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Lithium-ion batteries show strongly nonlinear behaviour regarding the battery current and state of charge. Therefore, the modelling of lithium-ion batteries is complex. Combining physical and data-driven models in a grey-box model can simplify the modelling. Our focus is on using neural networks, especially neural ordinary differential equations, for grey-box modelling of lithium-ion batteries. A simple equivalent circuit model serves as a basis for the grey-box model. Unknown parameters and dependencies are then replaced by learnable parameters and neural networks. We use experimental full-cycle data and data from pulse tests of a lithium iron phosphate cell to train the model. Finally, we test the model against two dynamic load profiles: one consisting of half cycles and one dynamic load profile representing a home-storage system. The dynamic response of the battery is well captured by the model.
Druckluft ist verdichtete atmosphärische Luft und wird in der Industrie sowie im Handwerk als Energieträger genutzt. Den vielfältigen Vorteilen stehen aber auch einige Nachteile gegenüber, wobei der wichtigste der Preis ist. Druckluft gilt als eine der teuersten Energieformen und die Energiekosten stellen den größten Kostenfaktor bei der Produktion dar. In der vorliegenden Arbeit soll eine modellprädiktive Regelung eines Druckluftsystems entworfen und implementiert werden. Das ökonomische Regelziel besteht darin, die Energiekosten bei der Erzeugung von Druckluft zu senken. Die Implementierung umfasst unterschiedliche Varianten eines Druckluftsystems. Dazu zählen folgende Auslegungsvarianten:
• Ein Druckluftsystem mit frequenzgeregeltem Kompressor
o Mit einem Schraubenkompressor
o Mit zwei Schraubenkompressoren
• Ein Druckluftsystem mit binärgeregeltem Kompressor
o Schraubenkompressor
o Kolbenkompressor
Basierend auf den erstellten Modellen wird ein modellprädiktiver Regler entworfen und implementiert. Die modellprädiktive Regelung leistet einen entscheidenden Beitrag zur Prozessoptimierung. Der Optimierungsalgorithmus erhöht bei niedrigen Strompreisen das Druckniveau im Behälter und profitiert bei hohen Preisen vom gespeicherten Luftvolumen. Die Flexibilität des Systems ist begrenzt. Mit zunehmender Behältergröße konvergieren die Kosten der Drucklufterzeugung gegen einen parameterabhängigen Wert des Systems. Außerdem bestimmen die Systemparameter die Lösbarkeit des Optimierungsproblems. Im Vergleich zu den frequenzgeregelten Kompressoren sind die binärgeregelten Kompressoren nur unter modifizierten Annahmen einsetzbar, ansonsten kann das Optimierungsproblem nicht gelöst werden.
Lithium‐ion battery cells are multiscale and multiphysics systems. Design and material parameters influence the macroscopically observable cell performance in a complex and nonlinear way. Herein, the development and application of three methodologies for model‐based interpretation and visualization of these influences are presented: 1) deconvolution of overpotential contributions, including ohmic, concentration, and activation overpotentials of the various cell components; 2) partial electrochemical impedance spectroscopy, allowing a direct visualization of the origin of different impedance features; and 3) sensitivity analyses, allowing a systematic assessment of the influence of cell parameters on capacity, internal resistance, and impedance. The methods are applied to a previously developed and validated pseudo‐3D model of a high‐power lithium‐ion pouch cell. The cell features a blend cathode. The two blend components show strong coupling, which can be observed and interpreted using the results of overpotential deconvolution, partial impedance spectroscopy, and sensitivity analysis. The presented methods are useful tools for model‐supported lithium‐ion cell research and development.
Thin-layer chromatography (TLC) is a well-established and widely used separation technique. Most undergraduate students of chemistry or food science used TLC as a primitive separation tool, which does not need more than small pieces of TLC plates, a glass jar and some solvents. TLC has evolved from a simple separation method of the past into an instrumental technique that offers automation, reproducibility and accurate quantification for a wide variety of applications [1]. The use of modern 10*10 cm TLC plates with narrow particle size distribution is called high performance thin layer chromatography (HPTLC), to distinguish the method from the use of traditional 20 20 cm TLC plates.
We tested the MOF framework Cu-BTC for natural gas (NG) storage. Adsorption isotherms of C1–C4 alkanes were simulated applying the Grand Canonical ensemble and the Monte Carlo algorithm in a classical molecular mechanics approach. Experimental monocomponent isotherm of the alkanes was used to validate the force field. We performed multicomponent adsorptions calculations for three different quaternary mixtures of C1–C4 alkanes, matching typical NG streams composition, and predicted theoretical storage capacities, efficiency and accumulation of the NG within that composition. Despite being one of the frameworks with greatest storage capacity of methane, we found that Cu-BTC presented great sensitivity to the variation of the heavier alkanes in NG composition. When we increase the percentage of butane from 0.1% to 0.7% in the mixture, the mass of components retained in the discharge pressure (1 bar) increases from 35 to 60%. We also perform siting and interaction energy investigations and compare the NG storage performance of the Cu-BTC with that of activated carbons. To our knowledge, this is the first study regarding the efficiency of the NG storage in Cu-BTC.
