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Preprint . 2026
License: CC BY
Data sources: Datacite
ZENODO
Preprint . 2026
License: CC BY
Data sources: Datacite
ZENODO
Preprint . 2025
License: CC BY
Data sources: Datacite
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A Dissociation Test for Causal Attribution Under Partial Observability: Separate Memory Channels for Rate Pressure and Capacity Damage in Li-Ion Batteries

Authors: Ollar, Austin;

A Dissociation Test for Causal Attribution Under Partial Observability: Separate Memory Channels for Rate Pressure and Capacity Damage in Li-Ion Batteries

Abstract

This preprint presents a dissociation-based attribution framework for separating two latent degradation channels in lithium-ion battery capacity trajectories under partial observability. We define two lightweight memory proxies representing rate-type stress (charge-rate history) and baseline-type stress (manufacturer batch offset), and evaluate their selective identifiability using ablation tests, permutation controls, bootstrap stability analysis, and a negative identifiability case study. Results demonstrate cross-dataset dissociation under controlled conditions and principled non-significance under structural confounding. The work is positioned as a falsifiable test of a lifecycle attribution hypothesis rather than a claim of universal validation.

Keywords

machine learning, lithium-ion batteries, dissociation test, partial observability, identifiability, energy systems, battery degradation

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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