Under Hankel-DMDc, lithium-ion SOC emerges as the marginally stable Koopman mode nearest the unit circle and yields a usable SOC-sensitive observable after min-max scaling.
Towards a smarter battery management system: A critical review on battery state of health monitoring methods
2 Pith papers cite this work, alongside 961 external citations. Polarity classification is still indexing.
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Framework extracts capacity, degradation rate, and dV/dQ features from 25 BESS modules that statistically distinguish 25 faulty cell groups from 325 non-faulty ones, while resistance does not.
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Koopman Spectral Analysis of Lithium-Ion Battery Dynamics: State of Charge as a Marginally Stable Observable
Under Hankel-DMDc, lithium-ion SOC emerges as the marginally stable Koopman mode nearest the unit circle and yields a usable SOC-sensitive observable after min-max scaling.
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Health feature extraction from battery energy storage system field fault data
Framework extracts capacity, degradation rate, and dV/dQ features from 25 BESS modules that statistically distinguish 25 faulty cell groups from 325 non-faulty ones, while resistance does not.