activity
20192022
most citedFeature Analyses and Modelling of Lithium-ion Batteries Manufacturing based on Random Forest Classification

18 citations · 22 across the 2 of their papers we have counts for

collaborators

4 papers

eess.SY20224 cited

State of Health Estimation of Lithium-Ion Batteries in Vehicle-to-Grid Applications Using Recurrent Neural Networks for Learning the Impact of Degradation Stress Factors

Kotub Uddin, James Schofield, W. Dhammika Widanage

This work presents an effective state of health indicator to indicate lithium-ion battery degradation based on a long short-term memory (LSTM) recurrent neural network (RNN) couple…

cs.LG202118 cited

Feature Analyses and Modelling of Lithium-ion Batteries Manufacturing based on Random Forest Classification

Kailong Liu, Xiaosong Hu, Huiyu Zhou +3

Lithium-ion battery manufacturing is a highly complicated process with strongly coupled feature interdependencies, a feasible solution that can analyse feature variables within man…

physics.chem-ph2020

Systematic derivation and validation of a reduced thermal-electrochemical model for lithium-ion batteries using asymptotic methods

Ferran Brosa Planella, Muhammad Sheikh, W. Dhammika Widanage

The widely used Doyler-Fuller-Newman (DFN) model for lithium-ion batteries is too computationally expensive for certain applications, which has motivated the appearance of a pletho…

physics.chem-ph2019

Derivation of an Effective Thermal Electrochemical Model for Porous Electrode Batteries using Asymptotic Homogenisation

Matthew J. Hunt, Ferran Brosa Planella, Florian Theil +1

Thermal electrochemical models for porous electrode batteries (such as lithium ion batteries) are widely used. Due to the multiple scales involved, solving the model accounting for…