Abstract: Traditional control methods exhibit inherent limitations in regulating the air environment of manned sealed cabins. To address these limitations, an intelligent operation and maintenance system based on digital twin technology was developed to achieve more efficient environmental control and intervention, which significantly enhanced the system’s adaptability to complex disturbances. In this intelligent framework, digital twins are employed to integrate high-fidelity virtual models with real-time data from multi-sensor networks, thereby enabling comprehensive monitoring and dynamic prediction of the cabin air environment. This study reviewed the implementation roadmap for such intelligent systems, with particular focus on the construction and optimization of high-fidelity air-environment models. Emphasizing the balance between model accuracy and real-time performance, the evolution of existing technologies was systematically traced, and their applicability boundaries within digital-twin systems were clarified. The results provide theoretical foundations and technical support for the current and future optimization of air-environment regulation in manned spacecraft sealed cabins.