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.

Experimental Identification using Equivalent Circuit Model for Lithium-Ion Battery

2018 ◽  
Vol 19 (3) ◽  
Author(s):  
F. Eltoumi ◽  
A. Badji ◽  
M. Becherif ◽  
H. S. Ramadan
Keyword(s):  
Lithium Ion Battery ◽  
Equivalent Circuit ◽  
Control Strategies ◽  
Dynamic Performance ◽  
Equivalent Circuit Model ◽  
Lithium Ion ◽  
Circuit Model ◽  
Model Parameters ◽  
Battery Management System ◽  
Monitoring And Control

Abstract The modelling of Lithium-ion batteries is considered as a powerful tool for the introduction and testing of this technology in energy storage applications. In fact, new application domains for the battery technology have recently placed greater emphasis on their energy management, monitoring, and control strategies. Battery models have become an essential tool for the design of battery-powered systems; their usage includes battery state-of-charge (SoC), state-of-health (SoH) estimations, and battery management system design and battery characterization. This paper presents a method on how to estimate Lithium-Ion battery equivalent circuit model (ECM) parameters based on experimental characteristic measurements by charging and discharging the battery at different modes. The experiment is realized with a computer that realizes the control of charge and discharge via LabVIEWTM software. In this paper, tests are conducted on Lithium-Ion battery 18650 (nominal voltage of 3.7 V and nominal capacity of 2900 mAh) with the proposed method to evaluate the battery model parameters. The proposed method has the best dynamic performance and gives accurate parameter identification which enables the use of models to simulate the battery system performance.

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