate (1)
- Horizon 2020 (1)
- Hydrogen (1)
- Lithium-ion batteries (1)
- Monte-Carlo-Analysis (1)
- Net zero (1)
- Production scatter (1)
- TAHYA (1)
- Tomography (1)
- X-ray imaging (1)
- battery aging mechanism (1)
- current collector corrosion (1)
- depth profiles (1)
Organisationseinheit der BAM
- 3 Gefahrgutumschließungen; Energiespeicher (13) (entfernen)
Eingeladener Vortrag
- nein (4)
The BAMline at the synchrotron X-ray source BESSY II (Berlin, Germany) is supporting researchers especially in materials science. As a non-destructive characterization method, synchrotron X-ray imaging, especially tomography with hard X-Rays, plays an important role in structural 3D characterization. The imaging capabilities allow for in-situ and operando experiments. In this presentation the equipment, data handling pipeline as well as various examples from material science are presented.
Hydrogen is an attractive energy carrier that requires high effort for safe storage. For ensuring safety, storage cylinders must undergo a challenging approval process. Relevant standards and regulations for composite cylinders used for the transport of hydrogen and for its onboard storage are currently based on deterministic (e.g. ISO 11119-3) or to some respect semi-probabilistic criteria (UN GTR No. 13; with respect to burst strength).
This paper provides a systematic analysis of the load cycle properties resulting from these regulations and standards. Their characteristics are compared with the probabilistic approach of the Federal Institute for Materials Research and Testing BAM. The most important aspect of comparing different concepts is the rate for accepting designs with potentially unsafe or critical safety properties. This acceptance rate is analysed by operating Monte-Carlo simulations over the available range of production properties.
Monte-Carlo-Analysis of Minimum Burst Requirements for Composite Cylinders for Hydrogen Service
(2021)
For achieving Net Zero-aims hydrogen is an indispensable component, probably the main component. For the usage of hydrogen, a wide acceptance is necessary, which requires trust in hydrogen based on absence of major incidents resulting from a high safety level. Burst tests stand for a type of testing that is used in every test standard and regulation as one of the key issues for ensuring safety in use. The central role of burst and proof test is grown to historical reasons for steam engines and steel vessels but - with respect for composite pressure vessels (CPVs) - not due an extraordinary depth of outcomes. Its importance results from the relatively simple test process with relatively low costs and gets its importance by running of the different test variations in parallel. In relevant test und production standards (as e. g. ECE R134) the burst test is used in at least 4 different meanings. There is the burst test on a) new CPVs and some others b) for determining the residual strength subsequent to various simulations of ageing effects. Both are performed during the approval process on a pre-series. Then there is c) the batch testing during the CPVs production and finally d) the 100% proof testing, which means to stop the burst test at a certain pressure level. These different aspects of burst tests are analysed and compared with respect to its importance for the resulting safety of the populations of CPVs in service based on experienced test results and Monte-Carlo simulations. As main criterial for this the expected failure rate in a probabilistic meaning is used. This finally ends up with recommendations for relevant RC&S especially with respect to GTR 13.
Lithium-ion batteries (LIBs) are one technology to overcome the challenges of climate and energy crisis. They are widely used in electric vehicles, consumer electronics, or as storage for renewable energy sources. However, despite innovations in batteries' components like cathode and anode materials, separators, and electrolytes, the aging mechanism related to metallic aluminum current collector degradation causes a significant drop in their performance and prevents the durable use of LIBs. Glow-discharge optical emission spectroscopy (GD-OES) is a powerful method for depth-profiling of batteries' electrode materials. This work investigates aging-induced aluminum deposition on commercial lithium cobalt oxide (LCO) batteries' cathodes. The results illustrate the depth-resolved elemental distribution from the cathode surface to the current collector. An accumulation of aluminum is found on the cathode surface by GD-OES, consistent with results from energy-dispersive X-ray spectroscopy (EDX) combined with focused ion beam (FIB) cutting. In comparison to FIB-EDX, GD-OES allows a fast and manageable depth-profiling. Results from different positions on an aged cathode indicate an inhomogeneous aluminum film growth on the surface. The conclusions from these experiments can lead to a better understanding of the degradation of the aluminum current collector, thus leading to higher lifetimes of LIBs.
Lithium-ion batteries (LIBs) are one technology to overcome the challenges of climate and energy crisis. They are widely used in electric vehicles, consumer electronics, or as storage for renewable energy sources. However, despite innovations in batteries' components like cathode and anode materials, separators, and electrolytes, the aging mechanism related to metallic aluminum current collector degradation causes a significant drop in their performance and prevents the durable use of LIBs.[1] Glow-discharge optical emission spectroscopy (GD-OES) is a powerful method for depth-profiling of batteries' electrode materials. This work investigates aging-induced aluminum deposition on commercial lithium cobalt oxide (LCO) batteries' cathodes. The results illustrate the depth-resolved elemental distribution from the cathode surface to the current collector. An accumulation of aluminum is found on the cathode surface by GD-OES, consistent with results from energy-dispersive X-ray spectroscopy (EDX) combined with focused ion beam (FIB) cutting. In comparison to FIB-EDX, GD-OES allows a fast and manageable depth-profiling. Results from different positions on an aged cathode indicate an inhomogeneous aluminum film growth on the surface. The conclusions from these experiments can lead to a better understanding of the degradation of the aluminum current collector, thus leading to higher lifetimes of LIBs.
