Preliminary Design of Low-Energy, Low-Thrust Transfers to Halo Orbits Using Feedback Control

Jagannatha, Bindu B.; Bouvier, Jean-Baptiste; Ho, Koki

doi:10.2514/1.g003759

Cited by 12 publications

(10 citation statements)

References 30 publications

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“…Thus, by splitting the mass transformation constraint between Equation (12) and (13) in this case, the propellant consumption is implicitly considered even though the commodity denoting propellant is not explicitly shown.…”

Section: Fig 4 Piecewise Linear Approximation Of Trajectory Performamentioning

confidence: 99%

“…Obtaining these low-thrust trajectories is a computationally intensive process involving design of the many-revolution thruster-on trajectory segment required to depart/arrive at the Earth/moon [32,[46][47][48][49][50]. Since most existing low-thrust trajectory design methods did not lend themselves well to quick parametric trade studies, our previous studies developed a computationally efficient and reasonably accurate method for calculating low-thrust transportation performance metrics over the considered arcs in the cislunar region [12,13]. The interested reader is directed to these previous works for a complete description, which is summarized here for clarity and continuity.…”

Section: Cargo Delivery For Low-thrust Sep Tugsmentioning

confidence: 99%

“…We appreciate Prof. Natashia Boland's feedback on this work. Arc ∆v, km/s TOF, days LEO to/from L1 [29] 3.375 21 L1 to/from LLO [13] 0.259 28 LEO to/from L2 [29] 3.336 17 L2 to/from LLO [13] 0.375 27 [54]. ++ Used to size the required droptanks.…”

Section: Acknowledgmentmentioning

confidence: 99%

“…The developed formulation incorporates surrogate models for trajectory evaluation and uses them to concurrently optimize the campaign logistics and trajectory selection. The surrogate models for our case study are either obtained from existing trajectory models for high-thrust propulsion or 3 derived from applying the computationally efficient Q-law low-energy low-thrust trajectory design method [12,13] to the current problem.Mathematical modeling and optimization of space logistics developed in this paper can support campaign-level architectural decisions where different propulsion technologies can be traded off to achieve overall exploration goals. The decisions made in this manner have a higher potential of sustaining long-term human and robotic space exploration than traditional mission-wise analyses.…”

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confidence: 99%

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confidence: 99%

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Event-Driven Network Model for Space Mission Optimization with High-Thrust and Low-Thrust Spacecraft

Jagannatha

2020

Journal of Spacecraft and Rockets

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Numerous high-thrust and low-thrust space propulsion technologies have been developed in the recent years with the goal of expanding space exploration capabilities; however, designing and optimizing a multi-mission campaign with both high-thrust and low-thrust propulsion options are challenging due to the coupling between logistics mission design and trajectory evaluation. Specifically, this computational burden arises because the deliverable mass fraction (i.e., final-to-initial mass ratio) and time of flight for low-thrust trajectories can can vary with the payload mass; thus, these trajectory metrics cannot be evaluated separately from the campaignlevel mission design. To tackle this challenge, this paper develops a novel event-driven space logistics network optimization approach using mixed-integer linear programming for space campaign design. An example case of optimally designing a cislunar propellant supply chain to support multiple lunar surface access missions is used to demonstrate this new space logistics framework. The results are compared with an existing stochastic combinatorial formulation developed for incorporating low-thrust propulsion into space logistics design; our new approach provides superior results in terms of cost as well as utilization of the vehicle fleet. The eventdriven space logistics network optimization method developed in this paper can trade off cost, time, and technology in an automated manner to optimally design space mission campaigns.(GMCNF) model [5,6]. These space logistics methods have been extended to campaign-level mission design framework using a time-expanded network by Ho et al [7,8]. These frameworks approach the problem of campaign design through a logistics-driven perspective. Other works such as the EXAMINE framework [9] and the graph-theory-based space system architectures model developed by Arney et al. [10] can compare and/or optimize user-input system architecture scenarios.A critical limitation of the conventional space logistics design methods referenced above is that they are unable to account for the use of low-thrust vehicles for transportation. More specifically, the conventional methods assumed a decoupling between logistics mission design and trajectory evaluation, where the mission design model takes pre-computed trajectory metrics such as the final-to-initial mass ratio (or ∆v) and time of flight for each arc as inputs and then optimize the mission architecture including the logistics flows of propellant, payload, and other commodities. This approach is effective for a campaign with a fleet of high-thrust spacecraft, and responded well to the background that many past space exploration campaigns considered only high-thrust spacecraft options (e.g., chemical propulsion). However, given the significant advancements made in low-thrust propulsion technology (e.g., SEP) in recent years, there is a growing interest in the question of how low-thrust spacecraft can be optimally integrated into a space exploration campaign. Thus, we need a mathematical fram...

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Section: Fig 4 Piecewise Linear Approximation Of Trajectory Performamentioning

confidence: 99%