UC San Diego

Multidisciplinary design optimization is playing an increasingly important role in the design of engineering systems. One example is the design of a CubeSat. Multidisciplinary optimization provides a way to evaluate complex tradeoffs involving tight power and mass budgets. However, existing methods are not able to consider swarms of CubeSats, which are becoming increasingly common. This thesis presents a new multidisciplinary optimization and modeling method for CubeSat swarms operation, including the multiple disciplines of orbita mechanics, attitude control, propulsion, and communication. The approach efficiently handles thousands of variables and successfully achieves high-fidelity optimization with respect to strict CubeSats alignment and separation constraints, and limited propellant and power. In terms of optimization results, the CubeSat swarm increases the total data download of chief communication spacecraft by 52.9% compared to the original design, yielding improvements of around 15%. improvements in the delta-v and succeeding in controlling the alignment of three CubeSats within a 300mm threshold during scientific observation phase.