Synthesize battery degradation modes via a diagnostic and prognostic model

By Matthieu Dubarry, C. Truchot, Bor Yann Liaw. 2012

904 citations recorded by the source corpus.

Subfields: Automotive Engineering, Electrical and Electronic Engineering, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/121da2f8abb5d5d63b43fa73da7f643fd916c233

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In Automotive Engineering

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In Mechanical Engineering

Citations in the corpus

Battery digital twins: Perspectives on the fusion of models, data and artificial intelligence for smart battery management systems (2020, neutral): “No-table work includes that of Dubarry et al. [35] who analysed the degradation modes in a LFP-Gr cell under diﬀerent modes of degradation and varying electrode loadings.”
Calendar Aging of NCA Lithium-Ion Batteries Investigated by Differential Voltage Analysis and Coulomb Tracking (2017, background): “20,21 As the peaks in the differential voltage spectrum appear more pronouncedly with lower currents, charging and discharging currents of C/20 and below are typically used.”
A Comparison between Electrochemical Impedance Spectroscopy and Incremental Capacity-Differential Voltage as Li-ion Diagnostic Techniques to Identify and Quantify the Effects of Degradation Modes within Battery Management Systems (2017, methodology): “From an electrochemical viewpoint this scenario involves the movement of a low amount of Li-ions and therefore, these phase changes are mostly attributed to structure disordering of the active materials (LAM) [4,12].”
A Generalized SOC-OCV Model for Lithium-Ion Batteries and the SOC Estimation for LNMCO Battery (2016, background): “Reference [19] developed another type of OCV model that generates OCV vs.”
Gaussian Process Regression for In Situ Capacity Estimation of Lithium-Ion Batteries (2017, methodology): “techniques have been conventionally used for detailed cell analyses, such as understanding degradation mechanisms [16], [17]; however, recent studies have considered the use of portions of the IC/DV curve for online capacity estimation [18]–[22].”