Year: 2026
Type: article
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.
Source: PLoS ONE
Authors: Nan Lu, Lehan Cui, Xinian Zhi
Institution: Northwestern Polytechnical University
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,382
Award: G9001173131
OpenAlex ID: W7221699006