Reduced order model for a lithium ion cell with uniform reaction rate approximation

Kumar, Vinay

doi:10.1016/j.jpowsour.2012.09.013

Cited by 45 publications

(20 citation statements)

References 9 publications

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“…[ 100,141 ] Proper approximations can reduce the model complexity significantly. Assuming that the charge‐transfer reactions occur uniformly across the porous electrodes, [ 138,296–298 ] this has resulted in a so‐called average model (AM). Based on this assumption, the electric potential gradients inside the electrodes and electrolyte can be easily and fast simulated.…”

Section: Applications To Libsmentioning

confidence: 99%

Porous Electrode Modeling and its Applications to Li‐Ion Batteries

Chen

Danilov

Eichel

et al. 2022

Advanced Energy Materials

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Figure 12. a-c) Schematic representation of the electrode potential at electrode/electrolyte interfaces. [145] Red areas indicate the electrode region and blue the electrolyte region. a) The Butler-Volmer approach does not consider charges at the interface. b) More detailed representation of the electrode/ electrolyte interface, considering specifically adsorbed species (green area) and screening counter charges at the surface of the electrode (dark red) and in the electrolyte (dark blue). c) Reduced electrode/electrolyte interface considering the surface charge in the electrode and screening charge in the electrolyte. d) Typical examples of impedance spectra for a porous electrode with insertion-type reactions. [151] Impedance simulations of porous graphite electrodes in contact with electrolyte with e) various particle sizes and f) electrode porosities. [152] a-c) Reproduced with permission. [145]

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Section: Applications To Libsmentioning

confidence: 99%

Porous Electrode Modeling and its Applications to Li‐Ion Batteries

Chen

Danilov

Eichel

et al. 2022

Advanced Energy Materials

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“…In order to describe the electrolyte diffusion process with an acceptable computational efficiency and accuracy, the volume-averaged forms of the equations for electrolyte diffusion are obtained as follows [31]:…”

Section: Electrolyte Diffusion Processmentioning

confidence: 99%

“…It is noted that the detailed expressions of c 2ip (t), c 2in (t), q 2ip (t), q 2in (t), can be found in [31].…”

Section: Electrolyte Diffusion Processmentioning

confidence: 99%

Online SOC Estimation Based on Simplified Electrochemical Model for Lithium-Ion Batteries Considering Current Bias

Pang

et al. 2021

Energies

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State of Charge (SOC) is essential for a smart Battery Management System (BMS). Traditional SOC estimation methods of lithium-ion batteries are usually conducted using battery equivalent circuit models (ECMs) and the impact of current sensor bias on SOC estimation is rarely considered. For this reason, this paper proposes an online SOC estimation based on a simplified electrochemical model (EM) for lithium-ion batteries considering sensor bias. In EM-based SOC estimation structure, the errors from the current sensor bias are addressed by proportional–integral observer. Then, the accuracy of the proposed EM-based SOC estimation is validated under different operating conditions. The results indicate that the proposed method has good performance and high accuracy in SOC estimation for lithium-ion batteries, which facilitates the on-board application in advanced BMS.

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“…Nevertheless, if all or most relevant degradation mechanisms are combined in a representative manner, they are computationally very expensive. Thus, some reduced order models are developed to reduce the computational time, but it still suffers from the inability of prediction with thick electrodes or high C-rate operating conditions [22,23]. Consequently, a protocol that can accurately determinate the degradation mechanism and quantify the losses in an efficient and simple manner is highly desired.…”

Section: Introductionmentioning

confidence: 99%

An efficient and independent modeling method for lithium-ion battery degradation

Shan

Zhang

Hou

et al. 2021

Ionics

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Degradation in the lithium-ion battery performance is an inevitable phenomenon during the service life. Therefore, the state of health (SOH) of the battery is an important indicator of the battery management system (BMS) in electric vehicles (EVs). The existing estimation techniques to predict the losses due to degradation and SOH of the battery are limited by the situation of being incomplete or computationally expensive. This work develops an efficient and independent modeling method for SOH estimation and degradation analysis, in which a simple parameter fitting can be used to represent the discharge profile that can be represented with an accuracy of > 99.9%, using simple parameter fitting. The homogeneity of the active lithium distribution, the discharge capacity and the evolution of internal resistance have been well demonstrated by the model parameters. In addition, through simple calculation, the loss of active materials and the state of electrode balance are accurately represented by the derivate parameters.

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Reduced order model for a lithium ion cell with uniform reaction rate approximation

Cited by 45 publications

References 9 publications

Porous Electrode Modeling and its Applications to Li‐Ion Batteries

Porous Electrode Modeling and its Applications to Li‐Ion Batteries

Online SOC Estimation Based on Simplified Electrochemical Model for Lithium-Ion Batteries Considering Current Bias

An efficient and independent modeling method for lithium-ion battery degradation

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