Predictive pretrained transformer (PPT) for real-time battery health diagnostics
Modeling and forecasting the evolution of battery systems involve complex interactions
across physical, chemical, and electrochemical processes, influenced by diverse usage …
across physical, chemical, and electrochemical processes, influenced by diverse usage …
[HTML][HTML] Transformer-based deep learning models for state of charge and state of health estimation of li-ion batteries: A survey study
The global transportation system's need for electrification is driving research efforts to
overcome the drawbacks of battery electric vehicles (BEVs). The accurate and reliable …
overcome the drawbacks of battery electric vehicles (BEVs). The accurate and reliable …
[HTML][HTML] Advancing state of health estimation for electric vehicles: Transformer-based approach leveraging real-world data
K Nakano, S Vögler, K Tanaka - Advances in Applied Energy, 2024 - Elsevier
The widespread adoption of electric vehicles (EVs) underscores the urgent need for
innovative approaches to estimate their lithium-ion batteries' state of health (SOH), which is …
innovative approaches to estimate their lithium-ion batteries' state of health (SOH), which is …
State-of-Health Estimation for Sustainable Electric Vehicle Batteries Using Temporal-Enhanced Self-Attention Graph Neural Networks
Electric vehicles (EVs) have emerged as an environmentally friendly alternative to
conventional fuel vehicles. Lithium-ion batteries are the major energy source for EVs, but …
conventional fuel vehicles. Lithium-ion batteries are the major energy source for EVs, but …
Transformer-Based Transfer Learning for Battery State-of-Health Estimation
The accurate prediction of batteries' state of health has been an important research topic in
recent years given the surge of electric vehicle production. Dynamically assessing the …
recent years given the surge of electric vehicle production. Dynamically assessing the …