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20222025
most citedInterpretable Battery Cycle Life Range Prediction Using Early Degradation Data at Cell Level

38 citations · 66 across the 5 of their papers we have counts for

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5 papers

eess.SY2025

A Practitioner's Guide to Automatic Kernel Search for Gaussian Processes in Battery Applications

Huang Zhang, Xixi Liu, Faisal Altaf +1

Gaussian process (GP) models have been used in a wide range of battery applications, in which different kernels were manually selected with considerable expertise. However, to capt…

eess.SY2025

Spectral Analysis of Approximated Capacity Fade Curvature for Lithium-Ion Batteries

Huang Zhang, Torsten Wik

The techno-economic benefits of incorporating battery degradation into advanced control strategies necessitate the development of degradation diagnosis as an advanced function in b…

eess.SY2025★ 4 cited

A Transferable Physics-Informed Framework for Battery Degradation Diagnosis, Knee-Onset Detection and Knee Prediction

Huang Zhang, Xixi Liu, Faisal Altaf +1

The techno-economic and safety concerns of battery capacity knee occurrence call for developing online knee detection and prediction methods as an advanced battery management syste…

eess.SP2023★ 24 cited

Battery Capacity Knee-Onset Identification and Early Prediction Using Degradation Curvature

Huang Zhang, Faisal Altaf, Torsten Wik

Abrupt capacity fade can have a significant impact on performance and safety in battery applications. To address concerns arising from possible knee occurrence, this work aims for…

eess.SY2022★ 38 cited

Interpretable Battery Cycle Life Range Prediction Using Early Degradation Data at Cell Level

Huang Zhang, Yang Su, Faisal Altaf +2

Battery cycle life prediction using early degradation data has many potential applications throughout the battery product life cycle. For that reason, various data-driven methods h…