Battery-aware contact plan design for LEO satellite constellations: The ulloriaq case study

Power demands of communication technologies between LEO small-satellites are difficult to counterbalance by solar infeed and on-board battery storage, due to size and weight limitations. This makes the problem of battery-powered intersatellite communication a very difficult one. Its management requires a profound understanding as well as techniques for a proper extrapolation of the electric power budget as part of the inter-satellite and satellite-to-ground communication design. We discuss how the construction of contact plans in delay tolerant networking can profit from a sophisticated model of the on-board battery behavior. This model accounts for both nonlinearities in battery behavior as well as stochastic fluctuations in charge, so as to control the risk of battery depletion. We take an hypothetical Ulloriaq constellation based on the GOMX–4 satellites from GomSpace as a reference for our studies.Fil: Fraire, Juan Andres. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina. Universitat Saarland; AlemaniaFil: Nies, Gilles. Universitat Saarland; AlemaniaFil: Gerstacker, Carsten. Universitat Saarland; AlemaniaFil: Hermanns, Holger. Universitat Saarland; Alemania. Institute of Intelligent Software; ChinaFil: Bay, Kristian. GomSpace A/S; DinamarcaFil: Bisgaard, Morten. GomSpace A/S; Dinamarc

Mastering operational limitations of LEO satellites – The GOMX-3 approach

When working with space systems the keyword is resources. For a satellite in orbit all resources are sparse and the most critical resource of all is power. It is therefore crucial to have detailed knowledge on how much power is available for an energy harvesting satellite in orbit at every time – especially when in eclipse, where it draws its power from onboard batteries. This paper addresses this problem by a two-step procedure to perform task scheduling for low-earth-orbit (LEO) satellites exploiting formal methods. It combines cost-optimal reachability analyses of priced timed automata networks with a realistic kinetic battery model capable of capturing capacity limits as well as stochastic fluctuations. The procedure is in use for the automatic and resource-optimal day-ahead scheduling of GOMX-3, a power-hungry nanosatellite currently orbiting the earth. We explain how this approach has overcome existing problems, has led to improved designs, and has provided new insights

Mastering satellite operation : on model-based and data-driven optimal battery-aware scheduling

