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Reducing Combinatorial Redundancy in Mixed-Integer MPC via Ranking-Based Feasible-Set Restriction for Reconfigurable Batteries — arXiv:2609.32029

Source: arXiv (en)
Original: https://arxiv.org/abs/2609.32029
License (as archived): CC0-1.0
Archived: 2026-10-08T01:34:06.551Z
SHA-256 of the archived text: 950e8b84ff51c58ab3998060b52e133a942614d55acc1da2329f9829ab57dcdf
Stable URL of this page: https://metraipolis.com/documento/dc_49b19cd447fa

How to cite

Reducing Combinatorial Redundancy in Mixed-Integer MPC via Ranking-Based Feasible-Set Restriction for Reconfigurable Batteries — arXiv:2609.32029 — arXiv (en), https://arxiv.org/abs/2609.32029 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_49b19cd447fa (Metraipolis archive dc_49b19cd447fa, sha256 950e8b84ff51c58ab3998060b52e133a942614d55acc1da2329f9829ab57dcdf)

BibTeX

@misc{dc49b19cd447fa,
  title = {Reducing Combinatorial Redundancy in Mixed-Integer MPC via Ranking-Based Feasible-Set Restriction for Reconfigurable Batteries — arXiv:2609.32029},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2609.32029},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_49b19cd447fa; sha256 950e8b84ff51c58ab3998060b52e133a942614d55acc1da2329f9829ab57dcdf},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2609.32029. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

When mixed-integer model predictive control must select which of several similar units to activate, many same-size selections can yield closely spaced predicted outcomes, and branch-and-bound may fail to certify optimality within one sampling period. We propose a ranking-based feasible-set restriction for this class of decisions: the units are ordered by a suitability score computed at each sampling instant, and a monotone constraint permits only the top-ranked units to be active. The optimizer then chooses only how many units to activate, so the admissible selections per prediction stage grow linearly instead of combinatorially, while the model, cost function, and remaining constraints are retained. We instantiate the method for reconfigurable battery packs in which each series-connected cell can be bypassed, scoring cells with fixed weights on normalized state of health, state of charge, and voltage headroom. In a 20-cell simulation over a dynamic drive cycle with a 1 s limit per online solve, all active online restricted solves terminate at the root node with certified optimality, compared with 77.83% certification for unrestricted subset selection, and the 95th-percentile solver time is lower by a factor of 13.4. The cycle-mean cell-to-cell standard deviation in state of charge falls 8.7-fold without power curtailment, at the expense of 3.45 times as much cell switching. Solving both problems from identical states along two trajectories shows that the restriction raises the optimal cost by 0.26% and 0.14% on average at states where both solves are certified and uncurtailed.

Tema degli esploratori: calcolo e infrastrutture (retro-catalogo arXiv: annunci del 2026-09-29 in eess.SY).
Categorie arXiv: Systems and Control (eess.SY).
Pagina del lavoro: https://arxiv.org/abs/2609.32029 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-08T01:10:47.811Z dalla pagina https://arxiv.org/catchup/eess.SY/2026-09-29?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).