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Peer-reviewedCC BY 4.0PLOS One

Task-aware conformal power envelopes for multi-horizon spacecraft monitoring

  1. 1School of Computer Science, Northwestern Polytechnical University, Xi’an, China
  2. 2Ningbo Institute, Northwestern Polytechnical University, Ningbo, China

Abstract

Reliable spacecraft power monitoring requires uncertainty estimates across forecast horizons and consistency between primitive electrical states and derived power. We present a task-aware conformal framework that selects joint residual geometry according to downstream power-envelope efficiency. A residual iTransformer produced point centres for five primitive electrical states at 1, 5, and 15 min. Candidate geometries were fitted, selected, and calibrated on chronologically separated complete-orbit blocks, and the final evaluation comprised 25,278 forecast origins from the chronologically subsequent July 2023 telemetry. Across three random-seed runs, the task-aware selector chose a joint box, whereas a residual-volume control selected the sample-covariance ellipsoid. Orbit-balanced primitive-state joint coverage was 0.892 (95% complete-orbit bootstrap confidence interval [CI], 0.883–0.899) at the 90% nominal level and 0.947 (95% CI, 0.943–0.952) at the 95% nominal level. At 90% and 95%, simultaneous coverage of both power channels across all horizons was 0.913 and 0.957. Relative to residual-volume selection, the task-aware method reduced normalized power interval score by 34.3% and 30.3%; the paired absolute reductions were 1.522 (95% CI, 1.505–1.540) and 1.552 (95% CI, 1.534–1.570). Power envelopes were computed from synchronized primitive current and bus-voltage sets. For the selected non-negative box, zero algebraic gap and full interval-image containment follow by construction; the empirical analyses quantify coverage and sharpness. The results demonstrate task-aware geometry selection for BUPT-1 multi-horizon power monitoring.

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BibTeX
@article{lu2026taskaware,
  title = {{Task-aware conformal power envelopes for multi-horizon spacecraft monitoring}},
  author = {Nan Lu and Lehan Cui and Xinian Zhi},
  journal = {PLOS One},
  year = {2026},
  month = oct,
  doi = {10.1371/journal.pone.0360910},
  url = {https://doi.org/10.1371/journal.pone.0360910},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Task-aware conformal power envelopes for multi-horizon spacecraft monitoring
AU  - Nan Lu
AU  - Lehan Cui
AU  - Xinian Zhi
PY  - 2026
DA  - 2026/10/13
JO  - PLOS One
DO  - 10.1371/journal.pone.0360910
UR  - https://doi.org/10.1371/journal.pone.0360910
AB  - Reliable spacecraft power monitoring requires uncertainty estimates across forecast horizons and consistency between primitive electrical states and derived power. We present a task-aware conformal framework that selects joint residual geometry according to downstream power-envelope efficiency. A residual iTransformer produced point centres for five primitive electrical states at 1, 5, and 15 min. Candidate geometries were fitted, selected, and calibrated on chronologically separated complete-orbit blocks, and the final evaluation comprised 25,278 forecast origins from the chronologically subsequent July 2023 telemetry. Across three random-seed runs, the task-aware selector chose a joint box, whereas a residual-volume control selected the sample-covariance ellipsoid. Orbit-balanced primitive-state joint coverage was 0.892 (95% complete-orbit bootstrap confidence interval [CI], 0.883–0.899) at the 90% nominal level and 0.947 (95% CI, 0.943–0.952) at the 95% nominal level. At 90% and 95%, simultaneous coverage of both power channels across all horizons was 0.913 and 0.957. Relative to residual-volume selection, the task-aware method reduced normalized power interval score by 34.3% and 30.3%; the paired absolute reductions were 1.522 (95% CI, 1.505–1.540) and 1.552 (95% CI, 1.534–1.570). Power envelopes were computed from synchronized primitive current and bus-voltage sets. For the selected non-negative box, zero algebraic gap and full interval-image containment follow by construction; the empirical analyses quantify coverage and sharpness. The results demonstrate task-aware geometry selection for BUPT-1 multi-horizon power monitoring.
SN  - 1932-6203
ER  -