Satellite Component Selection with Mixed Integer Nonlinear Programming
Satellite Component Selection with Mixed Integer Nonlinear Programming
复制标题
使用混合整数非线性规划的卫星组件选择
DOI：
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发表时间：
2020
期刊：
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通讯作者：
J. Norheim
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文献类型：
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作者：
J. Norheim
航天器概念设计往往是一个费力的手动过程，工程师在设计一致的同时反复评估性能，即满足系统级别的预算：质量、功率、链路预算等。问题的一个有趣的部分是，虽然可以从头开始定制设计航天器的所有部件，但通过选择满足所需功能的现有组件可以节省开发工作。在立方体卫星的范式中，几乎完全使用目录组件（可商用现成）建造航天器尤其有吸引力。然而，将设计限制在组件上也带来了一系列挑战：迭代满足所有预算的组件组合可能非常耗时，因为一个组件可能会平衡质量预算，同时不平衡功率预算。此外，随着组件目录不断增长，枚举和考虑所有组合变得不可能，并且很可能会错过可能以更低的成本或更高的性能实现的设计。这里提出了一种应用混合整数非线性规划（MINLP）的新颖方法，这是一种用于组件选择的通用公式。该研究应用了航天器设计中常见的非线性方程的变换方法，并结合了最先进的求解器，可以使用这些变换来非常有效地解决问题。优化速度非常快：研究的案例不到一分钟，并且可以扩展目录，而求解器运行时间不会呈指数增长。这反过来又使得改变任务背后的假设并快速枚举针对不同任务约束的最佳设计变得非常便宜。本文提出了地球观测卫星的简单模型，以及通信和电力系统、轨道动力学、动量管理和卫星寿命的早期概念设计模型。然后介绍了应用于每个不同学科的非线性模型的通用 MINLP 组件选择公式和转换。为所需的四个组件提供了真实和想象的硬件选项的小目录：观测有效载荷、电池、太阳能电池和天线。对四个不同的任务进行了评估和比较，其中分辨率从低到中再到高，卫星的寿命在 3 到 15 年之间变化，展示了这种新颖方法的多功能性。
Spacecraft conceptual design tends to be a laborious and manual procedure where engineers iterate on evaluating performance while having a consistent design, i.e., satisfying budgets at the system level: mass, power, link budget, etc. One interesting part of the problem is that although one could start from scratch to custom design all parts of the spacecraft, development efforts can be saved by picking existing components that satisfy the needed functionality. Building a spacecraft almost exclusively out of catalog components - available commercially off-the-shelf - is especially attractive within the paradigm of CubeSats. Restricting the design to components, however, poses its own set of challenges: iterating through combinations of components that satisfy all budgets can be time consuming as one component might balance the mass budget while unbalancing the power budget. Additionally, as component catalogs keep growing, it becomes impossible to enumerate and consider all combinations, and there is a good chance to miss designs that could come at a lower cost, or a higher performance. Here a novel approach is presented applying mixed-integer nonlinear programming (MINLP), a generalized formulation for component selection. The research applies transformations methods of the nonlinear equations commonly encountered in spacecraft design, in combination with state of the art solvers that can use these transformations to very efficiently solve the problem. The optimization is very fast: less than a minute for the case studied, and the catalog can be expanded without an exponential growth in the solver run time. This in turn makes it very cheap to change the assumptions behind the mission and quickly enumerate optimal designs for different mission constraints. The paper presents a simple model for an Earth Observation satellite, with early conceptual design models for the communications and power system, orbital dynamics, momentum management and satellite lifetime. It then presents the general MINLP component selection formulation and transformations that were applied to the nonlinear models for each different discipline. A small catalog of real and imagined hardware options is presented for four components needed: observation payload, battery, solar cell and antenna. Four different missions are evaluated and compared where the resolution is changed from low to mid to high, and the lifetime of the satellite is changed between 3 and 15 years, showcasing the versatility of this novel method.