Model-based trade-off analysis of aerospace equipment with coupling handling

As MBSE becomes increasingly prevalent in the aerospace sector, model complexity has surged dramatically. This makes highly reusable, loosely coupled designs critically important, with the scientific quantification of coupling directly impacting system quality, efficiency and even safety. However, during the critical tradeoff phase, existing methods generally fail to fully leverage the rich data and structural information embedded within MBSE models. This results in decisions lacking deep insight, potentially wasting valuable information and increasing the risk that design flaws will only be exposed during system integration. To address this, this paper proposes a novel model-based approach for complex coupling tradeoff analysis in aerospace equipment. This method proposes the Coupling Influence Index (CII) as a quantitative indicator that integrates static and dynamic coupling, and as a coupling criterion within the ‘architecture-behavior-tradeoff’ closed loop. It first quantifies model coupling by dividing it into static and dynamic coupling, then introducing the probabilistic weighted coefficient of variation entropy weight method for objective and comprehensive trade-off analysis. This approach aims to fully extract multidimensional information from MBSE models, enabling data-driven global trade-off decisions across the entire ‘architecture-to-behavior’ chain. It provides a more scientific and precise basis for decision-making in the development of complex aerospace equipment.