Performance Optimization and Verification of a New Type of Solar Panel for Microsatellites

Abstract

In this paper, a new method of replacing the conventional honeycomb aluminum panel with 3D metal printing on the microsatellite is presented. The multiobjective optimization method is used to optimize the temperature difference, compression strength, shear strength, and weight of the new type of solar panel structure. The relationships between the structural parameters and optimization targets are established, and the influence of five factors on thermal and structural properties is analyzed. Finally, a group of better structural parameters of the panel is obtained. The relative deviations between simulation analysis and model are 27.45%, 6.12%, 1.365%, and 3.27%, respectively. The optimization results show that the regression model can be used to predict thermal and structural properties of the panel, and the establishment of the model is effective. The analysis results show that the performances can be improved by 91.62%, 46.94%, 17.91%, and 10.28%, respectively. The optimized results are used for 3D metal printing, and the new type of solar panel is obtained. It is proved that the method can effectively improve the thermal and structural properties of the panel and can effectively shorten the development and manufacture cycle of the panel and also reduce the cost. It has high engineering application value.

Metal Additive Manufacturing for Satellites and Rockets

“…Similarly, metasurface antennas especially for Cu-beSats and SmallSats were built by metal additive manufacturing combined with CNC milling [41]. Larger structures, such as a solar panel, were prepared by SLM, allowing for printing a double-layer aluminum structure with I-shaped beams (Figure 4), which was found to show significantly increased shielding, improved mechanical properties, and reduced mass, as compared to a conventional aluminum honeycomb panel [42]. Generally, diverse parts of microsatellites have been prepared by metal additive manufacturing, interestingly not only in the laboratory, but also by companies such as Rocket Lab, SpaceX, or Blue Origin [43][44][45].…”

Low-Velocity Impact Localization on a Honeycomb Sandwich Panel Using a Balanced Projective Dictionary Pair Learning Classifier

“…In aerospace structures, honeycomb panels are widely used as wall panels and wing panels. Carbon-fiber aluminum honeycomb sandwich panels are lightweight, have strong load-bearing performance, and provide vibration isolation and energy absorption [ 4 , 5 ]. However, when subjected to low-velocity impacts, the honeycomb panel structures are prone to damage such as core collapse and surface layer tearing, which affects the performance and reliability of the material structure [ 6 , 7 ].…”