Model migration neural network for predicting battery aging trajectories
An accurate prediction of batteries' future degradation is a key solution to relief the users'
anxiety on battery lifespan and electric vehicles' driving range. Technical challenges arise …
anxiety on battery lifespan and electric vehicles' driving range. Technical challenges arise …
Battery cycle life study through relaxation and forecasting the lifetime via machine learning
Battery lifetime modeling and prediction of precise capacity degradation for real-life
applications are critical to understanding the complex and non-linear battery behavior …
applications are critical to understanding the complex and non-linear battery behavior …
Battery aging assessment for real-world electric buses based on incremental capacity analysis and radial basis function neural network
Accurate battery aging prediction is essential for ensuring efficient, reliable, and safe
operation of battery systems in electric vehicle application. This article presents a novel …
operation of battery systems in electric vehicle application. This article presents a novel …
Predictive battery health management with transfer learning and online model correction
Significant progress has been made in transportation electrification in recent years. As the
main energy storage device, lithium-ion batteries are one of the key components that need …
main energy storage device, lithium-ion batteries are one of the key components that need …
[HTML][HTML] A machine learning-based framework for online prediction of battery ageing trajectory and lifetime using histogram data
Accurately predicting batteries' ageing trajectory and remaining useful life is not only
required to ensure safe and reliable operation of electric vehicles (EVs) but is also the …
required to ensure safe and reliable operation of electric vehicles (EVs) but is also the …
A regression learner-based approach for battery cycling ageing prediction―advances in energy management strategy and techno-economic analysis
Y Zhou - Energy, 2022 - Elsevier
Renewable energy planning, electrochemical battery storages and advanced energy
management strategies are flexible solutions for transformation towards smart grids …
management strategies are flexible solutions for transformation towards smart grids …
A novel hybrid physics-based and data-driven approach for degradation trajectory prediction in Li-ion batteries
Lithium-ion batteries have been widely used in electric vehicles. To ensure safety and
reliability, accurate prediction of the battery's future degradation trajectory is critical …
reliability, accurate prediction of the battery's future degradation trajectory is critical …
Aging trajectory prediction for lithium-ion batteries via model migration and Bayesian Monte Carlo method
This paper develops a new prediction method for the aging trajectory of lithium-ion batteries
with significantly reduced experimental tests. This method is driven by data collected from …
with significantly reduced experimental tests. This method is driven by data collected from …
Battery degradation prediction against uncertain future conditions with recurrent neural network enabled deep learning
Accurate degradation trajectory and future life are the key information of a new generation of
intelligent battery and electrochemical energy storage systems. It is very challenging to …
intelligent battery and electrochemical energy storage systems. It is very challenging to …
AI-driven battery ageing prediction with distributed renewable community and E-mobility energy sharing
Y Zhou - Renewable Energy, 2024 - Elsevier
Electrochemical battery storages play multiple functions in district energy systems, like peak
shaving, load coverage, renewable penetration, load coverage, frequency regulation and …
shaving, load coverage, renewable penetration, load coverage, frequency regulation and …