Equivalent circuit models and parameter identification methods for lithium-ion capacitors

2019 ◽  
Vol 24 ◽  
pp. 100762 ◽  
Author(s):  
Shuang Song ◽  
Xiong Zhang ◽  
Chen Li ◽  
Kai Wang ◽  
Xianzhong Sun ◽  
...  
Keyword(s):  
Parameter Identification ◽  
Equivalent Circuit ◽  
Lithium Ion ◽  
Identification Methods ◽  
Equivalent Circuit Models

scholarly journals A Simplified Fractional Order Equivalent Circuit Model and Adaptive Online Parameter Identification Method for Lithium-Ion Batteries

2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Jianlin Wang ◽  
Le Zhang ◽  
Dan Xu ◽  
Peng Zhang ◽  
Gairu Zhang
Keyword(s):  
Parameter Identification ◽  
Least Squares ◽  
Equivalent Circuit ◽  
Fractional Order ◽  
Equivalent Circuit Model ◽  
Lithium Ion ◽  
Circuit Model ◽  
Stability And Convergence ◽  
Battery Management System ◽  
Identification Method

In order to improve the battery management system performance and enhance the adaptability of the system, a fractional order equivalent circuit model of lithium-ion battery based on electrochemical test was established. The parameters of the fractional order equivalent circuit model are identified by the least squares parameter identification method. The least squares parameter identification method needs to rely on the harsh test conditions of the laboratory, and the parameter identification result is static; it cannot adapt to the characteristics of the lithium battery under dynamic conditions. Taking into account the dynamic changes of lithium batteries, a parameter adaptive online estimation algorithm for fractional equivalent circuit model is proposed. Based on the theory of fractional order calculus and indirect Lyapunov method, the stability and convergence of the estimator are analyzed. Finally, simulation experiments show that this method can continuously estimate the parameters of the fractional order equivalent circuit under UDDS conditions.

scholarly journals Comparative Study on Parameter Identification Methods for Dual-Polarization Lithium-Ion Equivalent Circuit Model

Energies ◽  
2019 ◽  
Vol 12 (21) ◽  
pp. 4031 ◽  
Author(s):  
Theodoros Kalogiannis ◽  
Md Hosen ◽  
Mohsen Sokkeh ◽  
Shovon Goutam ◽  
Joris Jaguemont ◽  
...  
Keyword(s):  
Parameter Identification ◽  
Heuristic Algorithms ◽  
Lithium Ion ◽  
Optimal Operation ◽  
Computational Time ◽  
Dual Polarization ◽  
Identification Methods ◽  
Wide Range ◽  
Li Ion ◽  
Time Accuracy

A lithium-ion battery cell’s electrochemical performance can be obtained through a series of standardized experiments, and the optimal operation and monitoring is performed when a model of the Li-ions is generated and adopted. With discrete-time parameter identification processes, the electrical circuit models (ECM) of the cells are derived. Over their wide range, the dual-polarization (DP) ECM is proposed to characterize two prismatic cells with different anode electrodes. In most of the studies on battery modeling, attention is paid to the accuracy comparison of the various ECMs, usually for a certain Li-ion, whereas the parameter identification methods of the ECMs are rarely compared. Hence in this work, three different approaches are performed for a certain temperature throughout the whole SoC range of the cells for two different load profiles, suitable for light- and heavy-duty electromotive applications. Analytical equations, least-square-based methods, and heuristic algorithms used for model parameterization are compared in terms of voltage accuracy, robustness, and computational time. The influence of the ECMs’ parameter variation on the voltage root mean square error (RMSE) is assessed as well with impedance spectroscopy in terms of Ohmic, internal, and total resistance comparisons. Li-ion cells are thoroughly electrically characterized and the following conclusions are drawn: (1) All methods are suitable for the modeling, giving a good agreement with the experimental data with less than 3% max voltage relative error and 30 mV RMSE in most cases. (2) Particle swarm optimization (PSO) method is the best trade-off in terms of computational time, accuracy, and robustness. (3) Genetic algorithm (GA) lack of computational time compared to PSO and LS (4) The internal resistance behavior, investigated for the PSO, showed a positive correlation to the voltage error, depending on the chemistry and loading profile.

scholarly journals Lithium Ion Batteries—Development of Advanced Electrical Equivalent Circuit Models for Nickel Manganese Cobalt Lithium-Ion

Energies ◽  
2016 ◽  
Vol 9 (5) ◽  
pp. 360 ◽  
Author(s):  
Alexandros Nikolian ◽  
Yousef Firouz ◽  
Rahul Gopalakrishnan ◽  
Jean-Marc Timmermans ◽  
Noshin Omar ◽  
...  
Keyword(s):  
Lithium Ion Batteries ◽  
Equivalent Circuit ◽  
Lithium Ion ◽  
Electrical Equivalent Circuit ◽  
Nickel Manganese ◽  
Equivalent Circuit Models
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