A model-based framework is necessary to systematically represent system elements and operational constraints across different subsystems, thereby improving manageability. By structuring the interactions between subsystems within an architecture, the model becomes more understandable and enables consistent handling of constraints originating from various domains. This structured representation supports the systematic evaluation of large satellite constellations, particularly under VLEO-specific constraints.

In the doctoral seminar, the presentation will demonstrate a model-driven approach that fundamentally simplifies the complex process of satellite constellation task planning. By inputting the stakeholder’s mission requirements directly into the model-based framework, and connecting the configured model to the dynamics simulation and the optimization algorithm, we provide an automated method capable of generating scheduling algorithms for satellites on demand. The central goal of our framework is to enable stakeholders to define the mission and its associated requirements directly, allowing the system to automatically configure an optimized, feasible task planning algorithm. However, this model-based design tool is not intended for launching new satellites or solving the optimal constellation design problem. Instead, it supports users in selecting and configuring satellites that are already operating in orbit. The core of the modeling framework will be shown as a structured meta-model defined in the Eclipse Modeling Framework (EMF).

Furthermore, the study will include a discussion of VLEO specific constraints including atmospheric drag, propulsion system related constraints etc. The framework will be extended to large-scale constellation scenarios, where more than 20 satellites collaboratively execute the distributed optimization process. Finally, simulation results based on the OneWeb satellite constellation will be presented to evaluate the performance of the proposed algorithm, followed by a discussion of its advantages and potential limitations.