Differential thermal voltammetry for tracking of degradation in lithium-ion batteries

By Billy Wu, Vladimir Yufit, Yu Merla, Ricardo Martinez-Botas, Nigel P. Brandon, Gregory J. Offer. 2014

140 citations recorded by the source corpus.

Subfields: Automotive Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/89e5e3a2477be7102f7de7fdd441c4592081a368

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In Automotive Engineering

In Electrical and Electronic Engineering

Citations in the corpus

Gaussian Process Regression for In Situ Capacity Estimation of Lithium-Ion Batteries (2017, background): “Differential Thermal Voltammetry (DTV) is another approach to capacity estimation that has been introduced very recently [41], [42], [43].”
Lithium Battery State-of-Health Estimation via Differential Thermal Voltammetry With Gaussian Process Regression (2021, methodology): “[25] proposed a prior knowledge-based NN (PKNN) and the Markov chain method”
Novel application of differential thermal voltammetry as an in-depth state-of-health diagnosis method for lithium-ion batteries (2016, methodology): “[11] presented a novel in-situ on-board diagnosis method termed DTV as a faster complementary tool to the existing in-situ methods.”
State-of-Health Estimation Based on Differential Temperature for Lithium Ion Batteries (2020, methodology): “Although the peaks in the DTV curves have been reported to be tightly related to battery degradation [19], differentials of both temperature and voltage together will inevitably lead to difficulties in the data processing.”
Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review (2019, methodology): “2 Differential thermal voltammetry (DTV) analysis DTV analysis can be used as a complementary tool to existing SOH diagnostic techniques, which combines the concept of IC analysis with temperature measurements to infer thermodynamic information about the electrode materials [55,64].”
Battery Health Prognosis for Electric Vehicles Using Sample Entropy and Sparse Bayesian Predictive Modeling (2016, methodology): “Signal processing was also used for in situ diagnosis of battery degradation, including incremental capacity analysis (ICA) [37], differential voltage analysis (DVA) [38], differential thermal voltammetry (DTV) [39], and so forth.”