Deciding the right way to energy a CubeSat is among the biggest challenges when designing a modular spacecraft. Tradeoffs in photo voltaic panel measurement, battery measurement, and energy consumption ranges are all key issues when deciding on components and mission structure. To assist with these design selections, a paper from researchers in Ethiopia and Korea describes a brand new machine-learning algorithm that helps CubeSat designers optimize their energy consumption, guaranteeing these little satellites have a greater probability of fulfilling their objective.
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