State-of-Health Forecasting for Battery Cells using Bayesian Inference and LSTM-based Change Point Detection
With the global shift towards an ecologically conscious environment and the increasing
prominence of electric vehicles, the focus on Lithium-ion (Li-ion) batteries continues to grow …
prominence of electric vehicles, the focus on Lithium-ion (Li-ion) batteries continues to grow …
MOFSAut: Multi-task One-shot Feature Selection Autoencoder for Prognostics
W Hassanieh, A Chehade - IISE Annual Conference …, 2024 - search.proquest.com
Prognostic aims at predicting the lifetime at which a component or a system will be unable to
perform a desired function. Datadriven models have been shown in recent literature to be …
perform a desired function. Datadriven models have been shown in recent literature to be …
Battery state of charge prediction based on adaptive knowledge transfer mechanism and temporal deep learning model
State of charge (SOC) is an important prognostic parameter for assessing the performance
level and reliability of battery-powered systems. Most of the existing deep learning predictive …
level and reliability of battery-powered systems. Most of the existing deep learning predictive …
A Bayesian Predictive Inference with Parametric Regression Model for Battery SOH and RUL Predictions
Effective prognostic and health management of lithium-ion battery-powered systems relies
heavily on accurate prediction of battery internal state parameters, including state of health …
heavily on accurate prediction of battery internal state parameters, including state of health …