FRAMEWORK FOR CUBESATS MISSION MANAGEMENT, DESIGN, AND OPTIMIZATION

This doctoral work proposes a practical framework for the design and management of CubeSat missions. In recent years, CubeSats have moved from their original intent of educational nanosatellites to platforms that can deliver high scientific and commercial value. This mission performance improvement comes with a rise in their complexity. Yet, most CubeSat teams remain small, with limited experience and constrained budgets. The goal of this work is to streamline the way such missions are designed and managed, keeping the rigor that space projects demand while avoiding unnecessary overhead. Most of the procedures and guidelines here proposed address specifically the early phase of the design, since it is proven that most CubeSat mission failures occur due to poor preparation and bad design choices during this phase. The first part addresses mission management. It looks at the practices commonly used in CubeSat projects and explains how to tailor the ECSS family of standards, so they serve the mission success best. The approach starts from stakeholder needs, turns them first into clear and verifiable objectives, and then into requirements that can guide design and verification. Since CubeSats heavily rely on Commercial-Off-The-Shelf components, a deep review of the current COTS market for CubeSats has been performed, focusing on the key performance indicators to be considered. The review serves two purposes: it gives a picture of what is possible today and it provides the raw material for a structured database, which has been compiled with vendor specifications and captures mass, volume, power, interfaces, and performance attributes across all major subsystems. With the database in place, the component selection problem is formulated explicitly, as a multiple-choice-multi dimensional Knapsack Problem, where the goal is to select the components of the CubeSat maximizing its performance but respecting global budgets on mass, power, and volume. External configuration is handled next with a streamlined method for arranging solar arrays and platform elements, while internal configuration is treated as a simplified instance of the three-dimensional Bin Packing Problem. The novel proposed approach avoids all in one formulations that are hard to tune and difficult to apply in a real system. Instead, the internal volume is partitioned into containers that reflect mounting surfaces, harness paths, thermal zones, and accessibility; containers are described with fuzzy labels that capture the preferences of the designer. In the same way, components receive the same kind of fuzzy characterization, then an assignment stage matches components to containers using the Hungarian Algorithm. This approach is effective because it encodes the engineering judgment in a form the optimizer can use. The design thus obtained is validated through the standard technical budgets: mass and power are closed with margins, communications performance is checked against link opportunities and duty cycles. The design is then coupled with an orbital and attitude simulation. This step exercises a realistic operational scenario, checks energy balance across illumination cycles, looks at access windows and data return, and verifies that the configuration can deliver the intended mission results. The framework has been applied and refined on two real missions, EXCITE and IONSAT. EXCITE is a 12U CubeSat technology demonstration mission led by the University of Pisa, with the Author acting as systems engineer and technical responsible, that aims to test five payload technologies in orbit. As of writing, the mission has completed Phase A. The work on this dissertation has served as a proving ground for the end-to-end design flow, from requirement capture to the selection of components, configuration of the spacecraft, and technical budgets closure. IONSAT is a very low Earth orbit mission concept currently in Phase C led by the École Polytechnique de Paris. Within IONSAT, the framework demonstrated its effectiveness by consolidating information that had become fragmented across a student led project with contributors from multiple academic years. This consolidation restored a single source of truth for requirements, interfaces, and budgets. Whenever a mandatory payload change occurred, the same framework enabled a rapid update of the component catalogue, a swift reconfiguration of the flight design, and a structured re verification of the technical budgets and operational scenario. The result was a controlled change process with traceable decisions and minimal disruption to the schedule. The results of this work advance the state of the art by providing a general approach for CubeSat mission design and management, not dedicated to one single particular domain but instead aimed at defining a usable set of guidelines, as demonstrated by two real life applications.