Modular Power System: Enabling Scalable Missions for the 1W to 1kW Range
Bibliographic record
Abstract
As small satellites are increasingly tasked with more aggressive and responsive missions, the utility of scalable, modular and standardized avionics has become evident. A power system offering standard interfaces, with high efficiency across wide power throughput ranges, and late-stage expandability is clearly advantageous for a wide range of missions, particularly responsive ones. In order to address this need, the University of Toronto Space Flight Laboratory (SFL) has developed a modular power system (MPS) to facilitate missions with power requirements spanning two orders of magnitude. The presented case study on the modular power system consists of various modules responsible for power conversion and load switching. A central backplane enables the various MPS modules, as well as mission specific modules to either draw from or energize distributed power buses and interface to the systems digital communication busses. The MPS is designed to provide “only as much power system as needed", and the ultra-high efficiency of each card makes the system suitable for missions ranging from the 1-10W nanosatellite class (such as SFL's CanX-7) to the 100-500W class microsatellite (such as SFL's NEMO-HD). The first MPS deployment, on the Canadian Space Agency's Mars Exploration Science Rover (MESR), developed by MacDonald Dettwiler and Associates Ltd., was configured to run sustained loads of 1.3 kW. This paper provides a high-level overview of the MPS, how the system can be configured for missions ranging from cubesats to kW-class small spacecraft, and the impact modular avionics have on the rest of the satellite system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".