State of charge estimation of li-ion batteries based on the noise-adaptive interacting multiple model
This paper presents a type of noise-adaptive (NA) interacting multiple model (IMM) algorithm combined with an unscented Kalman filter (UKF) in order to address problems in poor filtering accuracy and filtering divergence of IMM caused by the statistical properties of noise. These properties further...
Enregistré dans:
Auteurs principaux: | Ce Huang, Xiaoyang Yu, Yongchao Wang, Yongqin Zhou, Ran Li |
---|---|
Format: | article |
Langue: | EN |
Publié: |
Elsevier
2021
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/c452c9c3d1bc41ccbd19bdf5ea74b950 |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Estimation of Lithium-Ion Battery SOC Model Based on AGA-FOUKF Algorithm
par: Chao Fang, et autres
Publié: (2021) -
An Integrated Deep Ensemble-Unscented Kalman Filter for Sideslip Angle Estimation With Sensor Filtering Network
par: Dongchan Kim, et autres
Publié: (2021) -
A stochastic metapopulation state-space approach to modeling and estimating COVID-19 spread
par: Yukun Tan, et autres
Publié: (2021) -
Multi-Rate Data Fusion for State and Parameter Estimation in (Bio-)Chemical Process Engineering
par: Robert Dürr, et autres
Publié: (2021) -
Surrounding Objects Detection and Tracking for Autonomous Driving Using LiDAR and Radar Fusion
par: Ze Liu, et autres
Publié: (2021)