Cargando…
Remaining Useful Life Prediction for Lithium-Ion Batteries Based on Gaussian Processes Mixture
The remaining useful life (RUL) prediction of Lithium-ion batteries is closely related to the capacity degeneration trajectories. Due to the self-charging and the capacity regeneration, the trajectories have the property of multimodality. Traditional prediction models such as the support vector mach...
Autores principales: | Li, Lingling, Wang, Pengchong, Chao, Kuei-Hsiang, Zhou, Yatong, Xie, Yang |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5024987/ https://www.ncbi.nlm.nih.gov/pubmed/27632176 http://dx.doi.org/10.1371/journal.pone.0163004 |
Ejemplares similares
-
A Novel Remaining
Useful Life Prediction Method for
Capacity Diving Lithium-Ion Batteries
por: Gao, Kaidi, et al.
Publicado: (2022) -
Remaining Useful Life Prediction of Lithium-Ion Batteries Using Neural Networks with Adaptive Bayesian Learning
por: Pugalenthi, Karkulali, et al.
Publicado: (2022) -
Early prediction of remaining useful life for lithium-ion batteries based on CEEMDAN-transformer-DNN hybrid model
por: Cai, Yuxiang, et al.
Publicado: (2023) -
A Hybrid Data-Driven Approach for Multistep Ahead Prediction of State of Health and Remaining Useful Life of Lithium-Ion Batteries
por: Ali, Muhammad Umair, et al.
Publicado: (2022) -
XGBoost-Based Remaining Useful Life Estimation Model with Extended Kalman Particle Filter for Lithium-Ion Batteries
por: Jafari, Sadiqa, et al.
Publicado: (2022)