1,620 research outputs found

    Nonlinear observation in fuel cell systems: a comparison between disturbance estimation and High-Order Sliding-Mode techniques

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    © . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/This paper compares two Nonlinear Distributed Parameter Observers (NDPO) for the observation of a Proton Exchange Membrane Fuel Cell (PEMFC). Both NDPOs are based on the discretisation of distributed parameters models and they are used to estimate the state profile of gas concentrations in the anode and cathode gas channels of the PEMFC, giving detailed information about the internal conditions of the system. The reaction and water transport flow rates from the membrane to the channels are uncertainties of the observation problem and they are estimated throughout all the length of the PEMFC without the use of additional sensors. The first observation approach is a Nonlinear Disturbance Observer (NDOB) for the estimation of the disturbances in the NDPO. In the second approach, a novel implementation of a High-Order Sliding-Mode (HOSM) observer is developed to estimate the true value of the states as well as the reaction terms. The proposed observers are tested and compared through a simulation example at different operating points and their performance and robustness is analysed over a given case study, the New European Driving Cycle.Peer ReviewedPostprint (author's final draft

    Geomechanical characterization of geothermal reservoirs in the Bavarian Molasse Basin

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    Switching Off Hysteresis in Perovskite Solar Cells by Fine‐Tuning Energy Levels of Extraction Layers

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    Lead halide perovskites often suffer from a strong hysteretic behavior on their j–V response in photovoltaic devices that has been correlated with slow ion migration. The electron extraction layer has frequently been pointed to as the main culprit for the observed hysteretic behavior. In this work three hole transport layers are studied with well‐defined highest occupied molecular orbital (HOMO) levels and interestingly the hysteretic behavior is markedly different. Here it is shown that an adequate energy level alignment between the HOMO level of the extraction layer and the valence band of the perovskite, not only suppresses the hysteresis, avoiding charge accumulation at the interfaces, but also degradation of the hole transport layer is reduced. Numerical simulation suggests that formation of an injection barrier at the organic/perovskite heterointerface could be one mechanism causing hysteresis. The suppression of such barriers may require novel design rules for interface materials. Overall, this work highlights that both external contacts need to be carefully optimized in order to obtain hysteresis‐free perovskite devices

    An ensemble approach to assess hydrological models’ contribution to uncertainties in the analysis of climate change impact on water resources

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    Over the recent years, several research efforts investigated the impact of climate change on water resources for different regions of the world. The projection of future river flows is affected by different sources of uncertainty in the hydro-climatic modelling chain. One of the aims of the QBic3 5 project (Que´bec-Bavarian International Collaboration on Climate Change) is to assess the contribution to uncertainty of hydrological models by using an ensemble of hydrological models presenting a diversity of structural complexity (i.e. lumped, semi distributed and distributed models). The study investigates two humid, mid-latitude catchments with natural flow conditions; one located in 10 Southern Que´bec (Canada) and one in Southern Bavaria (Germany). Daily flow is simulated with four different hydrological models, forced by outputs from regional climate models driven by a given number of GCMs’ members over a reference (1971–2000) and a future (2041–2070) periods. The results show that the choice of the hydrological model does strongly affect the climate change response of selected hydrological indicators, especially those related to low flows. Indicators related to high flows seem less sensitive on the choice of the hydrological model. Therefore, the computationally less demanding models (usually simple, lumped and conceptual) give a significant level of trust for high and overall mean flows

    A Decision Support System for Photovoltaic Potential Estimation

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    With knowledge on the photovoltaic potential of individual residential buildings, solar companies, energy service providers and electric utilities can identify suitable customers for new PV installations and directly address them in renewable energy rollout and maintenance campaigns. However, many currently used solutions for the simulation of energy generation require detailed information about houses (roof tilt, shading, etc.) that is usually not available at scale. On the other hand, the methodologies enabling extraction of such details require costly remote-sensing data from three-dimensional (3D) laser scanners or aerial images. To bridge this gap, we present a decision support system (DSS) that estimates the potential amount of electric energy that could be generated at a given location if a photovoltaic system would be installed. The DSS automatically generates insights about photovoltaic yields of individual roofs by analyzing freely available data sources, including the crowdsourced volunteered geospatial information systems OpenStreetMap and climate databases. The resulting estimates pose a valuable foundation for selecting the most prospective households (e.g., for personal visit and screening by an expert) and targeted solar panel kit offerings, ultimately leading to significant reduction of manual human efforts, and to cost-effective personalized renewables adoption
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