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Found 5 papers, 2 papers with code
Jointly Learning Consistent Causal Abstractions Over Multiple Interventional Distributions
An abstraction can be used to relate two structural causal models representing the same system at different levels of resolution.
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
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) coupled with a sliding-window.
Feature Analyses and Modelling of Lithium-ion Batteries Manufacturing based on Random Forest Classification
Lithium-ion battery manufacturing is a highly complicated process with strongly coupled feature interdependencies, a feasible solution that can analyse feature variables within manufacturing chain and achieve reliable classification is thus urgently needed.
Systematic derivation and validation of a reduced thermal-electrochemical model for lithium-ion batteries using asymptotic methods
These models are usually posed in an ad hoc manner, leading to inconsistencies with the DFN model and to multiple formulations of the same model, with the Single Particle Model (SPM) being a very good example of the latter.
Chemical Physics Computational Physics
Derivation of an Effective Thermal Electrochemical Model for Porous Electrode Batteries using Asymptotic Homogenisation
Thermal electrochemical models for porous electrode batteries (such as lithium ion batteries) are widely used.
Chemical Physics Applied Physics Computational Physics
