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Abstract

With the rapid evolution of commercial space markets in the new space era, satellite design philosophy is transitioning from "performance supremacy" toward "cost-effectiveness priority." This research concentrates on solar arrays, a critical component representing 15%-20% of satellite costs, addressing limitations in traditional design methodologies that inadequately coordinate user requirements and lack systematic frameworks for cost-performance collaborative optimization. We propose a solar array optimization methodology predicated on the integration of Quality Function Deployment (QFD) and the Theory of Inventive Problem Solving (TRIZ). This methodology incorporates cost dimensions through an extended QFD matrix, employs TRIZ to resolve technical contradictions, and develops a multi-constraint optimization model utilizing the NSGA-II multi-objective optimization algorithm. Through empirical validation with a commercial remote sensing satellite case study, results demonstrate that the optimized solar array design achieves a 12.5% cost reduction while simultaneously realizing a 20.8% improvement in specific power ratio, 0.04% enhancement in reliability, and 39.4% extension in operational lifespan. This cost-performance balanced optimization methodology provides practical engineering guidance for the commercial aerospace sector and offers valuable reference for promoting innovative satellite design in cost-sensitive environments.

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