Human interaction frequently includes decision-making processes during which interactants call on verbal and non-verbal resources to manage the flow of interaction. In 2017, Stevanovic et al. carried out pioneering work, analyzing the unfolding of moment-by-moment dynamics by investigating the behavioral matching during search and decision-making phases. By studying the similarities in the participant's body sway during a conversation task in Finnish, the authors showed higher behavioral matching during decision phases than during search phases. The purpose of this research was to investigate the whole-body sway and its coordination during joint search and decision-making phases as a replication of the study by Stevanovic et al. (2017) but based on a German population. Overall, 12 dyads participated in this study and were asked to decide on 8 adjectives, starting with a pre-defined letter, to describe a fictional character. During this joint-decision task (duration: 206.46 ± 116.08 s), body sway of both interactants was measured using a 3D motion capture system and center of mass (COM) accelerations were computed. Matching of body sway was calculated using a windowed cross correlation (WCC) of the COM accelerations. A total of 101 search and 101 decision phases were identified for the 12 dyads. Significant higher COM accelerations (5.4*10−3 vs. 3.7*10−3 mm/s2, p < 0.001) and WCC coefficients (0.47 vs. 0.45, p = 0.043) were found during decision-making phases than during search phases. The results suggest that body sway is one of the resources humans use to communicate the arrival at a joint decision. These findings contribute to a better understanding of interpersonal coordination from a human movement science perspective.
Muli-scale thermos-electrochemical modelling of aging mechanisms in an LFP/graphite lithium-ion cell
(2017)
Lithium-ion batteries show a complex thermo-electrochemical performance and aging behavior. This paper presents a modeling and simulation framework that is able to describe both multi-scale heat and mass transport and complex electrochemical reaction mechanisms. The transport model is based on a 1D + 1D + 1D (pseudo-3D or P3D) multi-scale approach for intra-particle lithium diffusion, electrode-pair mass and charge transport, and cell-level heat transport, coupled via boundary conditions and homogenization approaches. The electrochemistry model is based on the use of the open-source chemical kinetics code CANTERA, allowing flexible multi-phase electrochemistry to describe both main and side reactions such as SEI formation. A model of gas-phase pressure buildup inside the cell upon aging is added. We parameterize the model to reflect the performance and aging behavior of a lithium iron phosphate (LiFePO4, LFP)/graphite (LiC6) 26650 battery cell. Performance (0.1–10 C discharge/charge at 25, 40 and 60°C) and calendaric aging experimental data (500 days at 30°C and 45°C and different SOC) from literature can be successfully reproduced. The predicted internal cell states (concentrations, potential, temperature, pressure, internal resistances) are shown and discussed. The model is able to capture the nonlinear feedback between performance, aging, and temperature.
Phosphate-based inorganic–organic hybrid nanoparticles (IOH-NPs) with the general composition [M]2+[Rfunction(O)PO3]2– (M = ZrO, Mg2O; R = functional organic group) show multipurpose and multifunctional properties. If [Rfunction(O)PO3]2– is a fluorescent dye anion ([RdyeOPO3]2–), the IOH-NPs show blue, green, red, and near-infrared fluorescence. This is shown for [ZrO]2+[PUP]2–, [ZrO]2+[MFP]2–, [ZrO]2+[RRP]2–, and [ZrO]2+[DUT]2– (PUP = phenylumbelliferon phosphate, MFP = methylfluorescein phosphate, RRP = resorufin phosphate, DUT = Dyomics-647 uridine triphosphate). With pharmaceutical agents as functional anions ([RdrugOPO3]2–), drug transport and release of anti-inflammatory ([ZrO]2+[BMP]2–) and antitumor agents ([ZrO]2+[FdUMP]2–) with an up to 80% load of active drug is possible (BMP = betamethason phosphate, FdUMP = 5′-fluoro-2′-deoxyuridine 5′-monophosphate). A combination of fluorescent dye and drug anions is possible as well and shown for [ZrO]2+[BMP]2–0.996[DUT]2–0.004. Merging of functional anions, in general, results in [ZrO]2+([RdrugOPO3]1–x[RdyeOPO3]x)2– nanoparticles and is highly relevant for theranostics. Amine-based functional anions in [MgO]2+[RaminePO3]2– IOH-NPs, finally, show CO2 sorption (up to 180 mg g–1) and can be used for CO2/N2 separation (selectivity up to α = 23). This includes aminomethyl phosphonate [AMP]2–, 1-aminoethyl phosphonate [1AEP]2–, 2-aminoethyl phosphonate [2AEP]2–, aminopropyl phosphonate [APP]2–, and aminobutyl phosphonate [ABP]2–. All [M]2+[Rfunction(O)PO3]2– IOH-NPs are prepared via noncomplex synthesis in water, which facilitates practical handling and which is optimal for biomedical application. In sum, all IOH-NPs have very similar chemical compositions but can address a variety of different functions, including fluorescence, drug delivery, and CO2 sorption.
