Development of improved Li-ion battery model incorporating thermal and rate factor effects

2009 ◽  
Author(s):  
S. Bhide ◽  
Taehyun Shim
Keyword(s):  
Li Ion Battery ◽  
Battery Model ◽  
Li Ion

A GPU-accelerated parallel Jaya algorithm for efficiently estimating Li-ion battery model parameters

2018 ◽  
Vol 65 ◽  
pp. 12-20 ◽  
Author(s):  
Long Wang ◽  
Zijun Zhang ◽  
Chao Huang ◽  
Kwok Leung Tsui
Keyword(s):  
Model Parameters ◽  
Jaya Algorithm ◽  
Li Ion Battery ◽  
Battery Model ◽  
Li Ion

scholarly journals An advanced all-solid-state Li-ion battery model

2020 ◽  
Vol 330 ◽  
pp. 135147 ◽  
Author(s):  
L.H.J. Raijmakers ◽  
D.L. Danilov ◽  
R.-A. Eichel ◽  
P.H.L. Notten
Keyword(s):  
Solid State ◽  
Li Ion Battery ◽  
Battery Model ◽  
Li Ion

A Separated-Frequency Parameters Identification Method of Li-Ion Battery Model for Electric Vehicles

2014 ◽  
Vol 672-674 ◽  
pp. 727-730 ◽  
Author(s):  
Da Zhong Mu ◽  
Zhi Hong Dong ◽  
Ming Fei Wang
Keyword(s):  
Electric Vehicles ◽  
Main Idea ◽  
Open Circuit ◽  
Current Data ◽  
Model Parameters ◽  
Wavelet Domain ◽  
Li Ion Battery ◽  
Battery Model ◽  
Identification Method ◽  
Li Ion

This paper proposed a separated-frequency identification method of Li-ion battery model for Electric Vehicles (EVs). The main idea is to decompose the measured terminal voltage and current data in wavelet domain, and then the weighting least squares (LS) algorithm is used to extract the model parameters. Since the signal energy of open circuit voltage (OCV) mainly distributes in the low frequency band, the identifiable wavelet-domain battery model can be approximately obtained by neglecting the high frequency wavelet decomposition coefficients. Furthermore, based on the Akaike’s information criterion, we study the optimum decomposition order of the wavelet-domain battery model.

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