Lithium-ion battery capacity and remaining useful life prediction using board learning system and long short-term memory neural network
S Zhao, C Zhang, Y Wang - Journal of Energy Storage, 2022 - Elsevier
In order for lithium-ion batteries to function reliably and safely, accurate capacity and
remaining useful life (RUL) predictions are essential, but challenging. Some current deep …
remaining useful life (RUL) predictions are essential, but challenging. Some current deep …
State-of-Health Prediction of Lithium-Ion Batteries Based on Diffusion Model with Transfer Learning
C Luo, Z Zhang, S Zhu, Y Li - Energies, 2023 - mdpi.com
An accurate state-of-health (SOH) prediction of lithium-ion batteries (LIBs) is crucial to their
safe and reliable. Although recently the data-driven methods have drawn great attention …
safe and reliable. Although recently the data-driven methods have drawn great attention …
Prediction of State of Charge for Lead-Acid Battery Based on LSTM-Attention and LightGBM
Y Shen, Y Ge - Journal of Computing and …, 2024 - asmedigitalcollection.asme.org
Accurately estimating the state of charge (SOC) of batteries is crucial for the objective of
extending battery life and enhancing power supply reliability. Currently, machine learning …
extending battery life and enhancing power supply reliability. Currently, machine learning …
Genetic algorithm based production knowledge base for mechanical fault detection model
Y Shen - Journal of Computational Methods in Sciences and …, 2023 - content.iospress.com
Mechanical fault detection has an important influence on production schedule and
efficiency. With the development of intelligent technology, more and more intelligent …
efficiency. With the development of intelligent technology, more and more intelligent …
Automated Machine Learning for Remaining Useful Life Predictions
Being able to predict the remaining useful life (RUL) of an engineering system is an
important task in prognostics and health management. Recently, data-driven approaches to …
important task in prognostics and health management. Recently, data-driven approaches to …
Evaluating RNN and Its Improved Models for Lithium Battery SoH and BRL Prediction
Drones require high-performance lithium batteries, and conventional battery replacement
standards are not applicable in the context of drones. To address these issues, this paper …
standards are not applicable in the context of drones. To address these issues, this paper …
Prediction of Battery Package Temperature Rise with LSTM (Long Short-Term Memory)
CJ Hwa - Proceedings of the Korean Society of Computer …, 2024 - koreascience.kr
본 논문에서는 전기 자동차 배터리 팩 설계에서 성능 예측을 위해 전산유체해석 및 Long Short-
Term Memory (LSTM) 를 활용한다. 두 계산 모두의 예측이 상당한 유사성을 나타내며 …
Term Memory (LSTM) 를 활용한다. 두 계산 모두의 예측이 상당한 유사성을 나타내며 …
Leakage Detection of Water Supply Network Based on Neural Network
XQ Wu, L Ge - International conference on Variability of the Sun and …, 2022 - Springer
Leakage of water supply network refers to the phenomenon that some unused water flows
out of the pipe when the water output from the water supply plant passes through the water …
out of the pipe when the water output from the water supply plant passes through the water …
[引用][C] LSTM (Long Short-Term Memory) 을활용한Battery Package 온도상승예측
조종화， 민연아 - 한국컴퓨터정보학회학술발표논문집, 2024 - dbpia.co.kr
● 요 약● 본 논문에서는 전기 자동차 배터리 팩 설계에서 성능 예측을 위해 전산유체해석 및
Long Short-Term Memory (LSTM) 를 활용한다. 두 계산 모두의 예측이 상당한 유사성을 …
Long Short-Term Memory (LSTM) 를 활용한다. 두 계산 모두의 예측이 상당한 유사성을 …
[引用][C] Machine-Learning 을통한Battery Package 온도상승예측
조종화， 민연아 - 한국컴퓨터정보학회학술발표논문집, 2023 - dbpia.co.kr
● 요 약● 배터리 기술 고도화 및 기술표준 강화에 따라 완성차 제조사와 배터리 업계간 활발한
협업이이어질 전망이다. 또한 기존 배터리 제조사들이 활발한 증설 및 밸류 체인 확장을 통한 …
협업이이어질 전망이다. 또한 기존 배터리 제조사들이 활발한 증설 및 밸류 체인 확장을 통한 …