INES - Institut für nachhaltige Energiesysteme
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Der sommerliche Wärmeschutz von Schulgebäuden im Oberrheingraben und die Bereitstellung von Kühlenergie wurden bereits untersucht und finden Aufnahme im Leitfaden „Natürliche Gebäudeklimatisierung in Klassenzimmern des südlichen Oberrheins“. Im Rahmen der Arbeiten zur Minderung der sommerlichen Überhitzung wurde durch den Einbau und die damit verbundene kontinuierliche Aufzeichnung der CO2‐Konzentrationen der Raumluft festgestellt, dass besonders im Winterhalbjahr eine Verbesserung der Luftqualität erreicht werden muss.
Nickel cobalt aluminum oxide (NCA) based lithium-ion battery electrodes exhibit a distinct asymmetry in discharge/charge behavior towards high bulk stoichiometry (low state of charge). We show that basic electrochemical relationships, that is, the Nernst equation and the Butler-Volmer equation, are able to reproduce this behavior when a two-step reaction mechanism is assumed. The two-step mechanism consists of (1) lithium-ion adsorption from the electrolyte onto the active material particle surface under electron transfer, and (2) intercalation of surface-adsorbed lithium atoms into the bulk material. The asymmetry of experimental half-cell data of an NCA electrode cycled at 0.1 C-rate can be quantitatively reproduced with this simple model. The model parameters show two alternative solutions, predicting either a saturated (highly-covered) or a depleted surface for high bulk lithiation.
The uncertain and time-variant nature of renewable energy results in the need to deal with peaks in the production of energy. One approach is to achieve a load shift and thereby help balancing the grid by using thermally Activated Building Systems (TABS). Control systems currently in place do not exploit the full potential of TABS. This paper reviews how Model Predictive Control can possibly reduce the fluctuations of the demand and supply of (renewable) energy as it enables the TABS to react to the dynamics of weather and its impact on the grid at any time.
Battery degradation is a complex physicochemical process that strongly depends on operating conditions and environment. We present a model-based analysis of lithium-ion battery degradation in smart microgrids, in particular, a single-family house and an office tract with photovoltaics generator. We use a multi-scale multi-physics model of a graphite/lithium iron phosphate (LiFePO4, LFP) cell including SEI formation as ageing mechanism. The cell-level model is dynamically coupled to a system-level model consisting of photovoltaics, inverter, power consumption profiles, grid interaction, and energy management system, fed with historic weather data. The behavior of the cell in terms of degradation propensity, performance, state of charge and other internal states is predicted over an annual operation cycle. As result, we have identified a peak in degradation rate during the battery charging process, caused by charging overpotentials. Ageing strongly depends on the load situation, where the predicted annual capacity fade is 1.9 % for the single-family house and only 1.3 % for the office tract.
Mit der Messung des Wärme- und Kälteverbrauchs im Labor gelingt es, sowohl thermisch träge als auch agile Flächentemperiersysteme unter praxisnahen, dynamischen Bedingungen messtechnisch zu bewerten. Werden Nutzwärme- und Nutzkältebedarf berechnet und ins Verhältnis zu den gemessenen Verbräuchen gesetzt, können die Aufwandzahlen für die Nutzenübergabe ece für verschiedene Flächentemperiersysteme und in Kombinationen mit anderen Übergabesystemen unter verschiedenen Nutzungsbedingungen und für unterschiedliche Betriebsführungsstrategien bestimmt werden. Damit stehen Aufwandszahlen auf Basis kalorischer Messungen zur Verfügung, die je nach Aufgabenstellung entweder produkt- oder objektbezogen in der Planung komplexer Energiekonzepte verwendet werden können und die tatsächlichen Aufwandszahlen eh, ce für den Heizfall bzw. ec, ce für den Kühlfall genauer als Literaturwerte bzw. projektbezogen beschreiben
There is a growing trend for the use of thermo-active building systems (TABS) for the heating and cooling of buildings, because these systems are known to be very economical and efficient. However, their control is complicated due to the large thermal inertia, and their parameterization is time-consuming. With conventional TABS-control strategies, the required thermal comfort in buildings can often not be maintained, particularly if the internal heat sources are suddenly changed. This paper shows measurement results and evaluations of the operation of a novel adaptive and predictive calculation method, based on a multiple linear regression (AMLR) for the control of TABS. The measurement results are compared with the standard TABS strategy. The results show that the electrical pump energy could be reduced by more than 86%. Including the weather adjustment, it could be demonstrated that thermal energy savings of over 41% could be reached. In addition, the thermal comfort could be improved due to the possibility to specify mean room set-point temperatures. With the AMLR, comfort category I of the comfort norms ISO 7730 and DIN EN 15251 are observed in about 95% of occasions. With the standard TABS strategy, only about 24% are within category I.
Adaptive predictive control of thermo-active building systems (TABS) based on a multiple regression algorithm: First practical test. Available from: https://www.researchgate.net/publication/305903009_Adaptive_predictive_control_of_thermo-active_building_systems_TABS_based_on_a_multiple_regression_algorithm_First_practical_test [accessed Jul 7, 2017].
The humanoid Sweaty was the finalist in this year’s robocup soccer championship(adult size). For the optimization of the gait and the stability, data concerning forces and torques in the ankle joints would be helpful. In the following paper the development of a six-axis force and torque sensor for the humanoid robot Sweaty is described. Since commercial sensors do not meet the demands for the sensors in Sweatys ankle joints, a new sensor was developed. As a measuring devices we used strain gauges and custom electronics based on an acam PS09. The geometry was analyzed with the FEM program ANSYS to get optimal dimensions for the measuring beams. In addition ANSYS was used to optimize the position for the strain gauges on the beam.
Proton Exchange Membrane Fuel Cells (PEMFC) are energy efficient and environmentally friendly alternatives to conventional energy conversion systems in many yet emerging applications. In order to enable prediction of their performance and durability, it is crucial to gain a deeper understanding of the relevant operation phenomena, e.g., electrochemistry, transport phenomena, thermodynamics as well as the mechanisms leading to the degradation of cell components. Achieving the goal of providing predictive tools to model PEMFC performance, durability and degradation is a challenging task requiring the development of detailed and realistic models reaching from the atomic/molecular scale over the meso scale of structures and materials up to components, stack and system level. In addition an appropriate way of coupling the different scales is required.
This review provides a comprehensive overview of the state of the art in modeling of PEMFC, covering all relevant scales from atomistic up to system level as well as the coupling between these scales. Furthermore, it focuses on the modeling of PEMFC degradation mechanisms and on the coupling between performance and degradation models.