Rechargeable batteries as a power source have become omnipresent. Especially the lithium-ion variant powers virtually every contemporary portable device, it constitutes the central energy source in the domains of e-mobility, autonomous drones and robots, most earth-orbiting spacecraft like satellites and many more. In this work, we take the perspective of the kinetic battery model, an intuitive analytic model, that keeps track of a battery's charge as it is strained with a sequence of loads over time. We provide the mathematical foundation of the battery model, extend it with capacity limits and realistic charging behavior, as well as uncertainty in its initial state and the load it is strained with. In addition, we show how to estimate the non-measurable state of a kinetic battery via measurable quantities, like voltage and current, using Kalman filters. We derive efficient energy budget analysis algorithms in the form of discretization and analytical bisection schemes, deduce their efficiency, empirically analyze their performance and identify their individual strengths and weaknesses. We show how our techniques can be used during design time and in-flight, in the context of two nanosatellite missions \gomx1 and \gomx3. For the former, we derive probabilistic workload models to analyze the mission's yearly energy budget, while for the latter, we bridge the gap from analysis to synthesis by leveraging model checking techniques of the formal methods community in order to produce battery-aware optimal schedules to be executed by the satellite. We demonstrate the adequacy of our scheduling approach via three in-orbit test runs on \gomx3, and show a close correspondence between predicted workload and battery state compared to logged telemetry data such as voltage and current. Finally, in an attempt to continuously perpetuate the schedule synthesis, we extend the scheduling workflow with Kalman filters in order to additionally harness these in-flight telemetry data so as to regularly adjust the battery state estimation.Wiederaufladbare Akkumulatoren als Energiequelle sind mittlerweile omnipräsent. Insbesondere die Lithium-Ionen Variante versorgt fast jedes moderne, portable Gerät mit Energie. Sie ist in einer Vielzahl von Bereichen integral, insbesondere in den Bereichen der E-Mobilität, der autonomen Dronen und Roboter, sowie der Erdsatelliten. Das Augenmerk dieser Arbeit richtet sich auf das kinetische Batteriemodell. Dieses intuitive, analytischeModell, beschreibt die zeitliche Entwicklung des Ladezustands eines Akkumulators, der einer Sequenz elektronischer Lasten unterzogen wird. Das mathematische Fundament des Modells wird erweitert um Kapazitätsgrenzen und realistisches Ladeverhalten, sowie um den Umgang mit Unsicherheit im Kontext des initialen Ladezustands und der anliegenden Last. Darüber hinaus, schlagen wir ein auf dem Kalman-Filter basierendes Schätzverfahren vor, welches den unmessbaren Ladezustand anhand messbarer Quantitäten, wie Spannung und Stromfluss, approximiert. Wir leiten effiziente Algorithmen her, die der Bestimmung von Energiebedarf und Energiebilanz eines batteriebetriebenen Geräts dienen. Diese beruhen auf Diskretisierungs- sowie auf analytischen Intervallhalbierungsverfahren. Es folgt eine Analyse der theoretischen und praktischen Effizienz, sowie die Identifizierung etwaiger individueller Stärken und Schwächen der Paradigmen. Anhand zweier konkreter Fallstudien zeigen wir, wie unsere Verfahren die Planung sowie den laufenden Betrieb einerNanosatellitenmission erleichtern und verbessern. Für die GOMX–1Mission wird ein probabilistisches Arbeitslastmodell eines Nanosatelliten aus Flugtelemetriedaten inferiert, anhand dessen die jährliche Energiebilanz des Satelliten hergeleitet werden kann. Im Kontext der zweitenMission, GOMX–3, entwerfen wir ein Verfahren zur Synthese energieoptimaler Ablaufpläne, die in der Praxis durch den Satelliten ausgeführt werden. Zu diesem Zeck werdenMethoden aus dem Bereich derModellprüfung herangezogen und mit den Analyseverfahren des Batteriemodells verzahnt. Anhand dreier konkreter Testläufe, lässt sich eine starke Korrespondenz zwischen Telemetriedaten und vorhergesagter Quantitäten erkennen, welche die Angemessenheit unserer Syntheseverfahren untermauert. Zur kontinuierlichen Fortsetzung und Verlängerung der synthetisierten Pläne über die gesamteMissionsdauer, wird schließlich das Verfahren durch einen weiteren Zwischenschritt ergänzt. Dieser dient durch das Verwenden von Kalman- Filtern dazu, den vorhergesagten Ladezustand des Akkumulators anhand besagter Telemetriedaten regelmäßig anzupassen, um eventuelle, durch das Batteriemodell hervorgerufene Abweichungstendenzen auszugleichen

Mastering operational limitations of LEO satellites - The GOMX3 approach

When working with space systems the keyword is resources. For a satellite in orbit all resources are sparse and the most critical resource of all is power. It is therefore crucial to have detailed knowledge on how much power is available for an energy harvesting satellite in orbit at every time – especially when in eclipse, where it draws its power from onboard batteries. This paper addresses this problem by a two-step procedure to perform task scheduling for low-earth-orbit (LEO) satellites exploiting formal methods. It combines cost-optimal reachability analyses of priced timed automata networks with a realistic kinetic battery model capable of capturing capacity limits as well as stochastic fluctuations. The procedure is in use for the automatic and resource-optimal day-ahead scheduling of GomX-3, a power-hungry nanosatellite currently orbiting the earth. We explain how this approach has overcome existing problems, has led to improved designs, and has provided new insights

The molecular heterogeneity of hemocyanin: the role in crustacean adaptive plasticity.

none2Crustacean hemocyanin (He) represents a unique case of molecular heterogeneity among oxygen-carrying proteins. The existence of different genes, encoding single polypeptide chains, constitutes the genetic basis for the inter- and intra-specific polymorphism. In addition, the large number of He subunits within crustacean species, together with their flexible expression, provides an efficient intrinsic mechanism of modulation of oxygen transport. This review presents a description and classification of the various aspects of crustacean He heterogeneity and defines its role in a perspective of crustacean adaptive physiologynoneGIOMI F.; BELTRAMINI MGiomi, Folco; Beltramini, Marian