Dynamic Modeling of Li-Ion Batteries Using an Equivalent Electrical Circuit

2011 ◽  
Vol 158 (3) ◽  
pp. A326 ◽  
Author(s):  
T. K. Dong ◽  
A. Kirchev ◽  
F. Mattera ◽  
J. Kowal ◽  
Y. Bultel
Keyword(s):  
Dynamic Modeling ◽  
Electrical Circuit ◽  
Equivalent Electrical Circuit ◽  
Li Ion Batteries ◽  
Li Ion

scholarly journals Импедансная спектроскопия пористых кремниевых и кремний-углеродных анодов, полученных спеканием

2020 ◽  
Vol 54 (3) ◽  
pp. 310
Author(s):  
Д.А. Ложкина ◽  
А.М. Румянцев ◽  
Е.В. Астрова
Keyword(s):  
Diffusion Coefficient ◽  
Solid Phase ◽  
Effective Diffusion ◽  
Double Electric Layer ◽  
Electrochemical Process ◽  
Electrical Circuit ◽  
Li Ion Batteries ◽  
Li Ion ◽  
And Diffusion ◽  
Lithium Incorporation

Dry sintered macroporous Si electrodes for Li-ion batteries are first studied using spectral impedance measurements (EIS). The obtained EIS spectra in the lithiated and delithated state are modeled by an equivalent electrical circuit, the parameters of which make it possible to determine the main stages of the electrochemical process of lithium incorporation / extraction caused by the surface layer of solid-state electrolyte (SEI), a double electric layer, and diffusion in the solid phase of the electrode material. It was shown that the effective diffusion coefficient of Li in Si increases with rising degree of lithiation from D = 6.5·10 ^ (-12) cm2/s to D = 2.6·10^ (-10) cm2/s. The effect of carbonization by sucrose pyrolysis was studied, which led to a decrease in impedance and an increase in the diffusion coefficient of lithium to D = 2.2·10^(-10) - 1.7·10^(-9) cm2/s.

An Ensemble Bias-Correction Method With Adaptive Weights for Dynamic Modeling of Lithium-Ion Batteries

2017 ◽  
Author(s):  
Yifei Li ◽  
Mohammad Kazem Sadoughi ◽  
Zhixiong Li ◽  
Chao Hu
Keyword(s):  
Dynamic Modeling ◽  
Dynamic Characteristics ◽  
Bias Correction ◽  
Equivalent Circuit Model ◽  
Lithium Ion ◽  
Correction Method ◽  
Li Ion Batteries ◽  
Li Ion Battery ◽  
Adaptive Weights ◽  
Li Ion

Accurate modeling of the electrical behavior of a lithiumion (Li-ion) battery can provide accurate dynamic characteristics of the battery during charging/discharging and relaxation phases, which is essential to accurate online estimation of the battery state of charge (SoC). This paper proposes an ensemble bias-correction (BC) method with adaptive weights to improve the accuracy of an equivalent circuit model (ECM) in dynamic modeling of Li-ion batteries. The contribution of this paper is twofold: (i) the development of a novel ensemble method based on BC learning to model the dynamic characteristics of Li-ion batteries; and (ii) the creation of an adaptive-weighting scheme to learn online the weights of offline member BC models for building an online ensemble BC model. Repeated pulsing tests with single and multiple C-rates were conducted on seven Li-ion battery cells to evaluate the effectiveness of the proposed ensemble BC method. The analysis results with the use of an ECM demonstrate that the proposed method can reduce, on average, the voltage modeling error of the ECM by at least 50%.

Electrochemical and Safety Performances of Polyimide Nano fiber-based Nonwoven Separators for Li-ion Batteries

2015 ◽  
Vol 6 (1) ◽  
pp. 26-33 ◽  
Author(s):  
Yeon-Joo Kim ◽  
Sang-Min Lee ◽  
Seok Hong Kim ◽  
Hyun-Soo Kim
Keyword(s):  
Li Ion Batteries ◽  
Nano Fiber ◽  
Li Ion

Lithiation Mechanisms in High Entropy Oxides as Anode Materials for Li-Ion Batteries

2020 ◽  
Author(s):  
Paolo Ghigna ◽  
Lorenzo Airoldi ◽  
Martina Fracchia ◽  
Umberto Anselmi-Tamburini ◽  
Paola D'angelo ◽  
...  
Keyword(s):  
Anode Materials ◽  
Li Ion Batteries ◽  
High Entropy ◽  
Li Ion
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