Advanced EPS Component Models for Accurate Satellite EPS Simulation
Bibliographic record
Abstract
Detailed models for all EPS components are required for accurate Electric Power System (EPS) simulations of satellites in various LEO, MEO, and GEO missions. Older and outdated models had used various power margins to over-estimate the size and weight of the satellite EPS for a given mission. Today’s models incorporate the use of many sets of test data from various testing facilities to much better and more accurately predict the behavior of each component. This paper summarizes the library of the various component models currently used in such satellite simulations. The components modeled include solar array cells, solar array string and group diodes, solar array harnesses, battery cells, battery recharging efficiencies, battery charge control, battery heaters, bus diodes, cabling, and wiring. The models use various input variables in their simulation, including the effects of bus voltage, current, temperature, and age. These component models are used within the Power Suite Tools code within Lockheed Martin to perform sizing trades and BOL and EOL margin analyses. They can also be used to compare EPS behavior from on-orbit data, and to predict future transient behavior in worst-case scenarios. One major concern in the operation of such satellite systems is the prediction of the maximum state-of-discharge (SOD) of the batteries during the most challenging mission phases. The use of these PTS code models enables much more accurate simulations of EPS behavior, battery degradation, and lifetime estimates that are needed in the Aerospace Industry today.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".