27 research outputs found

    Dust Abrasion Damage on Martian Solar Arrays: Experimental Investigation and Opportunity Rover Performance Analysis

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    Here we investigate the effects of erosion and weathering that occur on III-V cover-glass interconnected cells (CICs) after exposure to Mars dust storm conditions. The durability of these materials in a Martian environment is not well characterized so we perform analogous experimentation. To replicate the dust impingement, test coupons were placed in an enclosure and sandblasted with Mars dust simulant. We show the J-V response dependency on both incident angle and exposure times. We find that the simulated Martian dust storm often results in damage to the anti-reflective coating and subsequent reduced short circuit current. Reduction in the open circuit voltage is observed, likely caused by structural damage to the crystal lattice after CIC fracture. We employ data-driven modeling to determine a performance degradation rate that is consistent with zero within uncertainty. We also quantify the soiling contribution and power degradation of the photovoltaic cells on Mars through analysis of 4.95 Martian years of report-out power conditions from the Opportunity rover. We find that atmospheric dust suspended due to a weather event does not result in instantaneous settled dust on the PV cells. We calculate via autocorrelation function that the dust settling rate is approximately 21 Sols from atmospheric dust suspension. The findings presented here deliver a realistic approximation for the insolation values and subsequent PV power expected over time on the Martian surface thus informing future dust abatement systems

    Dust Abrasion Damage on Martian Solar Arrays: Experimental Investigation and Opportunity Rover Performance Analysis

    Get PDF
    Here we investigate the effects of erosion and weathering that occur on III-V cover-glass interconnected cells (CICs) after exposure to Mars dust storm conditions. The durability of these materials in a Martian environment is not well characterized so we perform analogous experimentation. To replicate the dust impingement, test coupons were placed in an enclosure and sandblasted with Mars dust simulant. We show the J-V response dependency on both incident angle and exposure times. We find that the simulated Martian dust storm often results in damage to the anti-reflective coating and subsequent reduced short circuit current. Reduction in the open circuit voltage is observed, likely caused by structural damage to the crystal lattice after CIC fracture. We employ data-driven modeling to determine a performance degradation rate that is consistent with zero within uncertainty. We also quantify the soiling contribution and power degradation of the photovoltaic cells on Mars through analysis of 4.95 Martian years of report-out power conditions from the Opportunity rover. We find that atmospheric dust suspended due to a weather event does not result in instantaneous settled dust on the PV cells. We calculate via autocorrelation function that the dust settling rate is approximately 21 Sols from atmospheric dust suspension. The findings presented here deliver a realistic approximation for the insolation values and subsequent PV power expected over time on the Martian surface thus informing future dust abatement systems

    Insights into Space Solar Cell Durability Using SPICE Simulation Seeded by Current-Voltage Characteristics Parametrized Using the Lambert W Special Function

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    We developed and validated an automated routine for the fitting of I-V curve data to the single diode model according to an exact analytical solution. Our fitting routine was validated to show good noise immunity and high accuracy usingsimulated values from LTSPICE. We are thus able to automate parameter extraction from a dataset or arbitrary size. This parameterization allows for better simulation of performance of real cells and arrays and provides utility for a host of applications relevant to space arrays. We will use this methodology to determine the array performance of radiated cells over time, and simulate the performance of the arrays with bypass diodes and power electronics

    Insights into Metastability of Photovoltaic Materials at the Mesoscale Through Massive I–V Analytics

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    The authors demonstrate the feasibility of quantifying cell-level performance heterogeneity from module-level I–V curves by determining conditions of bypass diode turn-on. Analysis of these curves falls outside of typical diode-based models of photovoltaic (PV) performance. The authors show that this approach can leverage statistical and machine learning techniques for broad application to massive datasets, and combine those insights with simulations and laboratory-based experiments to provide useful information into the metastability of the interfaces of a PV cell. The authors find good agreement between the experimentally determined curves and the simulated curves, which guide the variable selection in the massive dataset collected from sites in Cleveland, OH, USA, the Negev Desert, Israel, Isla Gran Canaria, Spain, and Mount Zugspitze, Germany

    Advanced Development of Space Photovoltaic Concentrators Using Robust Lenses, Multi-Junction Cells, and Graphene Radiators

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    At the past three PVSCs, our team has presented recent advances in our space photovoltaic concentrator technology. In the past year, under multiple NASA-funded research and technology development programs, our team has made much additional progress in the advanced development of space photovoltaic concentrators. New robust Fresnel lenses, new high-efficiency multi-junction cells, and new graphene radiators have been developed. The paper will present the latest advances in this technology

    Degradation Science: Mesoscopic Evolution and Temporal Analytics of Photovoltaic Energy Materials

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    Based on recent advances in nanoscience, data science and the availability of massive real-world datastreams, the mesoscopic evolution of mesoscopic energy materials can now be more fully studied. The temporal evolution is vastly complex in time and length scales and is fundamentally challenging to scientific understanding of degradation mechanisms and pathways responsible for energy materials evolution over lifetime. We propose a paradigm shift towards mesoscopic evolution modeling, based on physical and statistical models, that would integrate laboratory studies and real-world massive datastreams into a stress/mechanism/response framework with predictive capabilities. These epidemiological studies encompass the variability in properties that affect performance of material ensembles. Mesoscopic evolution modeling is shown to encompass the heterogeneity of these materials and systems, and enables the discrimination of the fast dynamics of their functional use and the slow and/or rare events of their degradation. We delineate paths forward for degradation science
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