Huang Zhang

Doctoral Student at Automatic Control

Huang Zhang is an industrial Ph.D. student at Automatic Control Group, in collaboration with Volvo Group. His research interests include uncertainty estimation in machine learning and deep learning, and optimal control. His current research applications include battery degradation diagnostics and prognostics, battery lifetime prediction, and techno-economic analysis of second-life batteries.

Source: chalmers.se
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Showing 7 publications

2024

Battery capacity knee-onset identification and early prediction using degradation curvature

Huang Zhang, Faisal Altaf, Torsten Wik
Journal of Power Sources. Vol. 608
Journal article
2024

Scenario-Aware Machine Learning Pipeline for Battery Lifetime Prediction

Huang Zhang, Faisal Altaf, Torsten Wik
2024 European Control Conference, ECC 2024, p. 212-217
Paper in proceeding
2024

Synthetic dataset of LG M50 batteries with different degradation pathways

Huang Zhang, Faisal Altaf, Torsten Wik
Data in Brief. Vol. 57
Journal article
2023

Comparative Analysis of Battery Cycle Life Early Prediction Using Machine Learning Pipeline

Huang Zhang, Faisal Altaf, Torsten Wik et al
IFAC-PapersOnLine. Vol. 56 (2), p. 3757-3763
Paper in proceeding
2023

Interpretable Battery Cycle Life Range Prediction Using Early Cell Degradation Data

Huang Zhang, Yang Su, Faisal Altaf et al
IEEE Transactions on Transportation Electrification. Vol. 9 (2), p. 2669-2682
Journal article
2022

Performances of Machine Learning Algorithms in Predicting the Productivity of Conservation Agriculture at a Global Scale

Yang Su, Huang Zhang, Benoit Gabrielle et al
Frontiers in Environmental Science. Vol. 10
Journal article

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