Results 41 to 50 of about 9,187,359 (195)

Performance–Complexity Trade‐Offs in Battery Lifetime Prediction with Task‐Aware Transformers

Advanced Science, EarlyView.
FAST‐BatPro integrates convolutional feature extraction, flash Attention, and sparse attention for efficient battery lifetime prediction. Using limited early‐cycle data across multiple chemistries and operating conditions, it achieves robust accuracy while reducing inference latency, computational cost, and energy consumption.
Jingyuan Zhao, Misheng Cai, Zhenghong Wang, Yan Wang, Yuqi Li, Bo Dong, Hewu Wang, Andrew F. Burke, Simona Onori, Stephen J. Harris   +9 more
wiley   +1 more source

Metrics for Offline Evaluation of Prognostic Performance [PDF]

International Journal of Prognostics and Health Management, 2010
Prognostic performance evaluation has gained significant attention in the past few years.Currently, prognostics concepts lack standard definitions and suffer from ambiguous and inconsistent interpretations.
Sankalita Saha, Bhaskar Saha, Abhinav Saxena, Kai Goebel, Jose Celaya   +4 more
doaj  

Remaining Useful Life (RUL) Estimation of Lead Acid Battery using Bayesian Approach

Journal of Electrical Engineering and Automation, 2020
This article deals with Remaining Useful Life (RUL) estimation of Lead Acid Battery using a probabilistic approach which is Bayesian inference of Linear Regression. RUL estimation of lead acid battery plays a very crucial role as it can prevent the catastrophic failure for the system in which it is used to serve as a power supply mainly in automobiles.
Bhalaji N., Rimi Chowdhury
openaire   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

A Probabilistic Fractional Order Physics Informed Mamba Kolmogorov‐Arnold Network for State‐of‐Charge Estimation in Grid‐Connected Battery Energy Storage Systems

Energy Science &Engineering, EarlyView.
This paper introduces the probabilistic fractional‐order Mam‐KAN (PFO‐Mam‐KAN) controller, a physics‐informed gray‐box framework for real‐time battery state‐of‐charge estimation. By unifying efficient Mamba encoders with uncertainty‐aware fractional physics, it achieves superior 0.31% RMSE accuracy and robust grid‐support operation under dynamic ...
Arun Kumar Rawat, Subhash Chandra, Vinay Kumar Deolia   +2 more
wiley   +1 more source

Lithium-ion battery remaining useful life prediction [PDF]

, 2021
Lithium-Ion Battery Remaining Useful Life Prediction work consists of an initial approach to battery life prediction using Severson dataset and data-driven LSTM-based RUL predictive methods. Although the memory is written in English, the presentation
Larrarte Lizarralde, Beñat
core   +2 more sources

Innovative methods predicting the remaining useful life of transformer using limited data

Array
Electricity is essential in today's life, with electricity consumption expected to increase by up to 80% by 2024, making transformers essential. In developing countries, power transformers in power plants are often not regularly monitored, making the ...
Nur Avika Febriani, Ika Noer Syamsiana, Rachmat Sutjipto, Arwin Datumaya Wahyudi Sumari, Chandra Wiharya, Rhezal Agung Ananto, Rahma Nur Amalia   +6 more
doaj   +1 more source

Review on State Estimation and Remaining Useful Life Prediction Methods for Lithium-ion Battery

发电技术, 2023
Accurate estimation of state of charge (SOC), battery state of health (SOH) and prediction of battery remaining useful life (RUL) of lithium-ion battery are important contents of battery management. It is of great significance to prolong battery life and
ZHAO Jiahui, TIAN Liting, CHENG Lin
doaj   +1 more source

Weibull Variational Autoencoder for Remaining Useful Life Prediction

Quality and Reliability Engineering International, EarlyView.
ABSTRACT Remaining useful life (RUL) prediction is a critical technology for preventing unexpected failures and reducing maintenance costs in modern industrial systems. However, traditional model‐based approaches are limited by the need for explicit mathematical modeling of degradation mechanisms, while data‐driven methods often require large‐scale ...
JunWoo Yu, Yoojin Jang, Kwanghui Shin, Jinsoo Jeong, Yong Soo Kim   +4 more
wiley   +1 more source

Predictive Analysis of Remaining Useful Life (RUL) of Batteries: Review

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
The increasing reliance on batteries for electric vehicles, renewable energy systems, and consumer electronics has necessitated advancements in predictive models for their Remaining Useful Life (RUL). This paper reviews current methodologies for RUL prediction, focusing on machine learning techniques, data-driven approaches, and hybrid models that ...
Sakshi Belkhode, Dr. P.M. Chaudhari, Anjali Meshram, Krutika Nikhare, Shrushti Rangari, Sakshi Chimurkar   +5 more
openaire   +1 more source