The energy system of the future will transform from the current centralised fossil based to a decentralised, clean, highly efficient, and intelligent network. This transformation will require innovative technologies and ideas like trigeneration and the crowd energy concept to pave the way ahead. Even though trigeneration systems are extremely energy efficient and can play a vital role in the energy system, turning around their deployment is hindered by various barriers. These barriers are theoretically analysed in a multiperspective approach and the role decentralised trigeneration systems can play in the crowd energy concept is highlighted. It is derived from an initial literature research that a multiperspective (technological, energy-economic, and user) analysis is necessary for realising the potential of trigeneration systems in a decentralised grid. And to experimentally quantify these issues we are setting up a microscale trigeneration lab at our institute and the motivation for this lab is also briefly introduced.
This paper will introduce the open-source model MyPyPSA-Ger, a myopic optimization model developed to represent the German energy system with a detailed mapping of the electricity sector, on a highly disaggregated level, spatially and temporally, with regional differences and investment limitations. Furthermore, this paper will give new outlooks on the German federal government 2050 emissions goals of the electricity sector to become greenhouse gas neutral by proposing new CO2 allowance strategies. Moreover, the regional differences in Germany will be discussed, their role and impact on the energy transition, and which regions and states will drive the renewable energy utilization forward.
Following a scenario-based analysis, the results point out the major keystones of the energy transition path from 2020 to 2050. Solar, onshore wind, and gas-fired power plants will play a fundamental role in the future electricity systems. Biomass, run of river, and offshore wind technologies will be utilized in the system as base-load generation technologies. Solar and onshore wind will be installed almost everywhere in Germany. However, due to the nature of Germany’s weather and geographical features, the southern and northern regions will play a more important role in the energy transition.
Higher CO2 allowance costs will help achieve the 1.5-degree-target of the electricity system and will allow for a rapid transition. Moreover, the more expensive, and the earlier the CO2 tax is applied to the system, the less it will cost for the energy transition, and the more emissions will be saved throughout the transition period. An earlier phase-out of coal power plants is not necessary with high CO2 taxes, due to the change in power plant’s unit commitment, as they prioritize gas before coal power plants. Having moderate to low CO2 allowance cost or no clear transition policy will be more expensive and the CO2 budget will be exceeded. Nonetheless, even with no policy, renewables still dominate the energy mix of the future.
However, maintaining the maximum historical installation rates of both national and regional levels, with the current emissions reduction strategy, will not be enough to reach the level of climate-neutral electricity system. Therefore, national and regional installation requirements to achieve the federal government emission reduction goals are determined. Energy strategies and decision makers will have to resolve great challenges in order to stay in line with the 1.5-degree-target.
As PV enters the terawatt era, reliability, sustainability and low carbon footprint of solar modules are key requirements. The N.I.C.E.TM technology from Apollon Solar is a good candidate for significant improvements in these areas. As the second-generation pilot line is now functional with IEC certification underway, we present a holistic assessment of N.I.C.E.TM technology compared with conventional module technology with encapsulant. This includes electrical performance and cost/consumables, reliability, and degradation mechanisms as well as sustainability aspects. In addition, the new generation of N.I.C.E.-wire modules are presented that use thin round Cu wires instead of flat ribbons for interconnection. This candidate technology for an alternative to the Smart Wire Connection Technology (SWCT) is investigated experimentally as well as via numerical simulations.
Non-esterified plant oils gain ecological and economical importance, particularly in the EU where it is intended to increase the share of renewable energies. Plant oils do not require any chemical treatment so do not cause secondary pollution. The importance of plant oil will increase in Germany for mobile and stationary applications. The generation co-generation of heat and power is subsidized by the German “Erneuerbares Energiegesetz” and the “Kraft-Wärme-Kopplungsgesetz” when renewable fuels are used such as plant oils..
Plant oils have a much higher viscosity than conventional gas oil. It is mandatory to decrease the oil viscosity by heating prior to injection to assure proper injection and to avoid engine damage due to coke formation in the combustion chamber and at the injection nozzle. The German quality standard of Weihenstephan (RK-Qualitätsstandard 05/2000) for rape seed oil should be followed for use as diesel fuel. The chemical composition of plant oils is appreciably different in comparison to diesel fuels derived from mineral oils suggesting also different emission behavior.