activity
20142023
most citedGaussian process regression for forecasting battery state of health

730 citations · 4k across the 41 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

eess.SP2023★ 5 cited

Fast dynamic time warping and clustering in C++

Volkan Kumtepeli, Rebecca Perriment, David A. Howey

We present an approach for computationally efficient dynamic time warping (DTW) and clustering of time-series data. The method frames the dynamic warping of time series datasets as…

cs.LG2023★ 56 cited

Predicting Battery Lifetime Under Varying Usage Conditions from Early Aging Data

Tingkai Li, Zihao Zhou, Adam Thelen +2

Accurate battery lifetime prediction is important for preventative maintenance, warranties, and improved cell design and manufacturing. However, manufacturing variability and usage…

eess.SY2023★ 9 cited

Learning battery model parameter dynamics from data with recursive Gaussian process regression

Antti Aitio, Dominik Jöst, Dirk Uwe Sauer +1

Estimating state of health is a critical function of a battery management system but remains challenging due to the variability of operating conditions and usage requirements of re…

eess.SY2023★ 130 cited

Electrochemical impedance spectroscopy beyond linearity and stationarity - a critical review

Noël Hallemans, David Howey, Alberto Battistel +7

Electrochemical impedance spectroscopy (EIS) is a widely used experimental technique for characterising materials and electrode reactions by observing their frequency-dependent imp…

math.OC2023★ 4 cited

Constrained optimal control of monotone systems with applications to battery fast-charging

Ross Drummond, Nicola E. Courtier, David A. Howey +2

Enabling fast charging for lithium ion batteries is critical to accelerating the green energy transition. As such, there has been significant interest in tailored fast-charging pro…