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Automated variability evaluation using a model-based approach with an implementation in CubeSat
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DOI：10.1016/j.jss.2026.112965.png)
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Abstract
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The design of a Cyber-Physical System (CPS) presents significant challenges due to a vast configuration space and intensive dependencies among subsystems. Each subsystem requires careful selection and precise sizing of components from diverse hardware product lines to meet specific functional and performance requirements. This complexity increases as designers must balance objectives and constraints while accounting for the cascading effects of decisions across interconnected subsystems, highlighting how a small change in one area can greatly affect the overall system function and performance. However, there is limited research developing an automated model-based framework with the aim to address both challenges at once: architecture variability modeling and design evaluation of a CPS. Therefore, we propose a framework that integrates a novel variability-aware modeling methodology using the function-to-form concept, i.e., Architecture Design Space Graph (ADSG), with a numerical domain-dependency modeling named Multidisciplinary Design Optimization (MDO). The functional framework is then demonstrated through a use case of CubeSat design process, including the automated generation of architecture instances and numerical design space exploration. The framework has the potential to be implemented to other CPS as it provides generic building blocks in the form of an architecture modeler, generator, translator, and evaluator by leveraging the combination of ADSG and MDO.
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