Sequential Low-Thrust Orbit-Raising of All-Electric Satellites
In this paper, we consider a recently developed formulation of the electric orbit-raising problem that utilizes a novel dynamic model and a sequence of optimal control sub-problems to yield fast and robust computations of low-thrust trajectories. This paper proposes two enhancements of the computati...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-06-01
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| Series: | Aerospace |
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| Online Access: | https://www.mdpi.com/2226-4310/7/6/74 |
| _version_ | 1797566153334194176 |
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| author | Pardhasai Chadalavada Tanzimul Farabi Atri Dutta |
| author_facet | Pardhasai Chadalavada Tanzimul Farabi Atri Dutta |
| author_sort | Pardhasai Chadalavada |
| collection | DOAJ |
| description | In this paper, we consider a recently developed formulation of the electric orbit-raising problem that utilizes a novel dynamic model and a sequence of optimal control sub-problems to yield fast and robust computations of low-thrust trajectories. This paper proposes two enhancements of the computational framework. First, we use thruster efficiency in order to determine the trajectory segments over which the spacecraft coasts. Second, we propose the use of a neural network to compute the solar array degradation in the Van Allen radiation belts. The neural network is trained on AP-9 data and SPENVIS in order to compute the associated power loss. The proposed methodology is demonstrated by considering transfers from different geosynchronous transfer orbits. Numerical simulations analyzing the effect of thruster efficiency and average power degradation indicate the suitability of starting the maneuver from super-geosynchronous transfer orbits in order to limit fuel expenditure and radiation damage. Furthermore, numerical simulations demonstrate that proposed enhancements are achieved with only marginal increase in computational runtime, thereby still facilitating rapid exploration of all-electric mission scenarios. |
| first_indexed | 2024-03-10T19:22:38Z |
| format | Article |
| id | doaj.art-3fb76da90dfb406bbc62454bc6ae5bd0 |
| institution | Directory Open Access Journal |
| issn | 2226-4310 |
| language | English |
| last_indexed | 2024-03-10T19:22:38Z |
| publishDate | 2020-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Aerospace |
| spelling | doaj.art-3fb76da90dfb406bbc62454bc6ae5bd02023-11-20T02:51:01ZengMDPI AGAerospace2226-43102020-06-01767410.3390/aerospace7060074Sequential Low-Thrust Orbit-Raising of All-Electric SatellitesPardhasai Chadalavada0Tanzimul Farabi1Atri Dutta2Aerospace Engineering , Wichita State University, 1845 Fairmount St Box 42, Wichita, KS 67260, USAAerospace Engineering , Wichita State University, 1845 Fairmount St Box 42, Wichita, KS 67260, USAAerospace Engineering , Wichita State University, 1845 Fairmount St Box 42, Wichita, KS 67260, USAIn this paper, we consider a recently developed formulation of the electric orbit-raising problem that utilizes a novel dynamic model and a sequence of optimal control sub-problems to yield fast and robust computations of low-thrust trajectories. This paper proposes two enhancements of the computational framework. First, we use thruster efficiency in order to determine the trajectory segments over which the spacecraft coasts. Second, we propose the use of a neural network to compute the solar array degradation in the Van Allen radiation belts. The neural network is trained on AP-9 data and SPENVIS in order to compute the associated power loss. The proposed methodology is demonstrated by considering transfers from different geosynchronous transfer orbits. Numerical simulations analyzing the effect of thruster efficiency and average power degradation indicate the suitability of starting the maneuver from super-geosynchronous transfer orbits in order to limit fuel expenditure and radiation damage. Furthermore, numerical simulations demonstrate that proposed enhancements are achieved with only marginal increase in computational runtime, thereby still facilitating rapid exploration of all-electric mission scenarios.https://www.mdpi.com/2226-4310/7/6/74all-electric satelliteselectric orbit-raisinglow-thrust trajectory optimizationmulti-revolution orbit transfersolar array degradationartificial neural network |
| spellingShingle | Pardhasai Chadalavada Tanzimul Farabi Atri Dutta Sequential Low-Thrust Orbit-Raising of All-Electric Satellites Aerospace all-electric satellites electric orbit-raising low-thrust trajectory optimization multi-revolution orbit transfer solar array degradation artificial neural network |
| title | Sequential Low-Thrust Orbit-Raising of All-Electric Satellites |
| title_full | Sequential Low-Thrust Orbit-Raising of All-Electric Satellites |
| title_fullStr | Sequential Low-Thrust Orbit-Raising of All-Electric Satellites |
| title_full_unstemmed | Sequential Low-Thrust Orbit-Raising of All-Electric Satellites |
| title_short | Sequential Low-Thrust Orbit-Raising of All-Electric Satellites |
| title_sort | sequential low thrust orbit raising of all electric satellites |
| topic | all-electric satellites electric orbit-raising low-thrust trajectory optimization multi-revolution orbit transfer solar array degradation artificial neural network |
| url | https://www.mdpi.com/2226-4310/7/6/74 |
| work_keys_str_mv | AT pardhasaichadalavada sequentiallowthrustorbitraisingofallelectricsatellites AT tanzimulfarabi sequentiallowthrustorbitraisingofallelectricsatellites AT atridutta sequentiallowthrustorbitraisingofallelectricsatellites |