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Systems Engineering
Article . 2026 . Peer-reviewed
License: CC BY NC ND
Data sources: Crossref
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Tailoring Model‐Based Systems Engineering for Sub‐100 g PlanarSats: A Power‐First View Stack

Authors: Mehmet Şevket Uludaǧ; Alim Rüstem Aslan;

Tailoring Model‐Based Systems Engineering for Sub‐100 g PlanarSats: A Power‐First View Stack

Abstract

ABSTRACT This paper addresses how to apply model‐based systems engineering (MBSE) to ultrasmall planar satellites under severe power and resource constraints. PlanarSats are sub‐100‐gram spacecraft built as single printed‐circuit boards where the same surface must host both electronics and solar cells, so power generation, geometry, and component placement are tightly coupled. Conventional MBSE with a full requirements–functional–logical–physical (RFLP) stack is often too heavy for the small, fast teams that build these missions. We propose a tailored MBSE framework that keeps compact requirements and functional view, but makes a combined Physical/Electrical view the central driver. This view uses a power‐first sizing methodology based on current best estimate, maximum expected value, and maximum possible value of power, and derives an operational power envelope that links surface area, mode power, and allowable Sun incidence angles. Operational and verification views are reduced to a simple power‐aware state machine and a small requirement‐to‐test matrix. The framework is demonstrated on a conceptual sub‐100‐gram, batteryless radiation‐sensing PlanarSat in low Earth orbit, showing that the design remains power‐positive in all planned sunlit modes while using a reduced set of MBSE artefacts maintained in a lightweight, tool‐supported modeling environment. The approach is intended to help small teams retain traceability and explicit constraints for PlanarSat missions without the overhead of enterprise‐scale MBSE deployment. The framework is proposed and evaluated analytically on this conceptual case study; no hardware or flight data are presented.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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