Surrogate-Assisted Multidisciplinary System Design Optimization of Lunar Transfer Vehicles

In upcoming missions to the moon, transporting as much payload as possible within a limited timeframe is a critical challenge. However, identifying an optimal spacecraft system design is complex due to the interdependence of multiple subsystems, each requiring distinct design methodologies. Multidisciplinary design optimization (MDO), which concurrently evaluates various disciplines to identify an optimal design, presents a promising solution. Most existing research on MDO focuses on aircraft, launch vehicles, and Earth-orbiting satellites. In contrast, missions to cislunar space and beyond involve numerous candidate trajectories with varying geometries, significantly influencing spacecraft system design. This paper introduces a multidisciplinary system design optimization technique specifically for lunar transport missions using electric propulsion. A lunar transfer trajectory optimization problem is formulated that incorporates spacecraft design parameters. A surrogate model is developed to predict transportation performance based on these design parameters. By employing the surrogate model, an optimal system design is achieved that maximizes payload mass while minimizing flight time. The results elucidate the structure of the solution space for the spacecraft system design problem, enabling the automatic identification of feasible and optimal designs.