Investigation of degradation of the aluminum current collector in lithium-ion batteries by GD-OES
(2022)
Lithium-ion batteries (LIBs) are one technology to overcome the challenges of climate and energy crisis. They are widely used in electric vehicles, consumer electronics, or as storage for renewable energy sources. However, despite innovations in batteries' components like cathode and anode materials, separators, and electrolytes, the aging mechanism related to metallic aluminum current collector degradation causes a significant drop in their performance and prevents the durable use of LIBs. Glow-discharge optical emission spectroscopy (GD-OES) is a powerful method for depth-profiling of batteries' electrode materials. This work investigates aging-induced aluminum deposition on commercial lithium cobalt oxide (LCO) batteries' cathodes. The results illustrate the depth-resolved elemental distribution from the cathode surface to the current collector. An accumulation of aluminum is found on the cathode surface by GD-OES, consistent with results from energy-dispersive X-ray spectroscopy (EDX) combined with focused ion beam (FIB) cutting. In comparison to FIB-EDX, GD-OES allows a fast and manageable depth-profiling. Results from different positions on an aged cathode indicate an inhomogeneous aluminum film growth on the surface. The conclusions from these experiments can lead to a better understanding of the degradation of the aluminum current collector, thus leading to higher lifetimes of LIBs.
In this work, we employed glow discharge optical emission spectrometry (GD-OES) depth profiling as a fast and semi-quantitative method to investigate the aluminum (Al) current collector degradation in commercial lithium cobalt oxide (LCO) pouch cells with no Al2O3 pretreatment. After battery aging, a heterogeneous deposit was found on the surface of the cathode. Gray hotspot areas within an extensive pale white region were formed. Consistent with energy dispersive X-ray (EDX) analysis of micro-cross sections milled via targeted focused ion beam (FIB), an Al-containing layer of approximately 3 µm can be observed using GD-OES. We attribute one main cause of this layer is the degradation of the Al current collector. The nonuniform growth of this layer was investigated by performing GD-OES depth profiling at different in-plane positions. We found that the gray area has a higher mass concentration of Al, probably in metallic form, whereas the white area was probably covered more homogeneously with Al2O3, resulting from the inhomogeneous distribution of the pitting positions on the current collector. Compared to FIB-EDX, GD-OES enables a faster and more convenient depth profile analysis, which allows the more productive characterization of lithium-ion batteries (LIBs), and consequently benefits the development of preferable battery materials.
Determination of Distribution Function used in MCS on Safety Analysis of Hydrogen Pressure Vessel
(2019)
The test data of static burst strength and load cycle strength of composite pressure vessels are often described by GAUSSian normal or WEIBULL distribution function to perform safety analyses. The goodness of assumed distribution function plays a significant role in the inferential statistics to predict the population properties by using limited test data. Often, GAUSSian and WEIBULL probability nets are empirical methods used to validate the distribution function; Anderson-Darling and KolmogorovSmirnov tests are the mostly favorable approaches for Goodness of Fit. However, the different approaches used to determine the parameters of distribution function lead mostly to different conclusions for safety assessments. In this study, six different methods are investigated to show the variations on the rates for accepting the composite pressure vessels according to GTR No. 13 life test procedure. The six methods are: a) NormLog based method, b) Least squares regression, c) Weighted least squares regression, d) A linear approach based on good linear unbiased estimators, e) Maximum likelihood estimation and f) The method of moments estimation. In addition, various approaches of ranking function are considered. In the study, Monte Carlo simulations are conducted to generate basic populations based on the distribution functions which are determined using different methods. Then the samples are extracted randomly from a population and evaluated to obtain acceptance rate. Here, the “populations” and “samples” are corresponding to the burst strength or load cycle strength of the pressure vessels made from composite material and a plastic liner (type 4) for the storage of hydrogen. To the end, the results are discussed, and the best reliable methods are proposed.
Determination of Distribution Function used in MCS on Safety Analysis of Hydrogen Pressure Vessel
(2019)
The test data of static burst strength and load cycle strength of composite pressure vessels are often described by GAUSSian normal or WEIBULL distribution function to perform safety analyses. The goodness of assumed distribution function plays a significant role in the inferential statistics to predict the population properties by using limited test data. Often, GAUSSian and WEIBULL probability nets are empirical methods used to validate the distribution function; Anderson-Darling and Kolmogorov-Smirnov tests are the mostly favorable approaches for Goodness of Fit. However, the different approaches used to determine the parameters of distribution function lead mostly to different conclusions for safety assessments. In this study, six different methods are investigated to show the variations on the rates for accepting the composite pressure vessels according to GTR No. 13 life test procedure. The six methods are: a) Norm-Log based method, b) Least squares regression, c) Weighted least squares regression, d) A linear approach based on good linear unbiased estimators, e) Maximum likelihood estimation and f) The method of moments estimation. In addition, various approaches of ranking function are considered. In the study, Monte Carlo simulations are conducted to generate basic populations based on the distribution functions which are determined using different methods. Then the samples are extracted randomly from a population and evaluated to obtain acceptance rate. Here, the “populations” and “samples” are corresponding to the burst strength or load cycle strength of the pressure vessels made from composite material and a plastic liner (type 4) for the storage of hydrogen. To the end, the results are discussed, and the best reliable methods are proposed.