An electrochemical model for lithium-ion batteries is generally based on the porous electrode theory and the concentrated solution theory. An electrochemical model describes the behaviors of the battery from the electrochemical point of view by quantizing the internal microscopic processes (e.g., electrochemical reaction kinetics, mass, and heat transfer).
Maofei, T.: SOC estimation of lithium battery based online parameter identification and AEKF. Energy Storage Sci. Technol. 8(04), 745–750 (2019) Google Scholar Yang, Y.: SOC estimation of lithium batteries based on improved recursive least squares method. Control Eng. China 28(09), 1759–1764 (2021)
DOI: 10.1016/j.est.2022.106462 Corpus ID: 255077883; An improved parameter identification method considering multi-timescale characteristics of lithium-ion batteries @article{Yang2023AnIP, title={An improved parameter identification method considering multi-timescale characteristics of lithium-ion batteries}, author={Zhao Yang and Xuemei Wang}, …
Parameterization of battery dynamics based on terminal operating data is a main concern in engineering applications of batteries. The key technology is designing an adequate test procedure and a data processing procedure to excite different inner dynamics and then estimate the parameters of a corresponding equivalent circuit model (ECM). This paper …
Fractional-order model (FOM) is recognized as a preferable model of Lithium-ion Battery because of the inherent mechanism and the simplicity of the parameters. However the identification of its parameters still difficult if just with a simple engineering process. This paper proposes a parameter identification method for the FOM, which combines a time-domain …
The results, which are based on simulations and actual Li0.8Co0.1Mn0.1O2 lithium-ion batteries under multiple typical operating profiles and comparisons with other parameter identification methods ...
Accurate estimation of the lithium battery state plays an important role in battery management systems. The key is to obtain precise parameters of the battery model. Multi-innovation stochastic gradient (MISG) algorithm can be applied to identify model parameters, but suffers the problem of low convergence accuracy. To address this issue, a weighted MISG method based on kernel …
To eliminate the impact of inaccurate initial parameter value on the parameter identification results of lithium-ion battery (LIB) model, a method for parameter identification …
DOI: 10.1016/J.APENERGY.2018.03.053 Corpus ID: 115279086; An electrochemical model based degradation state identification method of Lithium-ion battery for all-climate electric vehicles application
A robust identification method for inherent parameters of lithium battery considering thermal distribution and state of charge. ... Model parameter identification for lithium-ion batteries using adaptive multi-context cooperatively co-evolutionary parallel differential evolution algorithm. Journal of Energy Storage, Volume 58, 2023, Article ...
Parameter identification of lithium-ion battery pseudo-2-dimensional models using genetic algorithm and neural network cooperative optimization. J. Energy Storage, 45 (2022), ... A hybrid signal-based fault diagnosis method for lithium-ion batteries in electric vehicles. IEEe Access., 9 (2021), pp. 19175-19186.
Electrification of vehicles is an effective way to decrease greenhouse gas emissions. Lithium-ion batteries are widely used as energy storage devices in electric vehicles and hybrid electric vehicles due to their high energy and power density, long cycle life, and lack of memory effect [1].
Accurate estimation of the state of charge (SOC) for lithium-ion batteries (LIBs) has now become a crucial work in developing a battery management system. In this paper, the characteristic parameters of LIBs under wide temperature range are collected to examine the influence of parameter identification precision and temperature on the SOC estimation …
Semantic Scholar extracted view of "A robust identification method for inherent parameters of lithium battery considering thermal distribution and state of charge" by Bowen Xu et al. Skip to search form Skip to main content Skip to account menu. Semantic Scholar''s Logo. Search 221,892,251 papers from all fields of science ...
A novel method for lithium-ion battery online parameter identification based on variable forgetting factor recursive least squares. Energies, 11 (2018), ... Model parameter identification for lithium batteries using the coevolutionary particle swarm optimization method. IEEE Trans. Ind. Electron., 64 (2017), ...
ABSTRACT The accuracy of lithium battery model parameters is the key to lithium battery state estimation. The offline parameter identification method for lithium batteries requires the nonlinear fitting of the voltage rebound curve of the hybrid pulse discharge experiment. The genetic algorithm has a strong global search ability, but it is easy to fall into …
Lithium-ion battery equivalent model plays an important role in studying charging, discharging, and capacity of lithium-ion battery. Reasonable battery model can fully characterize its external features, and the model parameters can reflect its performance state through system identification method.
Experimental results prove that the proposed fault identification approach based on mutual information is reliable to identify the MSC cell and the low-capacity cell. During the usage of electric vehicles, the battery decays and the cell variations expand in the battery pack. In the discharge process, both the low-capacity cell and the micro-short-circuit (MSC) cell have …
In this paper, the second-order RC equivalent circuit model of lithium-ion battery is studied, and the online identification of model parameters by multi-innovation least …
However, most of the methods mentioned above have a significant drawback in that they rely on numerous parameters provided by the designer. In contrast, a method based on recursive least squares with a sliding window difference forgetting factor was proposed in (Shi et al., 2021) to identify lithium-ion battery parameters.This approach incorporates an adaptive …
In this work, a multi-domain parameter identification method for a FOM of lithium-ion batteries is proposed. Based on FI and TI, the MI method constructs multi-domain objective function with the terminal voltage and EIS as the optimization objectives, and the GA-PSO algorithm is used to optimize the multi-domain objective function.
order RC model of lithium-ion batteries can be calculated by (5) and (6). 3 Parameter identification algorithm for a lithium-ion battery The parameter identification algorithm includes the following variables, which are defined as follows: k is a sampling instant, which also represents the current number of the estimated
The increasing adoption of batteries in a variety of applications has highlighted the necessity of accurate parameter identification and effective modeling, especially for lithium-ion batteries, which are preferred due to their high power and energy densities. This paper proposes a comprehensive framework using the Levenberg–Marquardt algorithm (LMA) for …
A noise‐immune model identification method for lithium‐ion battery using two‐swarm cooperative particle swarm optimization algorithm based on adaptive dynamic sliding window
Download scientific diagram | HPPC test of lithium-ion battery. from publication: A Simplified Fractional Order Equivalent Circuit Model and Adaptive Online Parameter Identification Method for ...
This paper describes a new curve-fitting lithium-ion battery parameter identification method for equivalent circuit models. The current pulse/relaxation test is carried …
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