398 citations · 445 across the 4 of their papers we have counts for
5 papers · 1 filter
Bayesian hierarchical modelling for battery lifetime early prediction
Zihao Zhou, David A. Howey
Accurate prediction of battery health is essential for real-world system management and lab-based experiment design. However, building a life-prediction model from different cyclin…
Piecewise-linear modelling with feature selection for Li-ion battery end of life prognosis
Samuel Greenbank, David A. Howey
The complex nature of lithium-ion battery degradation has led to many machine learning based approaches to health forecasting being proposed in literature. However, machine learnin…
Automated feature extraction and selection for data-driven models of rapid battery capacity fade and end of life
Samuel Greenbank, David A. Howey
Lithium-ion cells may experience rapid degradation in later life, especially with more extreme usage protocols. The onset of rapid degradation is called the `knee point', and forec…
Galvanalyser: A Battery Test Database
Adam Lewis-Douglas, Luke Pitt, David A. Howey
Performance and lifetime testing of batteries requires considerable effort and expensive specialist equipment. A wide range of potentiostats and battery testers are available on th…
Unlocking Extra Value from Grid Batteries Using Advanced Models
Jorn M. Reniers, Grietus Mulder, David A. Howey
Lithium-ion batteries are increasingly being deployed in liberalised electricity systems, where their use is driven by economic optimisation in a specific market context. However,…