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Lithium-ion cells (LIC) are emerging as the critical energy source in space applications for spacecraft. The analysis of the failure of small satellites reveals that 41.3% have either suffered partial or total failures in the space environment around Earth, resulting in the accumulation of debris. The defects in batteries caused more failures than thrusters. The present paper details a framework for ensuring the durability of LIC systems in space applications. It is discussed in three verticals viz. a) Durability through Design' that gives prominence to best practices in cell chemistry selection, processing and, design through parametric modelling; b) 'Durability through quality control and testing by the manufacturer and by identifying relevant reliability models; c)'On-orbit management' through the State of Health (SOH) assessment by Random Forest algorithm and a well-equipped intelligent Battery Management System (BMS). Lacuna in standards for cell development process is brought out. Importance of quantitative approach for design, reliability and asset management during space application is highlighted. Use of agile, contemporary techniques of artificial intelligence in this quantitative approach is also discussed. The framework tries to bring out a systematized protocol to be followed during the development and operational life cycle of LIC for ensuring highly reliable systems for space application. [ABSTRACT FROM AUTHOR]

Highlights • We study the problem of agile satellite scheduling with real-time cloud coverage. • A hierarchical scheduling model is established. • A hierarchical scheduling algorithm based on the ant colony algorithm is proposed. • The influence of environmental changes is well-mitigated by the proposed method. • The proposed method can greatly reduce the CPU time and increase the total profit. Abstract The imaging processes of optical satellites can be easily affected by unexpected environmental changes, such as changes in cloud coverage. Given the difficulty to predict environmental uncertainties, traditional offline scheduling methods need a follow-up re-scheduling process that responds to real-time environmental information. This repetitive scheduling processes make the offline fine scheduling process a waste of computational resources. Additionally, the offline scheduling method is quite complex owing to its lack of a hierarchy mechanism. To solve these problems, we propose a hierarchical scheduling method for the real-time scheduling problem. This method divides the scheduling process into three steps: pre-assignment, rough scheduling, and fine scheduling. A hierarchical scheduling algorithm based on ant colony algorithm is proposed. Tests with 36 scenarios show that the calculation time is efficiently reduced with this new mechanism. With this consideration of the dynamic environment, the re-scheduling process becomes unnecessary, meaning the wasting of computational resources is avoided and the solution profit is improved. [ABSTRACT FROM AUTHOR]